This document discusses metrics for estimating the effort and cost of developing mobile apps. It proposes defining a set of early metrics that can be extracted before full development begins. These early metrics are mapped to guidelines for estimating Cosmic Function Points (CFP). An empirical study evaluates the accuracy of CFP estimations based on the early metrics by comparing them to actual CFP values for 13 mobile apps. The results show the early estimations were reasonably close to the actual values, with mean magnitude relative error of 0.2 and prediction of actual values within 25% for 61% of apps. Future work involves additional validation with companies and gathering more project data.
Metrics for Effort/Cost Estimation of Mobile apps development
1. Università degli studi di Salerno
Dipartimento di Scienze Aziendali, Management & Innovation System
Corso di Laurea Magistrale inTecnologie Informatiche e Management
Metrics for Effort/Cost Estimation
of Mobile apps development
ANNO ACCADEMICO 2015-2016
Relatore:
Prof. ssa Filomena Ferrucci
Dott. Pasquale Salza
Candidata:
Catolino Gemma
Matricola 0222500095
Tesi di laurea magistrale in
Ingegneria del Software: Metriche, Qualità eValutazione Sperimentale
14. F P A
Function Point Analysis
(functional) transactions
and (logical) data
the SizeFactor
15. c f p
Cosmic Function Point
movements from/to persistent
storage and users
the SizeFactor
16. D’avanzo et al. approach
van Heeringen & van Gorp
approach
Sellami et al.
Set of guidelines for
an approximate and
quick sizing of mobile apps
IFPUG Guidelines
24. Defining a set of metrics for
mobile early effort estimation
25. Defining a set of metrics for
mobile early effort estimation
Investigating how the early size
measure can be mapped
into Cozzolino et al. guidelines
26. Defining a set of metrics for
mobile early effort estimation
Investigating if the mapping
is useful for estimating CFP
Investigating how the early size
measure can be mapped
into Cozzolino et al. guidelines
27. Defining a set of metrics for
mobile early effort estimation
28. Emilia Mendes
Emilia Mendes, Nile Mosley, and Steve Counsell.
Investigating early web size measures for web cost estimation. In Proceedings of EASE’2003 Conference,Keele, pages 1–22, 2003.
29. Analysis of quote form
Emilia Mendes, Nile Mosley, and Steve Counsell.
Investigating early web size measures for web cost estimation. In Proceedings of EASE’2003 Conference,Keele, pages 1–22, 2003.
30. Emilia Mendes, Nile Mosley, and Steve Counsell.
Investigating early web size measures for web cost estimation. In Proceedings of EASE’2003 Conference,Keele, pages 1–22, 2003.
377manually validated links
Analysis of quote form
31. Analysis of quote form
Emilia Mendes, Nile Mosley, and Steve Counsell.
Investigating early web size measures for web cost estimation. In Proceedings of EASE’2003 Conference,Keele, pages 1–22, 2003.
Extraction of initial
set of metrics
39. Emilia Mendes, Nile Mosley, and Steve Counsell.
Investigating early web size measures for web cost estimation. In Proceedings of EASE’2003 Conference,Keele, pages 1–22, 2003.
Extraction of initial
set of metrics Validation of initial
set of metrics
Analysis of quote form
58. Early phase of developments Requirement Elicitation/ Analysis
cosmic
59. View/Show Data
Exchange Data
via a network
Invoking service
Create/Set/Delete Data
Guidelines
Cozzolino et al.
Early MetricsSocial sharing
Search
Messaging
Ad hoc
authentication
Analytics
60. Exchange Data
via a network
Early Metrics
Ad hoc
authentication
Guidelines
Cozzolino et al.
61. Exchange Data
via a network
Lines guide
Cozzolino et al.Early Metrics
Ad hoc
authentication
MIN MAX
10 CFP5 CFP
Login + RegisterLogin
Ad hoc
authentication
62. Exchange Data
via a network
Lines guide
Cozzolino et al.Early Metrics
Ad hoc
authentication
MINMAX
10 CFP 5 CFP
Login + Register Login
41 METRICS
63. Exchange Data
via a network
Lines guide
Cozzolino et al.Early Metrics
Ad hoc
authentication
MINMAX
10 CFP 5 CFP
Login + Register Login
26 METRICS
MIN MAXOPERATIONS
65. Evaluate the accuracy of the
estimations in terms of
COSMIC Function Points
of the early metrics
66. RQ:To what extent the CFPs extractable using the early
metrics are close to the actual CFPs of a Mobile app?
Evaluate the accuracy of the
estimations in terms of
COSMIC Function Points
of the early metrics
67. Evaluate the accuracy of the
estimations in terms of
COSMIC Function Points
of the early metrics
13MOBILE APPLICATIONS
80. Application Early CFP_min Early CFP_max Early CFP_avg Oracle
Wikipedia 37 47 42 46
Munch 41 51 46 42
Loopboard 16 21 18,5 14
Man man 34 44 38,5 38
Easy Sound Recorder 20 25 22,5 18
K-9 Mail 38 53 45,5 32
Transportr 47 67 57 38
Hashr 23 23 23 19
arXiv Mobile 37 42 39,5 39
NPR News 37 42 39,5 38
Loop Habit Tracker 26 31 28,5 28
Radio Droid 33 38 35,5 50
RoomMates Expense 26 31 28,5 44
81. Application Early CFP_min Early CFP_max Early CFP_avg Oracle
Wikipedia 37 47 42 46
Munch 41 51 46 42
Loopboard 16 21 18,5 14
Man man 34 44 38,5 38
Easy Sound Recorder 20 25 22,5 18
K-9 Mail 38 53 45,5 32
Transportr 47 67 57 38
Hashr 23 23 23 19
arXiv Mobile 37 42 39,5 39
NPR News 37 42 39,5 38
Loop Habit Tracker 26 31 28,5 28
Radio Droid 33 38 35,5 50
RoomMates Expense 26 31 28,5 44
82. RQ:To what extent the CFPs extractable using the early
metrics are close to the actual CFPs of a Mobile app?
The estimations provided
by our metrics resulted quite
close to the actual values