结合遗传算法和成对测试,从UML ad优化测试生成

R. Anbunathan, A. Basu
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引用次数: 6

摘要

统一建模语言(UML)活动图(AD)用于抽象地表示系统行为,并且被测试人员用来生成测试用例和测试数据。在设计测试用例期间,具有并发活动的AD可能会导致大量的路径,并且可能并不总是能够测试所有的执行路径。从具有并发活动的AD中提取测试用例的研究主要集中在传统的搜索技术上,如广度优先搜索和深度优先搜索,这些技术在这种情况下被发现是低效的。为了克服这一缺点,作者提出了一种使用配对测试和遗传算法的方法,以减少AD中并发活动的测试用例数量。在各种实际并发系统上进行的实验表明,与现有方法相比,所提出的技术产生的测试用例数量减少了。
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Combining genetic algorithm and pairwise testing for optimised test generation from UML ADs
Unified modelling language (UML) activity diagram (AD) is used to represent system behaviour abstractly and is used by testers to generate test cases and test data. During the design of test cases, AD with concurrent activities may lead to a large number of paths, and it may not always be possible to test all execution paths. Research on deriving test cases from AD having concurrent activities has focused on conventional search techniques such as breadth-first search and depth-first search which has been found to be inefficient in such cases. To overcome this drawback, the authors propose a method using pairwise testing and genetic algorithm to derive a reduced number of test cases in AD with concurrent activities. Experiments conducted on various real-life concurrent systems show that the proposed technique generates a reduced number of test cases compared with existing methods.
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