Agile Software Development Practices: Perceptions & Project Data
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This document presents a study conducted on perceptions and usage of agile software development practices among student project teams at Hasso Plattner Institute and Carnegie Mellon University. It outlines research questions related to practice perception, relationships with project data, and empirically explores several agile practices through student feedback and analysis of their GitHub project data. The findings indicate correlations between self-assessments and empirical data, suggesting a need for integrating project analytics into software engineering processes for improved outcomes.
![Background
2
An undergraduate software engineering capstone course
“methods, concepts, and technologies that
help successfully deliver large software
products developed by multiple teams. [1]
[1] https://hpi.de/plattner/teaching/archive/winter-term-201819/softwaretechnik-ii.html”](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-2-320.jpg)
![Evidence of Agile Practice Usage
■ Dev. practices “inscribed into software artifacts” [deSouza, 2005]
■ Analysis of teams’ GitHub project data
■ Define measures of agile practice usage
□ Based on previous related literature where available
□ “Analytics cold-start” problem [deSouza, 2005]
□ Intuitively traceable to underlying data
12
Based on project data evidence
[deSouza et al., 2005] de Souza, C., Froehlich, J., & Dourish, P, “Seeking the Source: Software Source Code as a
Social and Technical Artifact”. In Proceedings of the 2005 international ACM SIGGROUP conference on
Supporting group work - GROUP ’05, p. 197, 2005.](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-12-320.jpg)
![Code Reviews in PRs
■ Expectations
□ Many developers with few comments
□ Barrier for leaving comments
■ Some devs very motivated: “Hero reviewers” cf. [Mockus et al., 2002]
14
Amount of code review comments
Amount of comments per reviewer
Frequency
[Mockus et al., 2002] Mockus, Audris, Roy T. Fielding, and James D. Herbsleb, "Two case studies of open source software development:
Apache and Mozilla," ACM Transactions on Software Engineering and Methodology (TOSEM) 11, no. 3, pp. 309-346, 2002.](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-14-320.jpg)
![Test-Driven Development
■ Test Statements per Solution Statement [Buffardi et al., 2012]
■ Expectation: Low ratios of test to app code changes
■ 10 test LOC changes / 100 app LOC changes = 0,1
15
Ratio of test to application code line changes
Amount of devs
Ratio test to app code
[Buffardi et al., 2012] K. Buffardi and S. H. Edwards, “Impacts of Teaching Test-Driven Development to Novice Programmers,”
International Journal of Information and Computer Science IJICS, vol. 1, no. 6, pp. 135–143, 2012.](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-15-320.jpg)
![Last-Minute Commits
■ Expectation:
high percentage of commits shortly before Sprint end
■ “Deadline-Driven development” [Ariely et al., 2002]
16
Percentage of Last-Minute Commits per developer
[Ariely et al., 2002] D. Ariely and K. Wertenbroch, “Procrastination, deadlines, and performance: self-control by precommitment.”
Psychological Science, vol. 133, pp. 219–224, 2002.
Frequency
Ratio of last-minute commits by developer](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-16-320.jpg)
![Future Work
21
Integrating project data analysis into SE processes
■ Scrum Retrospective: “an opportunity for the Scrum Team
to inspect itself” [Schwaber, 2017]
■ Common process problems, common diagnoses approaches
■ Project data: additional perspective on team development process
■ New Retrospective activities based on project data
■ e.g. Remedy Appraisal:
did a (process) change manifest in project data?
[Schwaber et al., 2017] Schwaber, K., & Sutherland, J., “The Scrum Guide - The Definitive Guide to Scrum: The Rules
of the Game”, 2017, [online] Available: http://scrumguides.org/docs/scrumguide/v2017/2017-Scrum-Guide-US.pdf](https://image.slidesharecdn.com/se2020-200305095636/85/Agile-Software-Development-Practices-Perceptions-Project-Data-21-320.jpg)
Agile Software Development Practices: Perceptions & Project Data
- 1. Hasso Plattner Institute, University of Potsdam, Germany *Carnegie Mellon University, Pittsburgh, USA christoph.matthies@hpi.de @chrisma0 Agile Software Development Practices: Perceptions & Project Data Christoph Matthies, Johannes Hügle, Tobias Dürschmid*, Ralf Teusner February ’20 Innsbruck
- 2. Background 2 An undergraduate software engineering capstone course “methods, concepts, and technologies that help successfully deliver large software products developed by multiple teams. [1] [1] https://hpi.de/plattner/teaching/archive/winter-term-201819/softwaretechnik-ii.html”
- 3. Motivation: Agile SE Teams 3 Teamwork in collaborating (student) groups
- 4. 4 Motivation: Agile SE Teams Teamwork in collaborating (student) groups
- 5. 5 Relationship between Process Perceptions and Project Data Motivation: Perceptions & Data Two worlds, each relevant
- 6. Perceptions vs. Project Data Main research questions ■ Q1: What are perceptions of agile practice usage in student project teams? ■ Q2: Which practices are perceived to be most related to agile values? ■ Q3: What is the relationship of perceptions and software project data? 6 Regarding agile practices
- 7. Perceptions vs. Project Data ■ SE lecture with agile (collaboration) process novices ■ Subset of eight agile best practices under study ■ Repeatedly collect perceptions of practice use ■ 42 students ■ Surveys after each of the four Sprints ■ Define data measurements reflecting Agile practice usage 7 Methods
- 8. Overall Survey Results 8 Q1: Perceptions regarding practices, answers over all sprints
- 9. Overall Survey Results 9 Q1: Perceptions regarding practices, answers over all sprints
- 10. Overall Survey Results 10 Q2: Correlations to perceptions of agile value implementation
- 11. Overall Survey Results 11 Practices most related to “Agile Mindset”: ■ Practicing Collective Code Ownership (Q2, τ=0.15, p < .05) ■ Not working near the deadline (Q5, τ=−0.21, p < .01) ■ Following “check in early, check in often” principle (Q6, τ= 0.24, p < .01) Q2: Correlations to perceptions of agile value implementation
- 12. Evidence of Agile Practice Usage ■ Dev. practices “inscribed into software artifacts” [deSouza, 2005] ■ Analysis of teams’ GitHub project data ■ Define measures of agile practice usage □ Based on previous related literature where available □ “Analytics cold-start” problem [deSouza, 2005] □ Intuitively traceable to underlying data 12 Based on project data evidence [deSouza et al., 2005] de Souza, C., Froehlich, J., & Dourish, P, “Seeking the Source: Software Source Code as a Social and Technical Artifact”. In Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work - GROUP ’05, p. 197, 2005.
- 13. Extract of Employed Measures ■ Code reviews □ Amount of Pull Request comments by a developer in a Sprint ■ Test-driven Development □ Ruby on Rails conventions separate test from application code □ Ratio of line changes in test and application code ■ Last-Minute Commits □ Percentage of commits by developer within 12 hours of sprint review meeting ■ ... 13 Agile practice measures based on project data
- 14. Code Reviews in PRs ■ Expectations □ Many developers with few comments □ Barrier for leaving comments ■ Some devs very motivated: “Hero reviewers” cf. [Mockus et al., 2002] 14 Amount of code review comments Amount of comments per reviewer Frequency [Mockus et al., 2002] Mockus, Audris, Roy T. Fielding, and James D. Herbsleb, "Two case studies of open source software development: Apache and Mozilla," ACM Transactions on Software Engineering and Methodology (TOSEM) 11, no. 3, pp. 309-346, 2002.
- 15. Test-Driven Development ■ Test Statements per Solution Statement [Buffardi et al., 2012] ■ Expectation: Low ratios of test to app code changes ■ 10 test LOC changes / 100 app LOC changes = 0,1 15 Ratio of test to application code line changes Amount of devs Ratio test to app code [Buffardi et al., 2012] K. Buffardi and S. H. Edwards, “Impacts of Teaching Test-Driven Development to Novice Programmers,” International Journal of Information and Computer Science IJICS, vol. 1, no. 6, pp. 135–143, 2012.
- 16. Last-Minute Commits ■ Expectation: high percentage of commits shortly before Sprint end ■ “Deadline-Driven development” [Ariely et al., 2002] 16 Percentage of Last-Minute Commits per developer [Ariely et al., 2002] D. Ariely and K. Wertenbroch, “Procrastination, deadlines, and performance: self-control by precommitment.” Psychological Science, vol. 133, pp. 219–224, 2002. Frequency Ratio of last-minute commits by developer
- 17. Project Evidence vs. Perceptions 17 Correlations between perceptions and data TDD - Ratio Test/App Code CCO - Unique Files Edited Deadline-Driven Development - Last-Minute Commits “Check in early, check in often” - Avg. LOC churn Parallel User Stories - Unique User Story Identifiers Useful code reviews - Pull Request Comments
- 18. Study Summary 18 A case study on agile practice usage in student teams ■ Case study within education context on selected Agile practice usage in teams ■ Initial measures for Agile practice ■ Self-assessments correlated with measurements concerning TDD and last-minute work □ Well-defined concepts, intuitive to grasp and measure □ Shared mental models
- 19. 19 ■ Differing assumptions between measurement creator and participants ■ Is employed proxy not measuring the intended construct or are perception and data at odds in this context? 🠆 Starting points for discussion and improvement Conclusions & Interpretation Contributions and lessons learned in this study
- 20. Future Work 20 Integrating project data analysis into SE processes Software Process Improvement
- 21. Future Work 21 Integrating project data analysis into SE processes ■ Scrum Retrospective: “an opportunity for the Scrum Team to inspect itself” [Schwaber, 2017] ■ Common process problems, common diagnoses approaches ■ Project data: additional perspective on team development process ■ New Retrospective activities based on project data ■ e.g. Remedy Appraisal: did a (process) change manifest in project data? [Schwaber et al., 2017] Schwaber, K., & Sutherland, J., “The Scrum Guide - The Definitive Guide to Scrum: The Rules of the Game”, 2017, [online] Available: http://scrumguides.org/docs/scrumguide/v2017/2017-Scrum-Guide-US.pdf
- 23. Summary 23
- 24. Image Sources 24 In order of appearance ■ attitude by Nithinan Tatah from the Noun Project ■ Data by Alice Design from the Noun Project ■ agile by Florent B from the Noun Project ■ Mortar Board by Mike Chum from the Noun Project ■ developer by Becris from the Noun Project ■ GitHub mark by GitHub, Inc. ■ questions by Gregor Cresnar from the Noun Project ■ Survey by unlimicon from the Noun Project ■ Merge by Danil Polshin from the Noun Project ■ measures by supalerk laipawat from the Noun Project ■ sum by Trevor Dsouza from the Noun Project ■ end by priyanka from the Noun Project ■ Future by Alice Design from the Noun Project