Paper Info
Title
Improving the Accuracy of Spectrum-based Fault Localization for Automated Program Repair
Abstract
ABSTRACTThe sufficiency of test cases is essential for spectrum-based fault localization (in short, SBFL). If a given set of test cases is not sufficient, SBFL does not work. In such a case, we can improve the reliability of SBFL by adding new test cases. However, adding many test cases without considering their properties is not appropriate in the context of automated program repair (in short, APR). For example, in the case of GenProg, which is the most famous APR tool, all the test cases related to the bug module are executed for each of the mutated programs. Execution results of test cases are used for checking whether they pass all the test cases and inferring faulty statements for a given bug. Thus, in the context of APR, it is important to add necessary minimum test cases to improve the accuracy of SBFL. In this paper, we propose three strategies for selecting some test cases from a large number of automatically-generated test cases. 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 decreased for 17.3% in the case of the best strategy. We also confirmed that the increase of the execution time was suppressed to 1.5 seconds at the median.
Year
DOI
Venue
2020
10.1145/3387904.3389290
International Conference on Software Engineering
DocType
Citations 
PageRank 
Conference
1
0.35
References 
Authors
0
4
Name
Order
Citations
PageRank
Tetsushi Kuma110.35
Yoshiki Higo256046.90
Shinsuke Matsumoto320533.53
Shinji Kusumoto41811137.88