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首页> 外文期刊>International journal of geotechnical earthquake engineering >Test Suite Optimization Using Chaotic Firefly Algorithm in Software Testing
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Test Suite Optimization Using Chaotic Firefly Algorithm in Software Testing

机译：在软件测试中使用混沌萤火虫算法优化测试套件

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摘要

Software testing is time consuming and a costly activity. Effective generation of test cases is necessary in order to perform rigorous testing. There exist various techniques for effective test case generation. These techniques are based on various test adequacy criteria such as statement coverage, branch coverage etc. Automatic generation of test data has been the primary focus of software testing research in recent past. In this paper a novel approach based on chaotic behavior of firefly algorithm is proposed for test suite optimization. Test suite optimization problem is modeled in the framework of firefly algorithm. An Algorithm for test optimization based on firefly algorithm is also proposed. Experiments are performed on some benchmark Program and simulation results are compared for ABC algorithm, ACO algorithm, GA with Chaotic firefly algorithm. Major research findings are that chaotic firefly algorithm outperforms other bio inspired algorithm such as artificial bee colony, Ant colony optimization and Genetic Algorithm in terms of Branch coverage in software testing.
机译：软件测试既耗时又昂贵。为了进行严格的测试，必须有效生成测试用例。存在用于有效生成测试用例的各种技术。这些技术基于各种测试充分性标准，例如语句覆盖率，分支覆盖率等。测试数据的自动生成是近来软件测试研究的主要重点。本文提出了一种基于萤火虫算法混沌行为的测试套件优化新方法。测试套件优化问题是在萤火虫算法的框架内建模的。提出了一种基于萤火虫算法的测试优化算法。在某些基准程序上进行了实验，并比较了ABC算法，ACO算法，GA和混沌萤火虫算法的仿真结果。主要研究结果是，混沌萤火虫算法在软件测试中的分支覆盖率方面优于其他生物启发算法，例如人工蜂群，蚁群优化和遗传算法。

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