In this article, test diversity has been suggested to be a valid way to improve test suite effectiveness. Extended finite state machine (EFSM) is a widely used formal model, but little attention is paid on the test suite generation with more diversity. EFSM test suite generation involves test paths generation and test data generation. Considering the discrepancy between test paths has a more crucial impact on the diversity of test suite, compared with the difference between test data, this article, therefore, mainly concerns the test paths generation with more diversity for EFSM models. Hence, the factors that influence the discrepancy between test paths are investigated. Then based on these factors, an integrated distance metric is designed to evaluate the dissimilarity between test paths, and a diversity measurement for EFSM test suite is presented. Furthermore, a diversity-oriented test suite generation (DOTSG) method is proposed where a dissimilarity-based fitness function and diversity-oriented update strategy are adopted in traditional coverage-oriented EFSM test suite generation (COTSG) by genetic algorithm. The experimental results show that, compared to COTSG, our DOTSG can not only generate more diverse test suite to satisfy a certain coverage criteria, improving the fault detection capability of the test suite, but also decrease the evolution time cost and the size of test suite generated.

中文翻译：

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EFSM 模型面向多样性的测试套件生成

在本文中，测试多样性被认为是提高测试套件有效性的有效方法。扩展有限状态机（EFSM）是一种广泛使用的形式模型，但很少关注具有更多多样性的测试套件生成。EFSM 测试套件生成包括测试路径生成和测试数据生成。考虑到测试路径之间的差异对测试套件的多样性有更重要的影响，与测试数据之间的差异相比，因此本文主要关注EFSM模型具有更多多样性的测试路径生成。因此，研究了影响测试路径之间差异的因素。然后基于这些因素，设计集成距离度量来评估测试路径之间的差异，并提出了 EFSM 测试套件的多样性测量。此外，提出了一种面向多样性的测试套件生成（DOTSG）方法，该方法在传统的面向覆盖的EFSM测试套件生成（COTSG）中通过遗传算法采用了基于差异的适应度函数和面向多样性的更新策略。实验结果表明，与COTSG相比，我们的DOTSG不仅可以生成更多样化的测试套件以满足一定的覆盖标准，提高了测试套件的故障检测能力，而且降低了进化时间成本和测试套件的规模生成。提出了一种面向多样性的测试套件生成（DOTSG）方法，该方法在传统的面向覆盖的EFSM测试套件生成（COTSG）中通过遗传算法采用了基于差异的适应度函数和面向多样性的更新策略。实验结果表明，与COTSG相比，我们的DOTSG不仅可以生成更多样化的测试套件以满足一定的覆盖标准，提高了测试套件的故障检测能力，而且降低了进化时间成本和测试套件的规模生成。提出了一种面向多样性的测试套件生成（DOTSG）方法，该方法在传统的面向覆盖的EFSM测试套件生成（COTSG）中通过遗传算法采用了基于差异的适应度函数和面向多样性的更新策略。实验结果表明，与COTSG相比，我们的DOTSG不仅可以生成更多样化的测试套件以满足一定的覆盖标准，提高了测试套件的故障检测能力，而且降低了进化时间成本和测试套件的规模生成。