skip to main content
10.1145/3328778.3366948acmconferencesArticle/Chapter ViewAbstractPublication PagessigcseConference Proceedingsconference-collections
research-article

Assessing Individual Contributions to Software Engineering Projects with Git Logs and User Stories

Published:26 February 2020Publication History

ABSTRACT

Software Engineering courses often incorporate large-scale projects with collaboration between students working in teams. However, it is difficult to objectively assess individual students when their projects are a product of collaborative efforts. This study explores measurements of individuals' contributions to their respective teams.

I analyzed ten Software Engineering team projects (n=42) and evaluations of individual contributions using automated evaluation of the version control system history (Git logs) and user stories completed on their project management (Kanban) boards. Unique insights from meta-data within the Git history and Kanban board user stories reveal complicated relationships between these measurements and traditional assessments, such as peer review and subjective instructor evaluation. From the results, I suggest supplementing and validating traditional assessments with insights from individuals' commit history and user story contributions.

References

  1. Howard Abikoff, Mary Courtney, William E. Pelham, and Harold S. Koplewicz. 1993. Teachers' ratings of disruptive behaviors: The influence of halo effects. Journal of Abnormal Child Psychology 21, 5 (01 Oct 1993), 519--533. https://doi.org/10.1007/BF00916317Google ScholarGoogle ScholarCross RefCross Ref
  2. ACM. 2013. Computer Science 2013: Curriculum Guidelines for Undergraduate Programs in Computer Science. http://www.acm.org/education/curricula-recommendationsGoogle ScholarGoogle Scholar
  3. Francesca Arcelli Fontana and Claudia Raibulet. 2017. Students' Feedback in Using GitHub in a Project Development for a Software Engineering Course. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '17). ACM, New York, NY, USA, 380--380. https://doi.org/10.1145/3059009.3072984Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Kent Beck, Mike Beedle, Arie van Bennekum, Alistair Cockburn, Ward Cunningham, Martin Fowler, James Grenning, Jim Highsmith, Andrew Hunt Ron Jeffries, Jon Kern, Brian Marick, Robert C. Martin Steve Mellor, Ken Schwaber, Jeff Sutherland, and Dave Thomas. 2001. Agile Manifesto. http://agilemanifesto.org/Google ScholarGoogle Scholar
  5. Grant Braught, John Maccormick, James Bowring, Quinn Burke, Barbara Cutler, David Goldschmidt, Mukkai Krishnamoorthy, Wesley Turner, Steven Huss- Lederman, Bonnie Mackellar, and Allen Tucker. 2018. A Multi-Institutional Perspective on H/FOSS Projects in the Computing Curriculum. ACM Trans. Comput. Educ. 18, 2, Article 7 (July 2018), 31 pages. https://doi.org/10.1145/3145476Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bernd Bruegge, Stephan Krusche, and Lukas Alperowitz. 2015. Software Engineering Project Courses with Industrial Clients. Trans. Comput. Educ. 15, 4, Article 17 (Dec. 2015), 31 pages. https://doi.org/10.1145/2732155Google ScholarGoogle Scholar
  7. Kevin Buffardi. 2018. Tech Startup Learning Activities: A Formative Evaluation. In IEEE/ACM International Workshop on Software Engineering Education for Millennials (SEEM). 24--31.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Kevin Buffardi. 2019. gitlog2csv. https://github.com/kbuffardi/gitlog2csvGoogle ScholarGoogle Scholar
  9. Kevin Buffardi, Colleen Robb, and David Rahn. 2017. Learning Agile with Tech Startup Software Engineering Projects. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '17). ACM, New York, NY, USA, 28--33. https://doi.org/10.1145/3059009.3059063Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Kevin Buffardi, Colleen Robb, and David Rahn. 2017. Tech Startups: Realistic Software Engineering Projects with Interdisciplinary Collaboration. J. Comput. Sci. Coll. 32, 4 (April 2017), 93--98. http://dl.acm.org/citation.cfm?id=3055338.3055355Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Donald T. Campbell. 1979. Assessing the impact of planned social change. Evaluation and Program Planning 2, 1 (1979), 67 -- 90. https://doi.org/10.1016/0149--7189(79)90048-XGoogle ScholarGoogle ScholarCross RefCross Ref
  12. Nicole Clark. 2005. Evaluating Student Teams Developing Unique Industry Projects. In Proceedings of the 7th Australasian Conference on Computing Education - Volume 42 (ACE '05). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 21--30. http://dl.acm.org/citation.cfm?id=1082424.1082428Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. N. M. Devadiga. 2017. Software Engineering Education: Converging with the Startup Industry. In 2017 IEEE 30th Conference on Software Engineering Education and Training (CSEE T). 192--196. https://doi.org/10.1109/CSEET.2017.38Google ScholarGoogle Scholar
  14. Heidi J.C. Ellis and Gregory W. Hislop. 2016. Pathways to Student Learning Within HFOSS. In Proceedings of the 17th Annual Conference on Information Technology Education (SIGITE '16). ACM, New York, NY, USA, 168--168. https://doi.org/10.1145/2978192.2978242Google ScholarGoogle Scholar
  15. F. Fagerholm and A. Vihavainen. 2013. Peer assessment in experiential learning Assessing tacit and explicit skills in agile software engineering capstone projects. In 2013 IEEE Frontiers in Education Conference (FIE). 1723--1729. https://doi.org/10.1109/FIE.2013.6685132Google ScholarGoogle ScholarCross RefCross Ref
  16. Vahid Garousi, Kai Petersen, and Baris Ozkan. 2016. Challenges and best practices in industry-academia collaborations in software engineering: A systematic literature review. Information and Software Technology 79 (2016), 106 -- 127. https://doi.org/10.1016/j.infsof.2016.07.006Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. GitHub. 2019. The world's leading software development platform - GitHub. https://github.com/ Accessed on August 2019.Google ScholarGoogle Scholar
  18. Nicole Herbert. 2007. Quantitative Peer Assessment: Can Students Be Objective?. In Proceedings of the Ninth Australasian Conference on Computing Education - Volume 66 (ACE '07). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 63--71. http://dl.acm.org/citation.cfm?id=1273672.1273680Google ScholarGoogle Scholar
  19. Bibb Latane, Kipling Williams, and Stephen Harkins. 1979. Many hands make light the work: The causes and consequences of social loafing. Journal of Personality and Social Psychology 37 (1979), 822--832. Issue 6. https://doi.org/10.1037/0022--3514.37.6.822Google ScholarGoogle ScholarCross RefCross Ref
  20. Richard A. Layton, Matthew W. Ohland, and Hal Pomeranz. 2007. Software For Student Team Formation And Peer Evaluation: Catme Incorporates Team Maker.Google ScholarGoogle Scholar
  21. Robert C. Martin. 2006. Agile Software Development: Principles, Patterns, and Practices. Prentice Hall.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Nancy R. Mead. 2015. Industry/University Collaboration in Software Engineering Education: Refreshing and Retuning Our Strategies. In Proceedings of the 37th International Conference on Software Engineering - Volume 2 (ICSE '15). IEEE Press, Piscataway, NJ, USA, 273--275. http://dl.acm.org/citation.cfm?id=2819009.2819050Google ScholarGoogle ScholarCross RefCross Ref
  23. Christian Murphy, Kevin Buffardi, Josh Dehlinger, Lynn Lambert, and Nanette Veilleux. 2017. Community Engagement with Free and Open Source Software. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE '17). ACM, New York, NY, USA, 669--670. https://doi.org/10.1145/3017680.3017682Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Natalja Nikitina, Mira Kajko-Mattsson, and Magnus Stråle. 2012. From Scrum to Scrumban: A Case Study of a Process Transition. In Proceedings of the International Conference on Software and System Process (ICSSP '12). IEEE Press, Piscataway, NJ, USA, 140--149. http://dl.acm.org/citation.cfm?id=2664360.2664382Google ScholarGoogle ScholarCross RefCross Ref
  25. Matthew Ohland, Misty Loughry, Rufus L. Carter, Lisa Bullard, Richard Felder, Cynthia Finelli, Richard Layton, and Douglas Schmucker. 2005. Developing a Peer Evaluation Instrument that is Simple, Reliable, and Valid. Proceedings 2005 American Society of Engineering Education Conference and Exposition Portland Oregon (01 2005).Google ScholarGoogle Scholar
  26. MatthewW. Ohland, Misty L. Loughry, David J.Woehr, Lisa G. Bullard, Richard M. Felder, Cynthia J. Finelli, Richard A. Layton, Hal R. Pomeranz, and Douglas G. Schmucker. 2012. The Comprehensive Assessment of Team Member Effectiveness: Development of a Behaviorally Anchored Rating Scale for Self- and Peer Evaluation. Academy of Management Learning & Education 11, 4 (2012), 609--630. https://doi.org/10.5465/amle.2010.0177Google ScholarGoogle Scholar
  27. Helen Parker and Mike Holcombe. 1999. Campus-based Industrial Software Projects: Risks and Rewards. SIGCSE Bull. 31, 3 (June 1999), 189--. https://doi.org/10.1145/384267.305935Google ScholarGoogle Scholar
  28. Gustavo Pinto, Clarice Ferreira, Cleice Souza, Igor Steinmacher, and Paulo Meirelles. 2019. Training Software Engineers Using Open-source Software: The Students' Perspective. In Proceedings of the 41st International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET '19). IEEE Press, Piscataway, NJ, USA, 147--157. https://doi.org/10.1109/ICSE-SEET.2019.00024Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Arnold Rosenbloom, Sadia Sharmin, and Andrew Wang. 2017. GIT: Pedagogy, Use and Administration in Undergraduate CS. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '17). ACM, New York, NY, USA, 82--83. https://doi.org/10.1145/3059009.3072980Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Frank W. Schneider, Jamie A. Gruman, and Larry M. Coutts. 2012. Applied Social Psychology: Understanding and Addressing Social and Practical Problems. SAGE.Google ScholarGoogle Scholar
  31. Therese Mary Smith, Robert McCartney, Swapna S. Gokhale, and Lisa C. Kaczmarczyk. 2014. Selecting Open Source Software Projects to Teach Software Engineering. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE '14). ACM, New York, NY, USA, 397--402. https://doi.org/10.1145/2538862.2538932Google ScholarGoogle Scholar
  32. Jeff Sutherland. 2018. Impediments of Performance Appraisals. https://www.scruminc.com/performance-appraisals/ Accessed November 2019.Google ScholarGoogle Scholar
  33. Anya Tafliovich, Andrew Petersen, and Jennifer Campbell. 2015. On the Evaluation of Student Team Software Development Projects. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE '15). ACM, New York, NY, USA, 494--499. https://doi.org/10.1145/2676723.2677223Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Linda van den Bergh, Eddie Denessen, Lisette Hornstra, Marinus Voeten, and Rob W. Holland. 2010. The Implicit Prejudiced Attitudes of Teachers: Relations to Teacher Expectations and the Ethnic Achievement Gap. American Educational Research Journal 47, 2 (2010), 497--527. https://doi.org/10.3102/0002831209353594 arXiv:https://doi.org/10.3102/0002831209353594Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Assessing Individual Contributions to Software Engineering Projects with Git Logs and User Stories

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education
          February 2020
          1502 pages
          ISBN:9781450367936
          DOI:10.1145/3328778

          Copyright © 2020 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 26 February 2020

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate1,595of4,542submissions,35%

          Upcoming Conference

          SIGCSE Virtual 2024

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader