.png){kind=icon}
.png){kind=icon}
Return
A Combinatorial Testing-Based Approach to Fault Localization
.png){kind=icon}
OA
AI
DOI：10.1109/TSE.2018.2865935.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Combinatorial testing has been shown to be a very effective strategy for software testing. After a failure is detected, the next task is to identify one or more faulty statements in the source code that have caused the failure. In this paper, we present a fault localization approach, called BEN, which produces a ranking of statements in terms of their likelihood of being faulty by leveraging the result of combinatorial testing. BEN consists of two major phases. In the first phase, BEN identifies a combination that is very likely to be failure-inducing. A combination is failure-inducing if it causes any test in which it appears to fail. In the second phase, BEN takes as input a failure-inducing combination identified in the first phase and produces a ranking of statements in terms of their likelihood to be faulty. We conducted an experiment in which our approach was applied to the Siemens suite and four real-world programs, flex, grep, gzip and sed, from Software Infrastructure Repository (SIR). The experimental results show that our approach can effectively and efficiently localize the faulty statements in these programs.
Keywords:
Testing
Fault diagnosis
Flexible printed circuits
Software
Task analysis
Debugging
Computer science
Combinatorial testing
fault localization
debugging
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.6
Papers:
2.8K
Citations:
1.1W