Original scientific paper
https://doi.org/10.20532/cit.2020.1005134
Fault Localization Based on Hybrid Genetic Simulated Annealing Algorithm
Zhihua Zhang
; Beijing Information Science and Technology University, Beijing, China
Yongmin Mu
; Beijing Key Laboratory of Internet Culture and Digital, Dissemination Research, Beijing, China
Abstract
Software testing is an important stage in the software development process, which is the key to ensure software quality and improve software reliability. Software fault localization is the most important part of software testing. In this paper, the fault localization problem is modeled as a combinatorial optimization problem, using the function call path as a starting point. A heuristic search algorithm based on hybrid genetic simulated annealing algorithm is used to locate software defects. Experimental results show that the fault localization method, which combines genetic algorithm, simulated annealing algorithm and function correlation analysis method, has a good effect on single fault localization and multi-fault localization. It greatly reduces the requirement of test case coverage and the burden of the testers, and improves the effect of fault localization.
Keywords
hybrid genetic simulated annealing algorithm, function call path, fault localization
Hrčak ID:
259332
URI
Publication date:
11.6.2021.
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