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Metrics for Effort/Cost Estimation of Mobile apps development

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My project of Master thesis at University of Salerno in:
Software Engineering - Metrics, Quality and Experimental Evaluation

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Metrics for Effort/Cost Estimation of Mobile apps development

  1. 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
  2. 2. The Effort and Cost Estimation
  3. 3. Not Only for traditional Software
  4. 4. always hard to estimate in advance
  5. 5. overbudget and overrun
  6. 6. Continuous process
  7. 7. When more data become available…
  8. 8. more accurate estimations can be achieved!
  9. 9. Non-Model-Based Human experts MAN / HOURS
  10. 10. Model-Based M M M M MAN / HOURS
  11. 11. the SizeFactor
  12. 12. the SizeFactor L OC
  13. 13. L OC the SizeFactor
  14. 14. F P A Function Point Analysis (functional) transactions and (logical) data the SizeFactor
  15. 15. c f p Cosmic Function Point movements from/to persistent storage and users the SizeFactor
  16. 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
  17. 17. D’avanzo approach van Heeringen & van Gorp approach Cozzolino et al. approach newset of guidelines
  18. 18. Cozzolino et al. approach View/Show Data Create/Set/Delete Data Invoking service newset of guidelines
  19. 19. Cozzolino et al. approach 3 CFP 3 CFP 2 CFP newset of guidelines
  20. 20. LIMITations
  21. 21. The software life cycle is already started!
  22. 22. Early Effort Estimation
  23. 23. Defining a set of metrics for mobile early effort estimation
  24. 24. Defining a set of metrics for mobile early effort estimation Investigating how the early size measure can be mapped into Cozzolino et al. guidelines
  25. 25. 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
  26. 26. Defining a set of metrics for mobile early effort estimation
  27. 27. 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.
  28. 28. 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.
  29. 29. 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
  30. 30. 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
  31. 31. Features Categories
  32. 32. Features Application GUI Categories
  33. 33. Features Application GUI Cost Driver Categories
  34. 34. Features Application GUI Project’s Metrics Cost Driver Categories
  35. 35. Features Application GUI Project’s Metrics Cost Driver Application functionality Categories
  36. 36. Features Application GUI Project’s Metrics Cost Driver Application functionality Application size Categories
  37. 37. Features Application GUI Project’s Metrics Cost Driver Application functionality Possible Metrics Application size Categories
  38. 38. 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
  39. 39. Validation of initial set of metrics 4 2 DEVELOPERS PROJECT MANAGERS
  40. 40. Validation of initial set of metrics TWO SURVEYS
  41. 41. Validation of initial set of metrics TWO SURVEYS
  42. 42. Validation of initial set of metrics TWO SURVEY YY
  43. 43. Validation of initial set of metrics 48METRICS
  44. 44. Validation of initial set of metrics 36CONFIRMED
  45. 45. Validation of initial set of metrics 12DELETED
  46. 46. Validation of initial set of metrics 12DELETED Project start date App purchasing Type of business owns the app idea Complex back-end
  47. 47. Validation of initial set of metrics 5ADDED
  48. 48. Validation of initial set of metrics 5ADDED Support Security Backward compatibility User target
  49. 49. Features Generalities Projects Design Platfom Accounting User features Social Aspect Remote Connection eCommerce Date & Location Monitoring Additional Functionality Renovation of Categories
  50. 50. DesignProjects Platfom Features Date & Location Monitoring Additional Functionality Renovation of Categories Accounting User features Social Aspect Generalities Remote Connection eCommerceGoogle Module
  51. 51. SIZE
  52. 52. Investigating how the early size measure can be mapped into Cozzolino et al. guidelines
  53. 53. Requirements Early phase of developments Requirement Elicitation/ Analysis
  54. 54. SOFTWARE SIZE Early phase of developments Requirement Elicitation/ Analysis
  55. 55. Early phase of developments Requirement Elicitation/ Analysis cosmic
  56. 56. 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
  57. 57. Exchange Data via a network Early Metrics Ad hoc authentication Guidelines Cozzolino et al.
  58. 58. 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
  59. 59. 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
  60. 60. 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
  61. 61. Empirical study
  62. 62. Evaluate the accuracy of the estimations in terms of COSMIC Function Points of the early metrics
  63. 63. 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
  64. 64. Evaluate the accuracy of the estimations in terms of COSMIC Function Points of the early metrics 13MOBILE APPLICATIONS
  65. 65. APP FUR EARLY METRIC DESIGN
  66. 66. EARLY METRIC # CFP DESIGN MIN MAX AVG
  67. 67. EARLY METRIC # CFP MRE MMRE MdMRE PRED(25) DESIGN
  68. 68. Results
  69. 69. 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
  70. 70. 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
  71. 71. Application Early CFP_min MRE_min PRED(25) Wikipedia 37 0,19 1 Munch 41 0,02 1 Loopboard 16 0,14 1 Man man 34 0,01 1 Easy Sound Recorder 20 0,11 1 K-9 Mail 38 0,19 1 Transportr 47 0,24 1 Hashr 23 0,21 1 arXiv Mobile 37 0,05 1 NPR News 37 0,03 1 Loop Habit Tracker 26 0,07 1 Radio Droid 33 0,34 0 RoomMates Expense 26 0,41 0 MIN
  72. 72. MIN MMRE 0,16 MDMRE 0,14 PRED(25) 85%
  73. 73. Application Early max MRE_max PRED(25) Wikipedia 47 0,02 1 Munch 51 0,21 1 Loopboard 21 0,5 0 Man man 44 0,16 1 Easy Sound Recorder 25 0,39 0 K-9 Mail 53 0,66 0 Transportr 67 0,76 0 Hashr 23 0,21 1 arXiv Mobile 42 0,08 1 NPR News 42 0,1 1 Loop Habit Tracker 31 0,11 1 Radio Droid 38 0,24 1 RoomMates Expense 31 0,29 1 MAX
  74. 74. MIN MMRE 0,29 0 MDMRE 0,21 PRED(25) 61%
  75. 75. Application Early avg MRE_avg PRED(25) Wikipedia 42 0,09 1 Munch 46 0,09 1 Loopboard 18,5 0,32 0 Man man 38,5 0,01 1 Easy Sound Recorder 22,5 0,25 1 K-9 Mail 45,5 0,42 0 Transportr 57 0,5 0 Hashr 23 0,21 1 arXiv Mobile 39,5 0,01 1 NPR News 39,5 0,04 1 Loop Habit Tracker 28,5 0,02 1 Radio Droid 35,5 0,29 0 RoomMates Expense 28,5 0,35 0 AVG
  76. 76. MMRE 0.2 MDMRE 0.21 PRED(25) 61% AVG
  77. 77. 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
  78. 78. 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
  79. 79. 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
  80. 80. EARLY METRIC Additional validation with companies Gather data FUTURE WORK
  81. 81. FUTURE WORK EARLY METRIC CFP+
  82. 82. Summary
  83. 83. Summary
  84. 84. Summary
  85. 85. Summary
  86. 86. Summary
  87. 87. Summary
  88. 88. Thank you!

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