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Search-based software test data generation: a survey

机译:基于搜索的软件测试数据生成:调查

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The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that, in general, test data generation is an undecidable problem. Metaheuristic search techniques offer much promise in regard to these problems. Metaheuristic search techniques are high-level frameworks, which utilize heuristics to seek solutions for combinatorial problems at a reasonable computational cost. To date, metaheuristic search techniques have been applied to automate test data generation for structural and functional testing; the testing of grey-box properties, for example safety constraints; and also non-functional properties, such as worst-case execution time. This paper surveys some of the work undertaken in this field, discussing possible new future directions of research for each of its different individual areas.
机译:近年来,将元启发式搜索技术用于自动生成测试数据已成为新兴的兴趣。自动化测试生成过程的先前尝试受到了软件的大小和复杂性以及测试数据生成通常是无法确定的问题这一基本事实的限制,因此受到了限制。元启发式搜索技术针对这些问题提供了广阔的前景。元启发式搜索技术是高级框架,它利用启发式算法以合理的计算成本来寻找组合问题的解决方案。迄今为止,已将元启发式搜索技术应用于结构和功能测试的自动化测试数据生成。测试灰箱特性,例如安全约束;以及非功能属性,例如最坏情况下的执行时间。本文调查了在该领域中开展的一些工作,并讨论了其各个不同领域中可能的未来研究新方向。

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