Revealing Software Development Work Patterns with PR-Issue Graph Topologies
How software developers work and collaborate, and how we can best support them is an important topic for software engineering research. One issue for developers is a limited understanding of work that has been done and is ongoing. Modern systems allow developers to create Issues and pull requests (PRs) to track and structure work. But, developers lack a coherent view that brings together related Issues and PRs.
In this paper we first report on a study of work practices of developers through Issues, PRs, and the links that connect them. Specifically, we mine graphs where the Issues and PRs are nodes, and references (links) between them are the edges. This graph-based approach provides a window into a set of collaborative software engineering practices that have not been previously described. Based on a qualitative analysis of 56 GitHub projects, we report on eight types of work practices alongside their respective PR/Issue topologies.
Next, inspired by our findings, we developed a tool called WorkflowsExplorer to help developers visualize and study workflow types in their own projects. We evaluated WorkflowsExplorer with 6 developers and report on findings from our interviews.
Overall, our work illustrates the value of embracing a topology-focused perspective to investigate collaborative work practices in software development
Thu 18 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
14:00 - 15:30 | Software Maintenance and Comprehension 3Research Papers / Journal First at Pitomba Chair(s): Xin Xia Huawei Technologies | ||
14:00 18mTalk | Revealing Software Development Work Patterns with PR-Issue Graph Topologies Research Papers Cleidson de Souza Federal University of Pará, Brazil, Emilie Ma University of British Columbia, Jesse Wong University of British Columbia, Dongwook Yoon University of British Columbia, Ivan Beschastnikh University of British Columbia | ||
14:18 18mTalk | Using acceptance tests to predict merge conflict risk Journal First Thaís Rocha UFAPE - Universidade Federal do Agreste de Pernambuco, Paulo Borba Federal University of Pernambuco Pre-print | ||
14:36 18mTalk | Generative AI for Pull Request Descriptions: Adoption, Impact, and Developer Interventions Research Papers Tao Xiao Nara Institute of Science and Technology, Hideaki Hata Shinshu University, Christoph Treude Singapore Management University, Kenichi Matsumoto Nara Institute of Science and Technology Pre-print Media Attached | ||
14:54 18mTalk | SimLLM: Measuring Semantic Similarity in Code Summaries Using a Large Language Model-Based Approach Research Papers | ||
15:12 18mTalk | Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations Research Papers David Broneske DZHW Hannover, Germany, Sebastian Kittan Otto-von-Guericke Unviersity Magdeburg, Germany, Jacob Krüger Eindhoven University of Technology |