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Model-Based Filtering of Combinatorial Test Suites

机译:基于模型的组合测试套件过滤

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Tobias is a combinatorial test generation tool which can effi ciently generate a large number of test cases by unfolding a test pattern and computing all combinations of parameters. In this paper, we first propose a model-based testing approach where Tobias test cases are first run on an executable UML/OCL specification. This animation of test cases on a model allows to filter out invalid test sequences produced by blind enumeration, typically the ones which violate the pre-conditions of operations, and to provide an oracle for the valid ones. We then intro duce recent extensions of the Tobias tool which support an incremental unfolding and filtering process, and its associated toolset. This allows to address explosive test patterns featuring a large number of invalid test cases, and only a small number of valid ones. For instance, these new constructs could mandate test cases to satisfy a given predicate at some point or to follow a given behavior. The early detection of invalid test cases improves the calculation time of the whole generation and execu tion process, and helps fighting combinatorial explosion.
机译:Tobias是组合测试生成工具,可以通过展开测试模式并计算所有参数组合来有效地生成大量测试用例。在本文中,我们首先提出一种基于模型的测试方法,其中Tobias测试用例首先在可执行的UML / OCL规范上运行。模型上测试用例的这种动画形式可以过滤出盲目枚举产生的无效测试序列(通常是违反操作先决条件的序列),并为有效的序列提供预言。然后,我们介绍Tobias工具的最新扩展,这些扩展支持渐进式展开和过滤过程及其相关的工具集。这样可以解决具有大量无效测试用例而只有少量有效测试用例的爆炸性测试模式。例如,这些新构造可能会强制测试用例在某个时候满足给定谓词或遵循给定行为。早期发现无效的测试用例可以提高整个生成和执行过程的计算时间,并有助于对抗组合爆炸。

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