Irving Muller Rodrigues, Daniel Aloise, Eraldo Rezende Fernandes and Michel Dagenais
Paper (2020)
An external link is available for this itemAbstract
Bug tracking systems (BTS) are widely used in software projects. An important task in such systems consists of identifying duplicate bug reports, i.e., distinct reports related to the same software issue. For several reasons, reporting bugs that have already been reported is quite frequent, making their manual triage impractical in large BTSs. In this paper, we present a novel deep learning network based on soft-attention alignment to improve duplicate bug report detection. For a given pair of possibly duplicate reports, the attention mechanism computes interdependent representations for each report, which is more powerful than previous approaches. We evaluate our model on four well-known datasets derived from BTSs of four popular open-source projects. Our evaluation is based on a ranking-based metric, which is more realistic than decision-making metrics used in many previous works. Achieved results demonstrate that our model outperforms state-of-the-art systems and strong baselines in different scenarios. Finally, an ablation study is performed to confirm that the proposed architecture improves the duplicate bug reports detection.
Uncontrolled Keywords
bug tracking systems; duplicate bug report detection; deep learning; attention mechanism
Subjects: |
2700 Information technology > 2706 Software engineering 2700 Information technology > 2720 Computer systems software |
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Department: | Department of Computer Engineering and Software Engineering |
Funders: | GRSNG / NSERC, Ericsson, Ciena, EffciOS |
PolyPublie URL: | https://publications.polymtl.ca/9345/ |
Conference Title: | 17th International Conference on Mining Software Repositories (MSR 2020) |
Conference Location: | Seoul, Republic of Korea |
Conference Date(s): | 2020-06-29 - 2020-06-30 |
Publisher: | ACM |
DOI: | 10.1145/3379597.3387470 |
Official URL: | https://doi.org/10.1145/3379597.3387470 |
Date Deposited: | 06 Sep 2023 13:20 |
Last Modified: | 25 Sep 2024 15:45 |
Cite in APA 7: | Rodrigues, I. M., Aloise, D., Fernandes, E. R., & Dagenais, M. (2020, June). A soft alignment model for bug deduplication [Paper]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. https://doi.org/10.1145/3379597.3387470 |
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