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Test Case Evaluation and Input Domain Reduction strategies for the Evolutionary Testing of Object-Oriented software

机译:面向对象软件的进化测试的测试用例评估和输入域缩减策略

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摘要

In Evolutionary Testing, meta-heuristic search techniques are used for generating test data. The focus of our research is on employing evolutionary algorithms for the structural unit-testing of Object-Oriented programs. Relevant contributions include the introduction of novel methodologies for automation, search guidance and Input Domain Reduction; the strategies proposed were empirically evaluated with encouraging results.rnTest cases are evolved using the Strongly-Typed Genetic Programming technique. Test data quality evaluation includes instrumenting the test object, executing it with the generated test cases, and tracing the structures traversed in order to derive coverage metrics. The methodology for efficiently guiding the search process towards achieving full structural coverage involves favouring test cases that exercise problematic structures. Purity Analysis is employed as a systematic strategy for reducing the search space.
机译:在进化测试中,元启发式搜索技术用于生成测试数据。我们研究的重点是将进化算法用于面向对象程序的结构单元测试。相关贡献包括引入新颖的自动化方法,搜索指南和输入域缩减;提出的策略在经验上得到了令人鼓舞的结果评估。测试案例是使用“强类型遗传规划”技术演变而来的。测试数据质量评估包括对测试对象进行检测,使用生成的测试用例执行该测试对象以及跟踪所遍历的结构以得出覆盖率指标。有效指导搜索过程以实现完整的结构覆盖的方法包括偏爱使用有问题结构的测试用例。纯度分析被用作减少搜索空间的系统策略。

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