Thesis+of+zohreh+sharafi.ppt
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This document summarizes Zohreh Sharafi's research on the influence of representation type and gender on program comprehension. The research includes several experiments that investigate how representation type (graphical vs. textual) and gender influence developers' efficiency, effectiveness, and viewing strategies during program comprehension tasks. The results show that developers prefer graphical representations and find relevant information faster with graphical representations compared to textual. The experiments also found that men and women use different strategies to select correct answers, with women taking longer but achieving higher accuracy. Further analysis revealed differences in how men and women distribute their visual attention across source code entities during comprehension tasks.
Thesis+of+zohreh+sharafi.ppt
- 1. On the Influence of Representation Type and Gender on Program Comprehension Zohreh Sharafi Département de Génie Informatique et Génie Logiciel Polytechnique Montréal
- 2. Program Comprehension “Programming is far more complex than usual human mental activities studied by psychologists”(Weinberg and Schulman, 1974)
- 4. Program Comprehension • Over 35 years of research • Rich with diverse theories Think-aloud Observational studies Questionnaires
- 10. Representation Type (Graphical vs. Textual )
- 11. Developers’ Characteristics • Expertise (novices vs. experts) There is still a great divergence between developers’ abilities that cannot be detected only by their level of expertise. (Storey, 2005).
- 12. Thesis Statement Representation type and gender: • To impact the cognitive process • To impact developers’ efficiency and effectiveness • To be proxy for developers’ viewing strategies • To be inferred partly from the developers’ eye- movements
- 14. 1992 2004 2010 Evidence-based Paradigm Evidence-based Software Engineering (EBSE) SLR about SLRs in SE UML Unit Testing Theory Systematic Literature Review (SLR)
- 15. A Systematic Literature Review on the Usage of Eye-tracking in Software Engineering
- 16. A Systematic Literature Review Descriptive Statistics How many 1990 - 2014 36 articles 9 journal 2 workshop 25 conference Under revision, IST Journal, 2013
- 17. A Systematic Literature Review Topics • Code comprehension (12) • Model comprehensions (10) • Debugging (9) • Collaborative interaction (3) • Traceability (2)
- 18. A Systematic Literature Review Metrics • Effort: • Fixation, Saccades • Visited AOIs • Visual gaze behaviour • Scan-path
- 19. A Systematic Literature Review Limitation • Technology • Data analysis • Participant & material selection • Experimental setting
- 20. A Systematic Literature Review Conclusion • To provide descriptive statistics • To present an annotated bibliography • To summarise all the metrics and tools • To present limitations • To provide a unified terminology for reporting
- 21. A Systematic Literature Review Lesson Learned
- 24. Picture Is Worth a Thousand Word
- 25. The Impact of Representation Type Only a few works compare textual vs. graphical representations for program comprehension RQ1: Developers’ preferred representation RQ2: Impact of representation type of time, accuracy, and effort ICPC, 2013
- 26. The Impact of Representation Type Task Session 1 Session 2 Session 3
- 29. The Impact of Representation Type Participants Academic Background Gender PhD Masters BSc Male Female 15 11 2 16 12 Total: 28
- 31. RQ1: Is Graphical More Effective?
- 32. Accuracy % Correct Wrong Graphical 97% 3% Textual 98% 2% Mixed 96% 4% RQ2: Impacts on Developers’ Efficiency
- 33. M:Model Re: Relevant Ir: Irrelevant Q: Question RQ2: Impacts on Developers’ Efficiency
- 34. The Impact of Representation Type Conclusion
- 35. The Impact of Representation Type Conclusion • Prefer graphical • Work with graphical in mixed stimulus • Find relevant parts faster
- 37. The Impact of Representation Type Lesson Learned Importance of Layout Source code as structures text
- 41. Women Take a Wider View M. Czerwinski, D. S. Tan, and G. G. Robertson, “Women take a wider view,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ser. CHI ’02. New York, NY, USA: ACM, 2002,
- 42. The Impact of Gender Why Do We Care? • Studying the need of one sub-population can benefit both sides • Design tools better adapted to different developers • Support different program understanding strategies
- 43. The Impact of Gender Experiment 1: The Impact of Identifier Style Previous work, such as (Binkley et al., 2012) and (Sharif and Maletic, 2010c), reported contradictory findings. RQ1: The impact of identifier style on effort, the task time, and accuracy RQ2: The impact of gender on effort, the task time, accuracy, and viewing strategies ICPC, 2012
- 44. The Impact of Gender Experiment 1: Task Source code stimulus Question stimulus
- 45. The Impact of Representation Type Participants Academic Background Gender PhD Masters BSc Male Female 11 10 3 15 9 Total: 24
- 46. The Impact of Gender Experiment 1: Results Accuracy Time (min) Male 74% 5.94 Female 82% 7.18
- 48. The Impact of Gender Experiment1: Conclusion Time Effort Accuracy Men and women use different strategies to select the correct answer
- 49. The Impact of Gender Lesson Learned Different Attention Distribution
- 50. The Impact of Gender Experiment 2: the Impact of SCEs • Previous studies suggest that developers: • Avoid understanding the entire system • Focus on some parts • Source code entities Class name Method name VariablesComments
- 51. The Impact of Gender Experiment 2: the impact of SCEs RQ3: What are the important source code entities (SCEs) RQ4: Impact of gender on developers’ viewing strategies EMSE, 2014 & ICSM, 2012
- 52. The Impact of Gender Experiment 2: Task
- 53. The Impact of Representation Type Participants Academic Background Gender PhD Masters BSc Male Female 20 4 0 17 7 Total: 24
- 55. The Impact of Gender Experiment 2: Viewing Strategies
- 56. The Impact of Gender Experiment 2: Viewing Strategies Path: 1,2,1,2,3,4 Path: 1,2,3,2,3,1,2,4,3,1,3,4,3 Total time: 1780 Total time: 1315
- 57. 0 5 10 15 20 25 30 35 Q1 Q2 Q3 Q4 Q5 Q6 Average length of scan-paths Men Women
- 58. The Impact of Gender Further Analysis Method name is the most preferred type of SCEs.
- 59. The Impact of Gender Further Analysis • No difference between MiB and CiB • Participants start looking at the Bigger SCE • Method name, method name, method name …
- 60. The Impact of Gender Lesson Learned • Do not rush into adaptation
- 61. The Impact of Gender Conclusion Our findings raise two significant new open questions: 1. Are there differences between viewing strategies of male and female developers while performing program comprehension tasks and whether these strategies impact their efficiency and effectiveness or not? 2. To which extent do current programming environments support these strategies?
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- 66. Short term • Analyze the impact of layout on developers’ performance • Scan-path and AOI analysis • Image processing approaches to analyze heatmaps Long term • Study developers’ viewing strategies and reading behaviour • Analyze the applicability of our gender differences findings
- 69. Awards 1. Taupe: Visualizing and Analysing Eye- tracking Data. SCP, 2011 2. An empirical study on the importance of source code entities for requirements traceability. EMSE, 2014 3. Systematic Literature Review on the Use of Eye-tracking Technique in Software Engineering. Under revision, IST, 2014 Conference Papers 1. Le Fonds de recherche du Québec, Nature et technologies (FRQNT) Journal Papers 1. Women & Men: Different but Equal: A Study on the Impact of Identifiers on Source Code Understanding. ICPC, 2012 2. Professional Status or Expertise for UML Class Diagram Comprehension: An Empirical Study Systematic. ICPC 2012 3. An Empirical Study on Requirements Traceability Using Eye-Tracking. ICSM, 2012 4. An Empirical Study on the Efficiency of Graphical vs. Textual in Requirements Comprehension. ICPC, 2013 69
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