Understanding Debugging as Episodes: A Case Study on Performance Bugs in Configurable Software Systems

Year: 2025

Type: article

Abstract: Debugging performance bugs in configurable software systems is a complex and time-consuming task that requires not only fixing a bug, but also understanding its root cause. While there is a vast body of literature on debugging strategies, there is no consensus on general debugging. This makes it difficult to provide concrete guidance for developers, especially for configuration-dependent performance bugs. The goal of our work is to alleviate this situation by providing an framework to describe debugging strategies in a more general, unifying way. We conducted a user study with 12 professional developers who debugged a performance bug in a real-world configurable system. To observe developers in an unobstructive way, we provided an immersive virtual reality tool, SoftVR, giving them a large degree of freedom to choose the preferred debugging strategy. The results show that the existing documentation of strategies is too coarse-grained and intermixed to identify successful approaches. In a subsequent qualitative analysis, we devised a coding framework to reason about debugging approaches. With this framework, we identified five goal-oriented episodes that developers employ, which they also confirmed in subsequent interviews. Our work provides a unified description of debugging strategies, allowing researchers a common foundation to study debugging and practitioners and teachers guidance on successful debugging strategies.

Source: Proceedings of the ACM on software engineering.

DOI: 10.1145/3717523

Authors: Max Weber, Alina Mailach, Sven Apel, Janet Siegmund, Raimund Dachselt, Norbert Siegmund

Institutions: Leipzig University, Center for Scalable Data Analytics and Artificial Intelligence, Saarland University, Chemnitz University of Technology, Technische Universität Dresden

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Technische Universität Dresden, Sächsisches Staatsministerium für Wissenschaft und Kunst, European Research Council

OpenAlex ID: W4411450002