AutoVCS is an application that presents summaries of individual developers' code contributions to team-based projects. We envision that this may be particularly helpful for helping TAs and instructors grade student projects.
We have a paper on this project, "Improving Grading Outcomes in Software Engineering Projects Through Automated Contributions Summaries", at ICSE-SEET 2023 (link forthcoming once made available by conference organisers).
AutoVCS is written in Java, and can present summaries for Java code contributions tracked through GitHub (either Github.com, or Github Enterprise). AutoVCS has the following requirements:
- Java 8+ (tested with Java 8, 11, and 17)
- MySQL or MariaDB (tested with MariaDB 10.3 & 10.8 and MySQL 8.0)
- Our improved version of ChangeDistiller [1].
Rather than simply reporting the number of lines of code added/removed by each developer, such as Github Insights offers, AutoVCS performs program analysis on (Java) code, and by considering code syntax, can offer richer insights. We present as an example a contributions summary produced by AutoVCS:
Details explaining I-IV are shown on the algorithm page.
Interested in seeing how AutoVCS can work for you? Check out Getting Started. Interested in seeing our algorithm for summarising individual contributions? Check out the algorithm details. Want to use AutoVCS to support grading in your class? Check out our suggested workflow.
We welcome bug reports and feature requests!
If you are interested in contributing new code, please reach out to see if the feature you are considering is already underway.
[1] Beat Fluri, Michael Würsch, Martin Pinzger, and Harald C. Gall. Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction. IEEE Transaction on Software Engineering, 33(11), pp. 725-743, 2007.