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AUTOMATIC SOFTWARE TEST DATA GENERATION FOR SPANNING SETS COVERAGE USING GENETIC ALGORITHMS

机译:使用遗传算法自动生成覆盖范围的软件测试数据

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Software testing takes a considerable amount of time and resources spent on producing software. Therefore, it would be useful to have ways to reduce the cost of software testing. The new concepts of spanning sets of entities suggested by Marre and Bertolino are useful for reducing the cost of testing. In fact, to reduce the testing effort, the generation of test data can be targeted to cover the entitiesrnin the spanning set, rather than all the entities in the tested program. Marre and Bertolino presented an algorithm based on the subsumption relation between entities to find spanning sets for a family of control flow and data flow-based test coverage criteria. This paper presents a new general technique for the automatic test data generation for spanning sets coverage. The proposed technique applies to the algorithm proposed recently by Marre and Bertolino to automatically generate the spanning sets of program entities that satisfy a wide range of control flow and data flow-based test coverage criteria. Then, it uses a genetic algorithm to automatically generate sets of test data to cover these spanning sets. The proposed technique employed the concepts of spanning sets to limit the number of test cases, guide the test case selection, overcome the problem of the redundant test cases and automate the test path generation.
机译:软件测试在生产软件上花费了大量时间和资源。因此,具有减少软件测试成本的方法将是有用的。 Marre和Bertolino提出的跨越实体集的新概念对于降低测试成本很有用。实际上,为了减少测试工作,可以将测试数据的生成定位为覆盖生成集中的实体,而不是覆盖测试程序中的所有实体。 Marre和Bertolino提出了一种基于实体之间的包含关系的算法,以找到一系列控制流和基于数据流的测试覆盖标准的扩展集。本文提出了一种新的通用技术,用于自动生成跨集覆盖的测试数据。所提出的技术适用于Marre和Bertolino最近提出的算法,以自动生成满足广泛控制流和基于数据流的测试覆盖标准的程序实体的扩展集。然后,它使用遗传算法自动生成测试数据集以覆盖这些跨越集。所提出的技术采用了跨越集的概念来限制测试用例的数量,指导测试用例的选择,克服冗余测试用例的问题并自动生成测试路径。

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