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An overview of techniques for detecting software variability concepts in source code

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Angela Lozano
Angela Lozano

The document discusses techniques for detecting software variability in source code. It describes key concepts related to variability including features, feature diagrams, mandatory vs optional features, and feature dependencies. It also discusses how mining source code can help identify variable features, variants selected by triggers, and feature dependencies. The document provides examples of how pre-processor directives in code specify selection of variants and notes triggers do not necessarily store the selection of a variant.

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An Overview of Techniques for Detecting SoftwareVariability Concepts in Source Code Angela Lozano 1/30
Variability • Customized and Affordable • Maximize reuse of common features • e.g. reuse hw. customize with sw. • e.g. sw families = { similar apps with shared provenance } • e.g. context-aware, fault tolerant and intelligent apps 2/30
Variability 2/30
Why mining for variability? • To recuperate from architectural degradation • To expand a successful single product to new markets ! • Cost-benefit assessment of variation ⚖ • Effect of a variation in the development of the product! 3/30
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 4/30 Variable features
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 4/30 Variable features
5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] ⚖! 6/30
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] ⚖! 6/30 Code that varies Variables that trigger changes
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes Which parts of code are chosen by which triggers: selection of variants Which trigers are subsumed by other triggers: dependencies
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X X: No relation with features X: Need a specific syntax for the configuration of the products X:A trigger does not necessarily store the selection of a variant #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes Which parts of code are chosen by which triggers: selection of variants Which trigers are subsumed by other triggers: dependencies
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 [Hummel RSSE 10] !
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) [Hummel RSSE 10] !
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Count same signatures for classes with similar names
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) Missing methods in the class: common functionality [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Some occasional methods: variants? Count same signatures for classes with similar names
Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain X: Business-specific concepts are likely to be missing in the database. 7/30 Name of a Class Database of classes & their methods (OSS) Missing methods in the class: common functionality [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Some occasional methods: variants? Count same signatures for classes with similar names
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 8/30 Variable features
Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature Can a variable feature have several variants? YES: Multiple / NO: Single YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Variant: option available for a variable feature Can a variable feature have several variants? YES: Multiple / NO: Single YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 [Faust SPE 03]
Their source code repository Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 [Faust SPE 03] Several products of the same domain
Their source code repository Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences [Faust SPE 03] Several products of the same domain
Their source code repository Metrics per SCE - Placement of a SCE: mandatory/ optional features, Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences [Faust SPE 03] Several products of the same domain
Their source code repository Metrics per SCE - Placement of a SCE: mandatory/ optional features, Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences X: Cannot identify dependencies X: No support for refactoring [Faust SPE 03] Several products of the same domain
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 [Mende CSMR 04]
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain [Mende CSMR 04] App. w. basic functionality of the domain
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
Metrics per SCE - How to merge a variant into the basic product: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
Metrics per SCE - How to merge a variant into the basic product: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 X: No support for non-corresponding code X: Cannot identify dependencies X: No link to feature diagram One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 [Frenzel WCRE 07]
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain [Frenzel WCRE 07] App. w. basic functionality of the domain
Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
Metrics per SCE - How to merge several variants into a product line: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
Metrics per SCE - How to merge several variants into a product line: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 X: No support for non-corresponding code X: Cannot identify dependencies X: No link to feature diagram Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 16/30 Variable features
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
18/30 [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension
18/30 Several products of the domain Starting SCEs [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension
18/30 Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
Feature diagram of the domain: mandatory/ optional features, single/multiple variable features 18/30 Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
Feature diagram of the domain: mandatory/ optional features, single/multiple variable features 18/30 X: Low-level diagram X: Cannot identify dependencies X: Results depend on the variety of the products of the domain Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
19/30 Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] !
19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! Consolidate features
19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
Feature diagram of the domain: mandatory/ optional features, exclusive/ inclusive variants 19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
Feature diagram of the domain: mandatory/ optional features, exclusive/ inclusive variants 19/30 X: Cannot identify dependencies X: Results depend on the variety of the products of the domain Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 20/30 Variable features
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] !
Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] !
Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
Variability analysis: (un)acceptable feature tangling Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
Variability analysis: (un)acceptable feature tangling X: Cannot mine for require & exclude relations Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Egyed ICSE 01]!
Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Egyed ICSE 01]!
Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario [Egyed ICSE 01]!
Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap [Egyed ICSE 01]!
Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature [Egyed ICSE 01]!
Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
Variability analysis: Overlap, sub- features, equivalence Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
Variability analysis: Overlap, sub- features, equivalence X: Cannot mine for require & exclude relations Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Jaring PhD 05] ⚖!
24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
Variability analysis: configuration dependencies 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
Variability analysis: configuration dependencies X: Need a specific syntax for the configuration of the products X: Just define when the relations occur. No mining proposed. 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. ⚖!
Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. ⚖! Mapping of SCEs to feature diagram
Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. Association rules = belief (frequent interpretation) ⚖! Mapping of SCEs to feature diagram
Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
Feature diagram of the domain: mandatory/optional features, exclusive/inclusive variants Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
Feature diagram of the domain: mandatory/optional features, exclusive/inclusive variants X: Results depend on the variety of the products of the domain Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] ⚖!
Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] ⚖!
Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Aspect or Var. feature B C ⚖!
Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts ⚖!
Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants ⚖!
Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
Feature diagram of the domain: mandatory/ optional features, single/multiple variable features Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
Feature diagram of the domain: mandatory/ optional features, single/multiple variable features X:Assumes implementation with aspects. X: Used to detect order or invalid configs. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 27/30 Variable features
Variant: option available for a variable feature Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Feature: unit/increment of functionality Mandatory: required in all products Variable: customization required Variation point: placeholder that stores the variant of a variable feature Binding: assigning a variant to a variation point ? 28/30
Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 [Thummalapenta MSR 08]!
Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 [Thummalapenta MSR 08]!
Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 otherwise Set type of Ci to TEMPLATE; } 5:Group Ci of the same type into hierarchies based on inheritance; 6:Associate hook hierarchies to template hierarchies; 7:Define dependencies between template hierarchies; 8:Output hook and template hierarchies as hotspot hierarchies; Fig. 5. Algorithm used for detecting hotspots through computed UsageMetrics pr m an cl ho te sh cl cl ba a cl hi cl st Y w de A tw fie if cl de fo us SB IN=instantiations EX=extensions OV=overrides IM=implementations UM=usages (+ above) rank & classify SCEs in the framework based on metrics: [Thummalapenta MSR 08]!
How to extend a framework: hotspots/hooks ➜ variation points cold-spots/templates ➜ mandatory part of the variable feature users of hooks ➜ variants Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 otherwise Set type of Ci to TEMPLATE; } 5:Group Ci of the same type into hierarchies based on inheritance; 6:Associate hook hierarchies to template hierarchies; 7:Define dependencies between template hierarchies; 8:Output hook and template hierarchies as hotspot hierarchies; Fig. 5. Algorithm used for detecting hotspots through computed UsageMetrics pr m an cl ho te sh cl cl ba a cl hi cl st Y w de A tw fie if cl de fo us SB IN=instantiations EX=extensions OV=overrides IM=implementations UM=usages (+ above) rank & classify SCEs in the framework based on metrics: [Thummalapenta MSR 08]!
An overview of techniques for detecting software variability concepts in source code
An overview of techniques for detecting software variability concepts in source code

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An overview of techniques for detecting software variability concepts in source code

  • 1. An Overview of Techniques for Detecting SoftwareVariability Concepts in Source Code Angela Lozano 1/30
  • 2. Variability • Customized and Affordable • Maximize reuse of common features • e.g. reuse hw. customize with sw. • e.g. sw families = { similar apps with shared provenance } • e.g. context-aware, fault tolerant and intelligent apps 2/30
  • 4. Why mining for variability? • To recuperate from architectural degradation • To expand a successful single product to new markets ! • Cost-benefit assessment of variation ⚖ • Effect of a variation in the development of the product! 3/30
  • 5. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 4/30 Variable features
  • 6. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 4/30 Variable features
  • 7. 5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 8. 5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 9. 5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 10. 5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 11. 5/30 some products of the same domain Feature: unit/increment of functionality Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 12. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] ⚖! 6/30
  • 13. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] ⚖! 6/30 Code that varies Variables that trigger changes
  • 14. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes
  • 15. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes Which parts of code are chosen by which triggers: selection of variants Which trigers are subsumed by other triggers: dependencies
  • 16. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain [Snelting TOSEM 96] UNIX DOS X_win BSD !BSD I X II X X III X X IV X X V X X: No relation with features X: Need a specific syntax for the configuration of the products X:A trigger does not necessarily store the selection of a variant #ifdef UNIX ...I ... #endif #if defined(X_win) && !defined(BSD) ...II... #endif #ifdef DOS #ifdef X_win ...III... #endif #ifdef BSD ...IV... #endif ...V... #endif ⚖! 6/30 Code that varies Variables that trigger changes Which parts of code are chosen by which triggers: selection of variants Which trigers are subsumed by other triggers: dependencies
  • 17. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 [Hummel RSSE 10] !
  • 18. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) [Hummel RSSE 10] !
  • 19. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Count same signatures for classes with similar names
  • 20. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain 7/30 Name of a Class Database of classes & their methods (OSS) Missing methods in the class: common functionality [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Some occasional methods: variants? Count same signatures for classes with similar names
  • 21. Car Transmission Engine Manual Suspension Gasoline Car Transmission Engine Extras Automatic Electric Cruise Suspension Car Horsepow Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension Mining products of the same domain X: Business-specific concepts are likely to be missing in the database. 7/30 Name of a Class Database of classes & their methods (OSS) Missing methods in the class: common functionality [Hummel RSSE 10] ! signatures amongst the first 100 results, as delivered by the search engine for various example queries. A reasonable threshold for accepting a signature as common enough for the design prompter seemed to require it to appear at least 20 times amongst the 100 considered results. In cases where there were fewer than six signatures above this value we added the following results in gray color to the table. Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 delivered results. Besides a number of further ideas proving the intersection algorithm we discuss in 5, it clear that hiding common signatures such as the ones ming from main methods or methods inherited from Object might further improve the user experience as for example offering the possibility to retrieve the fol most frequent signatures that are initially not show more. It should be obvious that common abstractions s ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d Table 1: Exemplary interface recommendations. Search Term(s) Averaged Interface # Matrix add Matrix ≈ 90 msec transpose():Matrix; 45 8, 844 results add(Matrix):Matrix; 39 732 methods toString():String; 39 multiply(Matrix):Matrix; 35 add(Matrix):void; 27 swapRows():Matrix; 24 BinaryTree BinaryTree ≈ 50 msec isEmpty():boolean; 35 1, 273 results main(String[]):void; 27 387 methods toString():String; 24 size():int; 21 height():int; 14 makeEmpty():void; 12 Stack Stack ≈ 40 msec push(Object):void; 48 68, 718 results pop():Object; 47 113 methods isEmpty():boolean; 34 toString():String; 22 pop():int; 20 push(int):void; 20 Deck Deck ≈ 50 msec shuffle():void; 55 3, 238 results dealCard():Card; 23 323 methods toString():String; 19 getCard():Card; 17 cardsLeft():int; 16 main(String[]):void; 10 CreditCard CreditCard ≈ 40 msec getNumber():String; 30 1, 148 results getCardNumber():String; 22 229 methods toString():String; 20 setCardNumber(String):void; 13 getCardType():String; 13 setNumber(String):void; 12 In addition to that, the table shows in the right row how often each signature appeared, while the left row includes the information how much time the calculation of the inter- face intersections required and how many unique signatures respectively how many results were found for each query. Our test system contained a dual core processor with 2.8 GHz and 6 GB RAM on which this algorithm works reason- ably fast. In other words, its response time of far less than a second is clearly sufficient to create recommendations for a proactive design prompter on the fly. 4.2 Discussion ”stack” deliver far better results than a search for mon programming term such as ”public”, but that is in the nature of things. Hence, identifying situations this technology can become helpful in practice in the should also be on the research agenda as performin meaningful evaluations that give a clear indication how ful it is in terms of an increased development velocity facilitating early completeness of software designs. In tion, the following section discusses some technical re directions we have identified so far in more detail. 5. ONGOING & FUTURE WORK In the previous sections we have given an insight i cent findings derived from preliminary experiments w approach. Although we have presented a prototype mentation which adds additional value to the Eclips this is still closely tied to the coding phase of softw velopment. Nevertheless, there is still potential for enhancements of the approach and broadening the fu ality from solely the implementation phase to the phase as well has the potential to significantly boos in the context of the early software life cycle. It sho feasible to generate useful hints for class or objects va (i.e. attributes) with similar techniques and it is eve ceivable to recognize specific idioms in the source c operations and to derive corresponding hints for d ers such as ”other developers used two nested for lo implement a bubblesort operation”. Since code-level are only the smallest group in the common pattern c cation by Buschmann et al. [5] it also seems feasible the abstraction level and to recognize and recomme sign or even architectural patterns that are common together with a given concept in the future. As sh another publication [14], Code Conjurer supports reu ommendations based upon UML class diagrams draw the help of appropriate Eclipse plug-ins. This featu also be used in conjunction with our prototypical imp tation of the design prompter. However, there is sp further enhancements, such as the presentation of the recommendations which is currently limited to ind classes. Therefore, a future release of the plug-in will UML representation of component design recommend as well as automatically create diagrams showing m classes and their relations. This will give developers a of an architectural design, derived from components Some occasional methods: variants? Count same signatures for classes with similar names
  • 22. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 8/30 Variable features
  • 23. Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
  • 24. Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
  • 25. Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
  • 26. Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
  • 27. Feature: unit/increment of functionality 9/30 Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Required in all (Mandatory) or in some (Optional) products
  • 28. Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 29. Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 30. Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 31. Variable: if customization is required Feature: unit/increment of functionality 10/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 32. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 33. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 34. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 35. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 36. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 37. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 38. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 39. Feature: unit/increment of functionality 11/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Variant: option available for a variable feature Variable: if customization is required
  • 40. Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 41. Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 42. Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 43. Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 44. Variant: option available for a variable feature YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 45. Variant: option available for a variable feature Can a variable feature have several variants? YES: Multiple / NO: Single YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 46. Variant: option available for a variable feature Can a variable feature have several variants? YES: Multiple / NO: Single YES: Mutually inclusive / NO:Mutually exclusive Feature: unit/increment of functionality Variable: if customization is required 12/30 Required in all (Mandatory) or in some (Optional) products Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension
  • 47. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 [Faust SPE 03]
  • 48. Their source code repository Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 [Faust SPE 03] Several products of the same domain
  • 49. Their source code repository Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences [Faust SPE 03] Several products of the same domain
  • 50. Their source code repository Metrics per SCE - Placement of a SCE: mandatory/ optional features, Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences [Faust SPE 03] Several products of the same domain
  • 51. Their source code repository Metrics per SCE - Placement of a SCE: mandatory/ optional features, Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 13/30 local layer regional layer global layer U L V S M C C Utilization = Users of the SCE Length = LOC Complexity = McCabe Volatility = 0.7 * changes last year + 0.3 * exp. changes this year Specificity = LOCs per variation Mitosis = % clone differences X: Cannot identify dependencies X: No support for refactoring [Faust SPE 03] Several products of the same domain
  • 52. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 [Mende CSMR 04]
  • 53. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain [Mende CSMR 04] App. w. basic functionality of the domain
  • 54. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
  • 55. Metrics per SCE - How to merge a variant into the basic product: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
  • 56. Metrics per SCE - How to merge a variant into the basic product: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 14/30 X: No support for non-corresponding code X: Cannot identify dependencies X: No link to feature diagram One product of the domain max(|f1|, |f2|)-LD(f1,f2) |f1| sim(f1,f2) = FI: Identical Functions (sim=1) FS: Similar Functions (0<sim<1) |FI| = 1: Identical correspondence |FI| > 1: Multiple correspondence |FI| = 0 & |FS| = 1: Single variant |FI| = 0 & |FS| > 1: Multiple variant |FI| = 0 & |FS| =0: No correspondence LD = Levenshtein Distance [Mende CSMR 04] App. w. basic functionality of the domain
  • 57. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 [Frenzel WCRE 07]
  • 58. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain [Frenzel WCRE 07] App. w. basic functionality of the domain
  • 59. Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
  • 60. Metrics per SCE - How to merge several variants into a product line: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
  • 61. Metrics per SCE - How to merge several variants into a product line: mandatory/ optional functions, single/multiple variable features Mining for variable & mandatory features Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 15/30 X: No support for non-corresponding code X: Cannot identify dependencies X: No link to feature diagram Several products of the domain LD(f1,f2) max(|f1|, |f2|) sim(s1,s2) = 1- Mn,i ∩ Mn,j Mn,i ∪ Mn,j Mn= Dn,i ∩ Dn,j Dn,i ∪ Dn,j Dn= Mni = Modules for variant i at nesting n Dni = Dependencies for variant i at nesting n IF entities are identical->‘kernel’ IF variant in all products -> ‘variant’ IF variant in some products -> ‘optional’ [Frenzel WCRE 07] App. w. basic functionality of the domain
  • 62. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 16/30 Variable features
  • 63. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
  • 64. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
  • 65. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
  • 66. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
  • 67. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension YES: Optional / NO:Alternative variants Is the corresponding variable feature required? 17/30
  • 68. 18/30 [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension
  • 69. 18/30 Several products of the domain Starting SCEs [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension
  • 70. 18/30 Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
  • 71. Feature diagram of the domain: mandatory/ optional features, single/multiple variable features 18/30 Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
  • 72. Feature diagram of the domain: mandatory/ optional features, single/multiple variable features 18/30 X: Low-level diagram X: Cannot identify dependencies X: Results depend on the variety of the products of the domain Several products of the domain Starting SCEs ![1] typedThread <fieldOfType: ’Thread’> [1] initializesThread <assignedNew: ’Thread(IRunnable)’> [1] nullifiesThread <assignedNull> [0..*] parameter <callsReceived: ’getParameter(String)’> [0..1] name (String) <valueOfArg: 1> [1] providesParameterInfo <methods: ’getParameterInfo()’> Table 4 Fragment of the metamodel of the Struts FSML FSML Feature <Pattern Expression> [0..*] Action <class> ![1] extendsAction <assignableTo: ’Action’> [0..1] extendsDispatchAction <assignableTo: ’DispatchAction’> [0..*] actionMethod <methods: ’*(ActionMapping, ActionForm, [. . . ], [. . . ])’> [0..1] overridesExecute <methods: ’execute(ActionMapping, ActionForm, [. . . ])’> [0..*] forwardImpl <callsTo: ’findForward(String)’> [1] name (String) <valueOfArg: 1> to. Values of the parameters can also be the patterns that other features corresp to, in which case, the features need to be specified using path expressions. For ex ple, the pattern expression attached to the feature deregistersSameObjec Table 3 requires two method calls and uses paths “../../registers” and “ to retrieve calls that the features registers and deregisters correspond t We present the metamodels for two reasons: (i) to give the reader example [Antiweckz JASE 09] ! Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Mapping of entities → operations done over the data (SCqueries)
  • 73. 19/30 Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] !
  • 74. 19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! Consolidate features
  • 75. 19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
  • 76. Feature diagram of the domain: mandatory/ optional features, exclusive/ inclusive variants 19/30 Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
  • 77. Feature diagram of the domain: mandatory/ optional features, exclusive/ inclusive variants 19/30 X: Cannot identify dependencies X: Results depend on the variety of the products of the domain Several products of the domain Mapping of concepts Mining for feature diagrams Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Yang WCRE 09] ! '98&15&80+&9+31=+9+;&5+'8.9+&>89.38.9+&S+519+&9+31$>89.38"1$ Consolidate features Mapping of entities → operations done over the data (DB access) + FCA
  • 78. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 20/30 Variable features
  • 79. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
  • 80. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
  • 81. Car Transmission Engine Manual Suspension Gasoline Car Horsepower Transmission Engine Extras Manual Gasoline Air Conditioning Cruise Suspension Car Horsepower Transmission Engine Extras Automatic GasolineElectric Air Conditioning Cruise Suspension basic car motor-head car executive car eco-aware car Car Transmission Engine Extras Automatic Electric Cruise Suspension Feature Diagram Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Are there constraints (dependencies) among them ? Requires: 1st = 2nd one / Excludes: 1st or 2nd 21/30
  • 82. 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] !
  • 83. Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] !
  • 84. Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
  • 85. Variability analysis: (un)acceptable feature tangling Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
  • 86. Variability analysis: (un)acceptable feature tangling X: Cannot mine for require & exclude relations Single app. Mapping of tokens to features & files to features 22/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Lai OOPSLA 99] ! Spread (f) = 5 / 20 Tangle(f) =250/500 Density(f) = 500/3 .* x 500 .... x 250 Overlap Order ✔ ✘ .. ....✔ ✘ Metrics per feature
  • 87. 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Egyed ICSE 01]!
  • 88. Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Egyed ICSE 01]!
  • 89. Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario [Egyed ICSE 01]!
  • 90. Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap [Egyed ICSE 01]!
  • 91. Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature [Egyed ICSE 01]!
  • 92. Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
  • 93. Variability analysis: Overlap, sub- features, equivalence Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
  • 94. Variability analysis: Overlap, sub- features, equivalence X: Cannot mine for require & exclude relations Traces of several scenarios (execution of feature) 23/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension scenarios from Table 1 using the Rational PureCoverage tool. By a footprint we mean the classes that were executed while testing a scenario. The numbers in Table 2 indicate how many methods of each class were used. For instance, scenario “A” used ten methods of the class CAboutDlg and three methods of the class CSettingsDlg. Table 2 does not display the actual methods in order to reduce the complex- ity of this example (the footprint graph shown later would otherwise get too big). Nevertheless, by only using classes the generated traces will still be useful, albeit, course- grained. If more fine-grained traces are needed then trace quires only a fairly limited amount of hypothe information; otherwise, the cost of using it wo high. Table 4 and Table 3 show a list of twelve hypothesized. We assume that most traces are a tially correct; however, our approach can pinp traces plus create new ones by matching the de information against the observed trace informat traces, together with the trace observations that matically generated (Table 2) can now be used reasoning. 5 ATOMIZING In order to reason about traces and how the model elements, we need to intertwine scenar elements, their footprints, and hypothesized trac tion. In order to do this, we have devised a footp Figure 3 depicts the complete footprint graph fo scenarios in Table 1. This graph also forms the for the remaining activities of our approach: G and Refining. One property that graph has is that footprints o trace information are split up into as many nodes to explicitly represent all possible overlaps betw ios (overlaps are footprints that any two scenar Table 2. Observeable Scenario Footprints A B C D E F G H CAboutDlg 0 10 10 CILLDB 1 3 2 2 2 4 CILLDBSet 2 4 4 mailreader 3 3 4 7 1 1 5 1 parsing 4 6 6 POP3 5 8 10 2 2 2 11 1 CPOP3Dlg 6 4 4 1 4 4 4 CAPP 7 1 1 CMainWin 8 3 5 5 3 6 7 5 CSettingsDlg 9 15 Class Scenario Overlap Sub-feature Equivalence [Egyed ICSE 01]!
  • 95. 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Jaring PhD 05] ⚖!
  • 96. 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
  • 97. 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
  • 98. Variability analysis: configuration dependencies 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
  • 99. Variability analysis: configuration dependencies X: Need a specific syntax for the configuration of the products X: Just define when the relations occur. No mining proposed. 24/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension IF !vpx ➜ vpy IF vpx ➜ (vpy,vyn) IF (vpx,vxm) ➜ !vpy IF (vpx,vxm) ➜ (vpy,vyn) Dependencies variation points - variants: [Jaring PhD 05] ⚖! Code that varies Variables representing variants (vxm vyn) Variables representing variation points (vpx vpy)
  • 100. 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. ⚖!
  • 101. Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. ⚖! Mapping of SCEs to feature diagram
  • 102. Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. Association rules = belief (frequent interpretation) ⚖! Mapping of SCEs to feature diagram
  • 103. Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
  • 104. Feature diagram of the domain: mandatory/optional features, exclusive/inclusive variants Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
  • 105. Feature diagram of the domain: mandatory/optional features, exclusive/inclusive variants X: Results depend on the variety of the products of the domain Several products of the domain 25/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Czarnecki PLC 08] on start off init on must override destroy off stop off Applet paint [75%] start [59%] destroy [42%] stop [53%] init [97%] Applet destroy encourages init start encourages stop stop encourages start init encourages destroy stop given start [84%] start given stop [97%] paint given destroy [88%] paint given stop [88%] init given start [97%] init given paint [98%] (a) A PFM specified by an expert (b) An automatically mined PFM (c) Interactive Configuration Figure 2. A PFM of Java applets: specification, mining, and configuration rt from being interpreted as belief measures, prob- s can also be given a frequentist interpretation, in a probability is viewed as the relative frequency of a particular outcome of an experiment in a large of trials. This perspective on probability naturally now included with complete certainty. The other bars show the probabilities of the remaining features. This could of course be visualized differently; for example by updating the most probable defaults in a form, or by prioritizing sev- eral most likely choices at the top of a drop-down list. p (A|B) = p (AB) / p(A) = (A ∩ B /A∪B) / (A) req = p(A|B) exc = p(!A|B) ⚖! Mapping of SCEs to feature diagram
  • 106. 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] ⚖!
  • 107. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] ⚖!
  • 108. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Aspect or Var. feature B C ⚖!
  • 109. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts ⚖!
  • 110. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants ⚖!
  • 111. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
  • 112. Feature diagram of the domain: mandatory/ optional features, single/multiple variable features Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
  • 113. Feature diagram of the domain: mandatory/ optional features, single/multiple variable features X:Assumes implementation with aspects. X: Used to detect order or invalid configs. Several products of the domain 26/30 Mining for variability dependencies Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension [Parra ECSA 10] Model A Var. points Aspect or Var. feature B C -Pointcuts-Advices -Variants A reqs B pc (A) ∩ m(B) B exc C pc (B) ∩ pc(C) ⚖!
  • 114. Variability Feature Feature Diagram Mandatory vs. Optional features Feature dependencies Variants Variation points Binding Domain instances Optional vs. Alternative variants Single vs. Multiple features 27/30 Variable features
  • 115. Variant: option available for a variable feature Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension Feature: unit/increment of functionality Mandatory: required in all products Variable: customization required Variation point: placeholder that stores the variant of a variable feature Binding: assigning a variant to a variation point ? 28/30
  • 116. Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 [Thummalapenta MSR 08]!
  • 117. Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 [Thummalapenta MSR 08]!
  • 118. Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 otherwise Set type of Ci to TEMPLATE; } 5:Group Ci of the same type into hierarchies based on inheritance; 6:Associate hook hierarchies to template hierarchies; 7:Define dependencies between template hierarchies; 8:Output hook and template hierarchies as hotspot hierarchies; Fig. 5. Algorithm used for detecting hotspots through computed UsageMetrics pr m an cl ho te sh cl cl ba a cl hi cl st Y w de A tw fie if cl de fo us SB IN=instantiations EX=extensions OV=overrides IM=implementations UM=usages (+ above) rank & classify SCEs in the framework based on metrics: [Thummalapenta MSR 08]!
  • 119. How to extend a framework: hotspots/hooks ➜ variation points cold-spots/templates ➜ mandatory part of the variable feature users of hooks ➜ variants Several products using the same framework (i.e. of the same domain) Mining for variation points and variants Car Horsepower Transmission Engine Extras Automatic Manual GasolineElectric Requires Excludes Air Conditioning Cruise Mandatory Optional Exclusive Inclusive Suspension 29/30 otherwise Set type of Ci to TEMPLATE; } 5:Group Ci of the same type into hierarchies based on inheritance; 6:Associate hook hierarchies to template hierarchies; 7:Define dependencies between template hierarchies; 8:Output hook and template hierarchies as hotspot hierarchies; Fig. 5. Algorithm used for detecting hotspots through computed UsageMetrics pr m an cl ho te sh cl cl ba a cl hi cl st Y w de A tw fie if cl de fo us SB IN=instantiations EX=extensions OV=overrides IM=implementations UM=usages (+ above) rank & classify SCEs in the framework based on metrics: [Thummalapenta MSR 08]!