Extending a search-based test generator with adaptive dynamic symbolic execution

Juan P. Galeotti, G. Fraser, Andrea Arcuri
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引用次数: 20

Abstract

Automatic unit test generation aims to support developers by alleviating the burden of test writing. Different techniques have been proposed over the years, each with distinct limitations. To overcome these limitations, we present an extension to the EvoSuite unit test generator that combines two of the most popular techniques for test case generation: Search-Based Software Testing (SBST) and Dynamic Symbolic Execution (DSE). A novel integration of DSE as a step of local improvement in a genetic algorithm results in an adaptive approach, such that the best test generation technique for the problem at hand is favoured, resulting in overall higher code coverage.
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用自适应动态符号执行扩展基于搜索的测试生成器
自动单元测试生成旨在通过减轻测试编写的负担来支持开发人员。多年来,人们提出了不同的技术,每种技术都有不同的局限性。为了克服这些限制,我们提出了EvoSuite单元测试生成器的扩展,它结合了两种最流行的测试用例生成技术:基于搜索的软件测试(SBST)和动态符号执行(DSE)。作为遗传算法局部改进步骤的DSE的新颖集成产生了一种自适应方法,这样对手头问题的最佳测试生成技术就会得到青睐,从而导致总体上更高的代码覆盖率。
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ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18 - 22, 2022 ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, Denmark, July 11-17, 2021 Automatic support for the identification of infeasible testing requirements Program-aware fuzzing for MQTT applications ISSTA '20: 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, USA, July 18-22, 2020
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