Insight knowledge in search based software testing
Insight knowledge in search based software testing
复制标题
基于搜索的软件测试的洞察知识
DOI：
10.1145/1569901.1570122
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Arcuri A
中科院分区：
文献类型：
--
作者：
Arcuri A
软件测试可以被重新表述为一个搜索问题，因此搜索算法（例如，遗传算法）可以用来解决它。到目前为止，大多数研究都是经验性质的，其中提出的新技术已经在软件测试基准上得到了验证。然而，很少有人关注为什么元启发式在软件测试中是有效的。这种洞察力知识可以用来设计更成功的新技术。最近的理论工作试图填补这一空白，但实施起来非常复杂。到目前为止，它的范围仅限于小问题。在本文中，我们希望对一个困难的软件测试问题获得深入的了解。我们将实证分析和理论分析结合在一起，并利用两者的优势。
Software testing can be re-formulated as a search problem, hence search algorithms (e.g., Genetic Algorithms) can be used to tackle it. Most of the research so far has been of empirical nature, in which novel proposed techniques have been validated on software testing benchmarks. However, only little attention has been spent to understand why meta-heuristics can be effective in software testing. This insight knowledge could be used to design novel more successful techniques. Recent theoretical work has tried to fill this gap, but it is very complex to carry out. This has limited its scope so far to only small problems. In this paper, we want to get insight knowledge on a difficult software testing problem. We combine together an empirical and theoretical analysis, and we exploit the benefits of both.