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Automatic debugging of operator errors based on efficient mutation analysis

delete2018-09-01
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PRE
AI
T
Tiantian Wang *
J
Jiahuan Xu
苏小红 (Xiaohong Su)
C
ChenShi Li
杨纯斌 (C. Yang)
DOI:10.1007/s11042-018-6603-3delete
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Abstract

Abstract

En 中文
It takes a lot of time and effort to manually locate and fix software bugs. This paper proposes a method for automatically debugging operator related bugs. Testing, fault localization, and bug-fixing are closely linked based on mutation analysis. However, in the process of mutation analysis, the generation of a large number of mutants and the execution of test cases on mutants, is fairly time-consuming. To solve this problem, optimization methods for selection of mutants and test cases have been proposed. Experiment results has shown that it can improve the efficiency of mutation analysis, so that the cost of fault-localization and bug-fixing can be reduced. We also implemented the exhaustive mutation method and the random mutation method and compared these three methods. These three method have different application scenarios. As the mutation based fault localization can rank statements by suspiciousness, the method integrated with fault localization is more stable and has batter performance. Also, it is more suitable for analyzing program with multi-bugs.
Keywords:
Mutation analysis
Fault-localization
Automatic repair
Operator error
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Multimedia Tools and Applications cover
Multimedia Tools and Applications
IF:
3
Papers:
1.9W
Citations:
3.2W

Organization

H
harbin institute of technology
Scholars:
8.0W
Papers: 6.6W
Citations: 66