To improve the accuracy of FL while suppressing the increase of execution time, we propose a technique to obtain test cases whose spectra are different from any of the original ones. Adding such test cases enables to calculate more accurate suspiciousness for each statement.
We conducted a small experiment on bug dataset Defect4J and confirmed that the accuracy of SBFL was improved for 56.3% of target bugs while the accuracy was ...
Jul 13, 2020 · The sufficiency of test cases is essential for spectrum-based fault localization (in short, SBFL). If a given set of test cases is not ...
We conducted a small experiment on bug dataset Defect4J and confirmed that the accuracy of SBFL was improved for 56.3% of target bugs while the accuracy was ...
This paper proposes three strategies for selecting some test cases from a large number of automatically-generated test cases and confirms that the accuracy ...
[12,73,93] Optimizing test cases Optimization methods can maximize SBFL's performance using a minimum (e.g., by removing redundant test cases) or a balanced ...
Jul 10, 2020 · ICPC 2020 - Session 03 - Faults - ERA - Improving the Accuracy of Spectrum-based Fault Localization for Automated Program Repair.
Spectrum-based fault localization shortens the test- diagnose-repair cycle by reducing the debugging effort. As a light-weight automated diagnosis technique ...
Jun 16, 2023 · Spectrum-based fault localization (SBFL) works well for single-fault programs but its accuracy decays for increasing fault numbers. We present ...
We present FLITSR (Fault Localization by Iterative Test Suite Reduction), a novel SBFL extension that improves the localization of a given base metric.