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Search-Based test case prioritization for simulation-Based testing of cyber-Physical system product lines

机译:基于搜索的测试用例优先级,用于基于仿真的电子物理系统产品线测试

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Cyber-Physical Systems (CPSs) integrate computation with physical processes. These systems are usually highly configurable to address different customer needs and are evolving to be CPS product lines. The variability of CPS product lines is large, which implies that they can be set into millions of configurations. As a result, different cost-effective methods are needed to optimize the test process of these systems. We propose a search-based approach that aims to cost-effectively optimize the test process of CPS product lines by prioritizing the test cases that are executed in specific products at different test levels. The prioritized test suite aims at reducing the fault detection time, the simulation time and the time required to cover functional and non-functional requirements.We compared our approach by integrating five search algorithms as well as Random Search (RS) using four case studies. As compared with RS, the search algorithms managed to reduce fault detection time by 47%, the simulation time by 23%, the functional requirements covering time by 22% and the non-functional requirements covering time by 47%. Moreover, we observed that the performance of search algorithms varied for different case studies but the local search algorithms were more effective than the global search algorithms. (C) 2018 Elsevier Inc. All rights reserved.
机译:网络物理系统(CPS)将计算与物理过程集成在一起。这些系统通常是高度可配置的,可以满足不同的客户需求,并且正在发展成为CPS产品线。 CPS产品系列的可变性很大,这意味着它们可以设置成数百万种配置。结果,需要不同的成本有效方法来优化这些系统的测试过程。我们提出了一种基于搜索的方法,旨在通过优先考虑在不同测试级别在特定产品中执行的测试用例,来经济高效地优化CPS产品线的测试过程。优先测试套件旨在减少故障检测时间,仿真时间以及满足功能和非功能需求所需的时间。我们通过整合五个案例搜索算法和随机案例搜索(RS),通过四个案例研究对我们的方法进行了比较。与RS相比,搜索算法将故障检测时间减少了47%,将仿真时间减少了23%,将功能需求覆盖了22%,将非功能需求覆盖了47%。此外,我们观察到搜索算法的性能因案例研究而异,但是本地搜索算法比全局搜索算法更有效。 (C)2018 Elsevier Inc.保留所有权利。

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