Presentation slides for the CHASE 2020 paper “Mining for Process Improvements: Analyzing Software Repositories in Agile Retrospectives,” C. Matthies, F. Dobrigkeit, and G. Hesse, in IEEE/ACM 42nd International Conference on Software Engineering Workshops, ACM Press, 2020. doi: https://doi.org/10.1145/3387940.3392168 http://www.chaseresearch.org/workshops/chase2020

1. Hasso Plattner Institute,
University of Potsdam, Germany
christoph.matthies@hpi.de
@chrisma0
Mining for Process Improvements: Analyzing
Software Repositories in Agile Retrospectives
Christoph Matthies, Franziska Dobrigkeit, Guenter Hesse
July ’20
13th International Workshop on Cooperative and
Human Aspects of Software Engineering (CHASE’20)

2. Motivation & Background
2
Retrospective Meetings and Exercises
■ Regular Retrospective meetings in development processes
■ Opportunities for process improvement [1]
■ Popular in professional software engineering [2]
■ Retro exercises/games to encourage idea sharing [3]
■ Most Retrospective exercises focus solely on
gathering perceptions of team members [4]
[1] Ken Schwaber and Jeff Sutherland. 2017. “The Scrum Guide - The Definitive Guide to Scrum: The Rules of the Game”. 19 pages.
[2] Scrum Alliance. 2018. “State of Scrum 2017-2018: Scaling and Agile Transformation”. 36 pages.
[3] Derby Esther and Diana Larsen. 2006. “Agile Retrospectives: Making Good Teams Great.” Pragmatic Bookshelf. 200 pages.
[4] Corinna Baldauf. 2018. “Retromat - Run great agile retrospectives!”. Leanpub.com. 239 pages.

3. Software Project Data
3
Software Repositories and Other Tools
■ Project artifacts created during regular development activities
contain valuable information on the executed process
■ In particular, provide evidence for project problems,
e.g. when tests fail [5] or systems go down [6] for long periods.
[5] Celal Ziftci and Jim Reardon. 2017. “Who broke the build? Automatically identify-ing changes that induce test failures in continuous integration at
Google Scale”. IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track. IEEE, 113–122
[6] Marc Haberkorn and Kishor Trivedi. 2007. “Availability monitor for a software based system”. 10th IEEE High Assurance Systems Engineering
Symposium. IEEE, 321–328

4. Research Goal
4
Applying “Mining Software Repositories” Techniques to Retros
■ Mining Software Repositories (MSR) research field [8]
■ Focus: extracting insights from vast collections of software data
■ Approaches have not yet been applied to software process
improvement in small, Agile teams
Goal: Enable an additional, project data-informed view
of development processes using Retrospective activities
[8] Ahmed E. Hassan. 2008. “The road ahead for Mining Software Repositories”. Frontiers of Software Maintenance. IEEE, 48–57.

5. Data-Informed Retro Activities
5
Progress Check
■ Without methods to gauge effectiveness of Retros, organizations
find it hard to justify expenses of performing Retrospectives [9]
■ Project artifact measurements, based on Retro action items,
can provide results interpretable by teams
■ Compare measurements for
current and following iterations
[9] David G Marshburn. 2018. “Scrum retrospectives: Measuring and improving effectiveness”.
SAIS 2018 Proceedings

6. Proposed Retro Activity
6
Remedy Appraisal: An Example
■ Identified issue: single person committing most of the team’s code
■ Action item: Train all team members in VCS usage
■ Data measurement: Track progress by the number of unique
contributors to team’s code repository
Analyze results in the team, discussion starting points
■ Was the original issue resolved?
■ Does the measurement need tweaking?

7. Conclusion
7
Retrospective Meetings & Data-Informed Activities
■ Increasing knowledge on developers’ interactions is available in
project artifacts, which allows improving dev. processes [10]
■ Approaches not yet established in Agile process improvement
■ We propose defining new, data-informed Retrospective
activities based on project data measurements
■ Future work: automating data-informed insights,
e.g. through chatbots or instant messaging channels
[10] L. Singer, M.-A. Storey, F. Figueira Filho, A. Zagalsky, and D.M. German. 2017. “People Analytics in Software Development”.
Grand Timely Topics in Software Engineering. Springer, 124–153.

8. Summary
8
christoph.matthies@hpi.de
@chrisma0

9. Image Sources
9
In order of appearance
■ Mining by Firza Alamsyah from the Noun Project
■ perception by Maxim Basinski from the Noun Project
■ goal by Alice Design from the Noun Project
■ Data Driven HR by Vectors Market from the Noun Project
■ discussion by Alice Design from the Noun Project
■ Data by Alice Design from the Noun Project