Understanding the Impact of Domain Term Explanation on Duplicate Bug Report Detection
Duplicate bug reports make up 42% of all reports in bug tracking systems (e.g., Bugzilla), causing significant maintenance overhead. Hence, detecting and resolving duplicate bug reports is essential for effective issue management. Traditional techniques often focus on detecting textually similar duplicates. However, existing literature has shown that up to 23% of the duplicate bug reports are textually dissimilar. Moreover, about 78% of bug reports in open-source projects are very short (e.g., less than 100 words) often containing domain-specific terms or jargon, making the detection of their duplicate bug reports difficult. In this paper, we conduct a large-scale empirical study to investigate whether and how enrichment of bug reports with the explanations of their domain terms or jargon can help improve the detection of duplicate bug reports. We use 92,854 bug reports from three open-source systems, replicate seven existing baseline techniques for duplicate bug report detection, and answer two research questions in this work. We found significant performance gains in the existing techniques when explanations of domain-specific terms or jargon were leveraged to enrich the bug reports. Our findings also suggest that enriching bug reports with such explanations can significantly improve the detection of duplicate bug reports that are textually dissimilar.
Thu 19 JunDisplayed time zone: Athens change
13:30 - 15:05 | BugsResearch Papers / Short Papers, Emerging Results / Industry Papers / AI Models / Data at Workshop Room Chair(s): Beyza Eken Sakarya University | ||
13:30 15mTalk | ImageR: Enhancing Bug Report Clarity by Screenshots AI Models / Data Xuchen Tan York University, Deenu Yadav York University, Faiz Ahmed York University, Maleknaz Nayebi York University | ||
13:45 10mTalk | Privacy-Preserving Methods for Bug Severity Prediction Industry Papers Havvanur Dervişoğlu Scientific and Technological Research Council of Turkiye (TUBITAK), Rusen Halepmollasi Istanbul Technical University, Elif Eyvaz Scientific and Technological Research Council of Turkiye (TUBITAK) | ||
13:55 15mTalk | The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models Research Papers Fernando Vallecillos Ruiz Simula Research Laboratory, Max Hort Simula Research Laboratory, Leon Moonen Simula Research Laboratory Pre-print Media Attached | ||
14:10 15mTalk | Understanding the Impact of Domain Term Explanation on Duplicate Bug Report Detection Research Papers Pre-print | ||
14:25 15mTalk | Accelerating Delta Debugging through Probabilistic Monotonicity Assessment Research Papers | ||
14:40 15mTalk | Characterising Bugs in Jupyter Platform Research Papers Yutian Tang University of Glasgow, United Kingdom, Hongchen Cao ShanghaiTech University, Yuxi Chen University of Glasgow, David Lo Singapore Management University | ||
14:55 10mShort-paper | Towards an Interpretable Analysis for Estimating the Resolution Time of Software Issues Short Papers, Emerging Results Dimitrios-Nikitas Nastos Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Themistoklis Diamantopoulos Electrical and Computer Engineering Dept, Aristotle University of Thessaloniki, Davide Tosi Università degli Studi dell'Insubria, Martina Tropeano Università degli studi dell’Insubria, Varese - Italy, Andreas Symeonidis Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki Pre-print | ||