Barreto Simedo Pacheco, Lorena (2024) Leveraging Stack Traces for Spectrum-based Fault Localization in the Absence of Failing Tests. Masters thesis, Concordia University.
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Abstract
Bug fixing is a crucial task in software maintenance to hold user trust. Although various automated fault localization techniques exist, they often require specific conditions to be effective. For example, Spectrum-Based Fault Localization (SBFL) techniques need at least one failing test to identify bugs, which may not always be available. Bug reports, particularly those with stack traces, provide detailed information on system execution failures and are invaluable for developers. This study focuses on utilizing stack traces from crash reports as fault-triggering tests for SBFL. Our findings indicate that only 3.33% of bugs have fault-triggering tests, limiting traditional SBFL efficiency. However, 98.3% of bugfix intentions align directly with exceptions in stack traces, and 78.3% of buggy methods are reachable within an average of 0.34 method calls, proving stack traces as a reliable source for locating bugs. We introduce a new approach, SBEST, that integrates stack trace data with test coverage to enhance fault localization. Our approach shows a significant improvement, increasing Mean Average Precision (MAP) by 32.22% and Mean Reciprocal Rank (MRR) by 17.43% over traditional stack trace ranking methods.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Barreto Simedo Pacheco, Lorena |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Software Engineering |
Date: | 25 June 2024 |
Thesis Supervisor(s): | Chen, Tse-Hsun (Peter) and Yang, Jinqiu |
ID Code: | 994058 |
Deposited By: | Lorena Barreto Simedo Pacheco |
Deposited On: | 24 Oct 2024 18:48 |
Last Modified: | 24 Oct 2024 18:48 |
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