Search-Based Software Testing: Past, Present and Future
Search-Based Software Testing: Past, Present and Future
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DOI：
10.1109/icstw.2011.100
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发表时间：
2011-03
期刊：
影响因子：
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通讯作者：
Phil McMinn
中科院分区：
文献类型：
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作者：
Phil McMinn
基于搜索的软件测试是使用元海拔优化搜索技术（例如遗传算法）来自动化或部分自动化测试任务，例如自动生成测试数据。优化过程的关键是特定于问题的健身函数。健身函数的作用是指导搜索在实际时间限制内从潜在无限搜索空间中获得良好的解决方案。基于搜索的软件测试的工作可以追溯到1976年，对1990年代开始收集步伐的兴趣。最近，工作量爆炸了。本文回顾了过去的工作和当前的艺术状况，并讨论了潜在的未来研究领域以及该领域中仍然存在的开放问题。
Search-Based Software Testing is the use of a meta-heuristic optimizing search technique, such as a Genetic Algorithm, to automate or partially automate a testing task, for example the automatic generation of test data. Key to the optimization process is a problem-specific fitness function. The role of the fitness function is to guide the search to good solutions from a potentially infinite search space, within a practical time limit. Work on Search-Based Software Testing dates back to 1976, with interest in the area beginning to gather pace in the 1990s. More recently there has been an explosion of the amount of work. This paper reviews past work and the current state of the art, and discusses potential future research areas and open problems that remain in the field.