Bench4BL: Reproducibility Study on the Performance of IR-Based Bug Localization
In recent years, the use of Information Retrieval (IR) techniques to automate the localization of buggy files, given a bug report, has shown promising results. The abundance of approaches in the literature, however, contrasts with the reality of IR-based bug localization (IRBL) adoption by developers (or even by the research community to complement other research approaches). Presumably, this situation is due to the lack of comprehensive evaluations for state-of-the-art approaches which offer insights into the actual performance of the techniques.
We report on a comprehensive reproduction study of six state-of-the-art IRBL techniques. This study applies not only subjects used in existing studies (old subjects) but also 46 new subjects (amounting to 61,431 Java files and 9,459 bug reports) to the IRBL techniques. In addition, the study compares two different version matching (between bug reports and source code files) strategies to highlight some observations related to performance deterioration. We also vary test file inclusion to investigate the effectiveness of IRBL techniques on test files, or its noise impact on performance. Finally, we assess potential performance gain if duplicate bug reports are leveraged.
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Test Case Prioritization for Acceptance Testing of Cyber Physical Systems: A Multi-Objective Search-Based Approach
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