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What do Practitioners Expect from the Meta-modeling Tools? A Survey

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Modeling languages are defined with a meta-model, which are specified using the meta-modeling tools that produce the editors for specifying models in accordance with the meta-models. While many different meta-modeling tools have been available today, it is not yet clear what the expectations of practitioners are from the meta-modeling tools and what sort of challenges that practitioners face with. So, we designed and conducted a survey, which was responded by 103 practitioners from 24 different countries. The survey participants represent the different profiles of the population who differ in terms of the work industries, the problem domains, job positions, and years of experiences. Our survey investigates three important research questions, which essentially focus on the usage frequencies of the existing meta-modeling tools, practitioners’ expectations from the meta-modeling tools, and any challenges that practitioners face with. The survey questionnaire considers the notation, semantics, editor services, model-transformation, validation, testing, and composability requirements for meta-modeling tools.

The survey results lead to many interesting findings regarding the practical use of meta-modeling tools from different viewpoints. The survey also reveals many important challenges in each type of requirements. We strongly believe that the survey results are expected to be useful for anyone who consider developing their own DSMLs (domain-specific modeling languages) in understanding the top-used meta-modeling tools for different domains. Also, the tool vendors could use the survey results in learning the expectations of practitioners from the meta-modeling tools and any challenges encountered.

Assoc.Prof.Dr. Mert Ozkaya, Yeditepe University

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What do Practitioners Expect from the Meta-modeling Tools? A Survey

  1. 1. What Do Practitioners Expect fromthe Meta-modelling Tools? A Survey Mert Ozkaya Assoc.Prof.of Computer Engineeringat YeditepeUniversity ResearcherandConsultant onSoftwareEngineering Web-site:http://cse.yeditepe.edu.tr/~mozkaya E-mail:mozkaya@cse.yeditepe.edu.tr Linkedin:www.linkedin.com/in/mert-ozkaya 1
  2. 2. Scope of Research 1. Practitioners use meta-modelling tools to 1. design and develop modelling languages 2. develop model transformation tools 3. use existing modelling languages 2. Practitioners use modelling languages to 1. specify models and 2. process models for, e.g., early analysis and code generation 3. Practitioners use models for 1. abstraction and managing complexity 2 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  3. 3. Scope of Research • We are interested in understanding practitioners’ • perspectives, • expectations, and • challenges towards meta-modelling tools, meta-models & modelling languages, and models 3 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  4. 4. Practitioners – who are they? • A practitioner is someone who • uses/edits models • uses/edits meta-models • does not use/edit models and meta-models but do feel interested • Practitioners may hold diverse job positions • Including software developer, architect, consultant, manager, system engineer, analyst, etc. • Practitioners may vary depending on their • education level • work industries • experiences 4 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  5. 5. Practitioners’ approach towards modelling and modelling languages • Possible questions to be investigated • Practitioners’ understanding towards modelling • Practitioners’ expectations from modelling • Practitioners’ challenges in modelling • Practitioners’ perspectives towards different modelling techniques • E.g., software architectures, design patterns, object-oriented modelling, etc. • Practitioners’ perspectives towards different types of modelling languages • E.g., UML, formal languages, and ADLs • Practitioners’ perspectives towards applying models at particular domains • E.g., embedded domain • The good thing is: The literature already includes several empirical researches • Many survey papers with interesting results 5 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  6. 6. Modelling Surveys -1 1. G. Liebel, N. Marko, M. Tichy, A. Leitner, J. Hansson, Model-based engineering in the embedded systems domain: an industrial survey on the state-of-practice, Software and Systems Modeling 17 (1) (2018) 2. L. T. W. Agner, I. W. Soares, P. C. Stadzisz, J. M. Sim~aO, A brazilian survey on uml and model-driven practices for embedded software development, J. Syst. Softw. 86 (4) (2013) 3. M. Torchiano, F. Tomassetti, F. Ricca, A. Tiso, G. Reggio, Preliminary findings from a survey on the md state of the practice, in: Proceedings of the 2011 International Symposium on Empirical Software Engineering and Measurement, ESEM '11, IEEE Computer Society, USA, 2011 4. J. Whittle, J. E. Hutchinson, M. Rounceeld, The state of practice in model-driven engineering, IEEE Softw. 31 (3) (2014) 5. P. Mohagheghi, W. Gilani, A. Stefanescu, M. A. Fernandez, An empirical study of the state of the practice and acceptance of model-driven engineering in four industrial cases, Empir. Softw. Eng. 18 (1) (2013) 6. F. Tomassetti, M. Torchiano, A. Tiso, F. Ricca, G. Reggio, Maturity of software modelling and model driven engineering: A survey in the italian industry, in: M. T. Baldassarre, M. Genero, E. Mendes, M. Piattini (Eds.), 16th International Conference on Evaluation & Assessment in Software Engineering, EASE 2012, Ciudad Real, Spain, May 14-15, 2012. Proceedings, IET - The Institute of Engineering and Technology/ IEEE Xplore, 2012 7. D. Akdur, V. Garousi, O. Demir•ors, A survey on modeling and modeldriven engineering practices in the embedded software industry, Journal of Systems Architecture - Embedded Systems Design 91 (2018) 8. D. Bork, D. Karagiannis, B. Pittl, A survey of modeling language specification techniques, Inf. Syst. 87 (2020) 9. J. Cabot, E. Teniente, Constraint support in MDA tools: A survey, in: A. Rensink, J. Warmer (Eds.), Model Driven Architecture - Foundations and Applications, 2nd European Conference, ECMDAFA 2006, Bilbao, Spain, July 10-13, 2006, Proceedings, Vol. 4066 of Lecture Notes in Computer Science, Springer, 2006 10. R. F. Paige, D. Varro, Lessons learned from building model-driven development tools, Softw. Syst. Model. 11 (4) (2012) 11. J. L. Perez-Medina, S. Dupuy-Chessa, A. Front, A survey of model driven engineering tools for user interface design, in: M. Winckler, H. Johnson, P. A. Palanque (Eds.), Task Models and Diagrams for User Interface Design, 6th International Workshop, TAMODIA 2007, Toulouse, France, November 7-9, 2007, Proceedings, Vol. 4849 of Lecture Notes in Computer Science, Springer, 2007 6 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  7. 7. Modelling Surveys - 2 12. I. Malavolta, P. Lago, H. Muccini, P. Pelliccione, A. Tang, What industry needs from architectural languages: A survey, IEEE Trans. Software Eng. 39 (6) (2013) 13. M. Ozkaya, Do the informal & formal software modeling notations satisfy practitioners for software architecture modeling?, Information & Software Technology 95 (2018) 14. P. C. Clements, A survey of architecture description languages, in: Proceedings of the 8th International Workshop on Software Specification and Design, IWSSD '96, IEEE Computer Society, Washington, DC, USA, 1996 15. M. Ozkaya, What is software architecture to practitioners: A survey, in: S. Hammoudi, L. F. Pires, B. Selic, P. Desfray (Eds.), MODELSWARD 2016 - Proceedings of the 4rd International Conference on Model-Driven Engineering and Software Development, Rome, Italy, 19-21 February, 2016., 35 SciTePress, 2016 16. A. Forward, T. C. Lethbridge, Perceptions of software modeling: A survey of software practitioners, Tech. Rep. TR-2008-07, School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, Canada K1N 6N5 (2008) 17. G. Liebel, N. Marko, M. Tichy, A. Leitner, J. Hansson, Model-based engineering in the embedded systems domain: an industrial survey on the state-of-practice, Software & Systems Modeling 17 (1) (2018) 18. P. Mohagheghi, V. Dehlen, Where is the proof? - a review of experiences from applying mde in industry, in: I. Schieferdecker, A. Hartman (Eds.), Model Driven Architecture Foundations and Applications, Springer Berlin Heidelberg, Berlin, Heidelberg, 2008 19. T. Berger, R. Rublack, D. Nair, J. M. Atlee, M. Becker, K. Czarnecki, A. Wasowski, A survey of variability modeling in industrial practice, in: Proceedings of the Seventh International Workshop on Variability Modelling of Software-intensive Systems, VaMoS '13, ACM, New York, NY, USA, 2013 20. C. F. J. Lange, M. R. V. Chaudron, J. Muskens, In practice: Uml software architecture and design description, IEEE Software 23 (2) (2006) 21. F. Tomassetti, M. Torchiano, A. Tiso, F. Ricca, G. Reggio, Maturity of software modelling and model driven engineering: A survey in the italian industry, in: 16th International Conference on Evaluation Assessment in Software Engineering (EASE 2012), 2012 7 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  8. 8. Practitioners’ approach towards meta-modelling • Many research questions again.. • Practitioners’ understanding towards meta- modelling • Practitioners’ expectations from meta-modelling • Practitioners’ challenges in meta-modelling • Practitioners’ perspectives towards different meta-modelling tools • Practitioners’ perspectives towards applying meta-models at particular domains such as embedded domain • However, the literature does not really consider answering those research questions • Lack of survey studies on practitioners and meta- modelling • The current works focus more on • analysing the existing meta-modelling tools for some requirements and • proposing a taxonomy of requirements for meta- modelling tools 8 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  9. 9. Our Goal We aim at answering three important research questions 1. What are the usage frequencies of the existing meta-modelling tools in different problem domains? 2. What do practitioners expect from the meta-modelling tools? 3. What are the challenges that practitioners face with on their meta-modelling activities? 9 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey A survey has been designed and executed on a number of practitioners
  10. 10. Survey on Meta-Modelling Tool Requirements • Question: • How can we determine the meta-modelling tool requirements that we focus on our survey? • Answer: • Erdweg S. et al. (2013) The State of the Art in Language Workbenches. In: Erwig M., Paige R.F., Van Wyk E. (eds) Software Language Engineering. SLE 2013. Lecture Notes in Computer Science, vol 8225. Springer, Cham. • A feature model proposed out of the language workbench workshops conducted in between 2011 and 2013 • Consisting of the meta-modelling tool features 10
  11. 11. Category of Requirements for the Meta-modelling Tools • Language definition • Notation • Textual, graphical, tabular, matrix, map • Semantics • Translational (model-to-text, model-to- model) and interpretative • Modelling editors • Editing mode • Free-form and projectional • Syntactic services • Highlighting, outline, folding, syntactic completion, diff, auto formatting, etc. • Semantic services • Semantic completion, refactoring, error marking, quick fixes, live translation, etc. 11 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey • Language validation • Structural and semantic validations • Language testing • Testing the language definitions, editors, validation rules, etc. • Language composability • Composing the language definitions, editors, validation rules, etc.
  12. 12. Survey Design • We prepared 25 different questions • 5 profile questions • Countries, job positions, work industries, domains, and experiences • 1 question for understanding the tool usage frequencies • A set of questions for each category of requirements • Multiple-choice questions for understanding participants’ thoughts on the tool requirement • A free-text question for understanding the challenges 12 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey A pilot study conducted with a small set of academics and practitioners Many issues avoided: • inconsistency and completeness of the research questions wrt the survey questions, • any missing, ambiguous, or redundant questions and answers, • the coherence of the survey sections, • the correctness of the answer formats, • the appropriateness of the time needed to complete the survey New requirements added • Model transformation/code-generation
  13. 13. Survey Execution • The survey made available online via google-forms • The survey accessible in between June 2020 and August 2020 13 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey To spread the survey, • Personal contacts • Past R&D project members with many industrial partners and past work experiences on software and systems modelling • Mailing lists • Eclipse modelling platforms • Netbeans mailing list • IEEE architecture description mailing list • AADL list • Practitioners who contributed to the conf./journal papers contacted by e-mail • Determined by searching the well-cited papers on google scholar • Linkedin groups on modeling • In total, 300 individuals have been contacted • We received 103 different participants from diverse countries and industries
  14. 14. Survey Results 14 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  15. 15. Participant Profiles • Participants from 24 different countries • Countries include • Austria, Belgium, Finland, France, Germany, Hungary, Italy, Poland, Portugal, Sweden, Turkey, the Netherlands, United Kingdom., Argentina, Brasil, China, Colombia, Japan, Iran, Israel, Taiwan, and USA, Australia, South Africa 15 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  16. 16. Participants' meta-modelling tool usages • Most practitioners use either of the five different meta-modeling tools • Sirius, • GEMS, • Metaedit+, • Xtext, and • Microsoft DSL tools • Among the top-five meta-modeling tools, • Sirius, Xtext, and GEMS are Eclipse-based tools • based on the Eclipse Modeling Framework (EMF) • Xtext is the only meta-modeling tool that offers a textual visualisation • Some tools are rarely used • ANTLR, ConceptBase, Melange, GEMOC, Graphiti, WebGME, Cameo, EVA, and JastEMF 16 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  17. 17. The correlations between the participants' domains and meta-modelling tool choice 17 • Some meta-modelling tools used for a few particular domains • ANTLR, GEMOC, EVA, Cameo, JastEMF, and Graphiti • While GME, Melange, and MPS are not among the frequently-used tools, • those tools preferred for various domains • In almost all the domains, the top-used meta-modelling tool is Metaedit+ • Except the embedded domain where the top- used meta-modelling tool is GEMS. Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  18. 18. The correlations between the participants' meta- modelling tool choice and their countries 18 • The tools that are used in the greatest number of countries are GEMS, Metaedit+, Sirius, and Xtext • Some meta-modelling tools are each used in one or two countries • ANTLR, GEMOC, WebGME, Melange, JastEMF, Graphiti • Some countries use particular meta-modelling tools more than the other tools • USA's top used tool is Microsoft DSL tools • Finland's is Metaedit+ • Many European countries’ top-used tools are Eclipse-based tools (e.g., GEMS, Sirius, Xtext) • The Netherland and Turkey's is GEMS • Many countries include some practitioners who prefer to use in-house solutions • Belgium, Germany, Finland, France, Taiwan, The Netherlands, Turkey and USA Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  19. 19. Language Definition 19 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Picture taken from Prof. Dr. Knut Hinkelmann’s slides on “Meta-Modeling and Modeling Languages”
  20. 20. Language Definition – Types of notation sets 20 • Diagrammatic visualisation • enables the model elements to be specified using graphical symbols • Textual visualisation • enables the model elements to be specified in terms of texts (e.g., writing code with the programming languages) • Tabular visualisation • enables the model elements to be specified using a table editor that can be displayed as a table • Matrix style visualisation • enables the model elements to be specified in two axes • each matrix cell is the relationship of the elements in two axes • Map visualisation • enables the model elements to be specified with the location and distances • Hybrid visualisation • supports multiple visualisations (e.g., textual, graphical, and tabular) that can be used for editing the same model in a synchronised way Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  21. 21. Language Definition– Semantics definitions 21 • Interpretative language semantics • promotes the model execution without performing any translations into some intermediate formats • Translational language semantics • promotes the definition of the model translations into an intermediate format that can be executed • Translational semantics: • Model-to-text translation • defines the semantics in terms of rules for the translations into some structured text notation such as source-code • Model-to-model translation • defines the semantics in terms of rules for the translation into a model with a different notation set • e.g., producing entity-relationship model from a UML class diagram Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  22. 22. The challenges on defining the languages • The top challenges are • meta-modelling tools' steep learning curve for defining the language syntax and semantics • One participant herein is especially concerned about learning the projectional editing with MPS • the lack of support for training • e.g., tutorials, guidance, and examples on how to dene the language syntax and semantics • A few other participants are concerned about the lack of support for • the integration with the version management tools (e.g., GIT and SVN) for versioning meta-models, • the collaborative meta-modelling, and • keeping the language syntax and semantics complete and consistent as the new modelling elements are added 22
  23. 23. Editor Services 23 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  24. 24. Editor Services – Editing mode • Free-form editing • Users edit a textual or graphical model that is stored persistently • A persistent model transformed into an abstract representation that is transformed into an executable representation • Projectional editing • Users edit projections of the model's abstract representation that is stored persistently and transformed into an executable representation • Each projection may be in different formats • e.g., graphical, textual, tabular, and matrix • Unlike the free-form editing, the projections edited by the users are not stored persistently 24 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  25. 25. Editor Services – Syntactic editor services • Model re-use • The models created kept in a repository • New models created by re-using the existing models in the repository • Model comparison (diff-like tool) • enables to detect and review the differences between models and even merge them • Syntactic completion templates • provide incomplete models to the users (e.g., design pattern models) • Auto-formatting, restructuring, aligning models’ presentation 25 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  26. 26. Editor Services – Semantic editor services • Error marker • highlighting model elements and any associated error messages for detecting the semantical errors • e.g., the violation of well-formedness rules • Automatic update of the models when meta-model changes • enables the modelers to detect any errors due to the semantical changes automatically • Semantic completions • for receiving automatic suggestions at modelling time • Refactoring of models • the refactoring of models without changing semantics • e.g., renaming and language-specific restructuring • UML support • Reusing and extending the UML language syntax and semantics • Live translation • Displaying model and code side-by-side 26 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  27. 27. Other Editor Services • Document generation • generating Word, PDF, or XML files from models automatically • Importing/exporting models • for sharing models among collaborators • Version control system integration • Managing model versions • Usability • the minimum number of clicks for modelling/meta-modelling • Traceability • checking the consistencies between structural and behavioural models • IDE integration • the integration with development environments such as Eclipse and Visual Studio 27
  28. 28. The challenges on developing/using editors • The top concern is the usability of the editors • Usability issues in using Eclipse Xtext/Xtend and MPS meta-modelling tools for developing editors • Xtext’s support for scalability and traceability based on the OSLC* linking • Also, some participants are concerned about editors' lack of support for • model versioning • training (i.e., any learning materials to learn how to produce modeling editors) • integrating editors with other development technologies, such as .NET, to combine modelling and coding • Lastly, one participant is concerned about the support for the web-based editors • Another participant is concerned about the syntax colouring 28 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey *OSLC: https://open-services.net/
  29. 29. Model Transformation/ Code-generation 29 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Picture taken from https://www.metacase.com
  30. 30. Model transformation/code-generation features • Error detection • Detecting errors during the code generator development • Syntax highlighting • Colouring the code for transformation • Facilitating the readability and the detection of syntax errors • Scalability • Developing large transformation tools • With hundreds of lines of code for transforming large and complex models 30 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  31. 31. The challenges on using the model transformation/code-generation technologies • A few of the participants stated some challenges on their use of the model transformation technologies • These challenges are to do with • adapting the code generators with the end-user requirements • the training support for using the transformation technologies • integrating code generators with external Java programs, and • the transformation technologies being too Java-centric and neglecting the needs of embedded domains. 31 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  32. 32. Language Validation 32 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  33. 33. Validation Types • Structural validation rules • The structural aspects of the language definitions • E.g., the multiplicities of the language elements and containment relationships between them • Semantic validation rules • The semantical aspects of language definitions • E.g., Name/type analysis 33 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Language validation is concerned with meta-modelling tools' support for defining the language validation rules that can be executed via the modelling editor to validate models
  34. 34. The meta-modelling tool features for language validations • Some desired features are • the integration with some external validation tools • formal verification tools • theorem provers • simulation tools • testing tools • automated model and meta-model validations for • user-defined rules • pre-defined rules 34 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  35. 35. The challenges on defining the language validation rules • While most participants did not state any challenges, a few participants pointed out meta-modelling tools' lack of support for • checking any model for the validation rules at modelling time and • defining complex validation rules 35 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  36. 36. Language Testing 36 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Picture taken from https://www.scnsoft.com/software-testing/software-testing-trends
  37. 37. Testing different aspects of language development 37 • The syntax and semantics testing is for checking if • the language meta-model consists of the expected modeling elements and relationships and • the syntax and semantics rules have been defined correctly and completely • The editor testing is for checking if the editor • enables creating models in accordance with the syntax and semantics and • meets such quality requirements as usability and performance • The code generator testing is for checking if the code-generator • performs the model transformation correctly and meets the quality expectations • The validation rules testing is for checking if • the validation rules can be defined in accordance with the language requirements and used for validating models correctly Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Language testing is concerned with testing the • language definition (syntax and semantics) • editor services • code generator • validation rules
  38. 38. The challenges on testing different aspects of language development • Only a few participants stated some challenges • These challenges are to do with the lack of support for • specifying and executing test cases on different aspects of languages, • integrating any external testing tools that can aid in the language testing, and • the model-based testing of different aspects. 38 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  39. 39. Language Composability 39 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey Picture taken from www.freepik.com
  40. 40. Different aspects of language composability 40 • The language syntax/semantics composed of the syntax/semantics of any existing languages • E.g., re-using the semantical definitions of the existing languages such as UML • A modelling editor developed by composing multiple existing tools • E.g., the model versioning tool, collaboration tool, validation tool, and code-generation tool. • The model transformation/code-generation tool developed via reuse • E.g., re-using transformation templates, patterns, or the existing code • The validation rules defined by re-using and modifying the existing rules or composing multiple rules Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey The language composability is concerned with the meta-modelling tools’ support for extending an existing language with some new features or unifying the parts of multiple languages for developing a new language
  41. 41. The challenges on composing different languages • Just 3 participants stated some challenges, which are to do with • composing different languages without changing them and • the difficulties in performing composition with textual languages. 41 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  42. 42. Lessons Learned • While most practitioners prefer either diagrammatical or textual visualisations, hybrid visualisation is neglected • Practitioners are not familiar with hybrid visualisation • This might be due to the fact that most meta-modelling tools ignore hybrid visualisation • Practitioners define the language semantics by means of translations into text (e.g., source-code) or model (e.g., formal process algebra) • Most practitioners ignore the interpretative semantics definition • Collaborative meta-modelling is important for many practitioners • Importing/exporting the language definitions and versioning the definitions in a repository for later re-use are among practitioners’ top-interests • Practitioners are not familiar with the projectional editing • Indeed, hybrid modelling that could be possible with projectional editing is not preferred either • Also, MPS meta-modeling tool that supports the projectional editing is rarely used 42 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  43. 43. Lessons Learned • Re-using models/meta-models are the top-concern • Defining the language syntax and semantics by re-using the definitions of the existing languages • Re-using the existing models by extending or modifying them • Versioning models/meta-models is also highly important • Practitioners wish to integrate with version control systems (e.g., GIT) and compare and merge model/meta-model versions • Defining the validation rules is so important for most practitioners • Most practitioners are interested in validating both the structural and semantical aspects of languages • Practitioners also wish the meta-modelling tools to be integrated with external verification tools • Formal verification tools, simulation tools, theorem provers, etc. • Testing the language semantics definitions is the most desired testing facility • Likewise, the compositional definitions of semantics is the most desired composition facility 43 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey
  44. 44. Thanks for Listening 44 Assoc.Prof.Dr.MertOzkaya WhatDoPractitionersExpectfromtheMeta-modellingTools?ASurvey

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