用于Simulink模型的测试用例生成：来自电动自行车领域的经验
Test Case Generation for Simulink Models: An Experience from the E-Bike Domain
AI总结：
本文研究了SBST技术在生成故障揭示测试用例中的有效性与效率，针对电动自行车领域软件控制器的功能、监管和安全需求，评估了HECATE框架在两个软件控制器中的表现，成功识别83%的测试用例，验证了其在工业应用中的相关性。
摘要：
车载系统开发往往需要工程师在Simulink模型中查找缺陷。基于搜索的软件测试（SBST）是支持此活动的标准技术。为提高实际适应性，行业需要不同领域和复杂度的基准数据来证明现有SBST技术的有效性和效率。为满足这一工业需求，本文介绍了我们在电动自行车领域评估SBST生成故障揭示测试用例有效性与效率的经验。我们的研究对象是电动自行车（e-Bike）领域，特别是电动自行车电机软件控制器的功能、监管和安全需求。我们评估了HECATE，一个用于Simulink模型的SBST框架，以分析两个软件控制器。HECATE成功识别了83%（30/36）的实验中的故障揭示测试用例。平均计算故障揭示测试用例所需时间为1小时17分26秒（最小11分56秒，最大8小时16分22秒，标准差1小时50分34秒）。电动自行车模型开发者确认了HECATE识别的故障。我们提出了经验教训，并讨论了我们的结果对工业应用、实践改进和结果可推广性的重要性。
英文摘要：
Cyber-physical systems development often requires engineers to search for defects in their Simulink models. Search-based software testing (SBST) is a standard technology that supports this activity. To increase practical adaption, industries need empirical evidence of the effectiveness and efficiency of (existing) SBST techniques on benchmarks from different domains and of varying complexity. To address this industrial need, this paper presents our experience assessing the effectiveness and efficiency of SBST in generating failure-revealing test cases for cyber-physical systems requirements. Our study subject is within the electric bike (e-Bike) domain and concerns the software controller of an e-Bike motor, particularly its functional, regulatory, and safety requirements. We assessed the effectiveness and efficiency of HECATE, an SBST framework for Simulink models, to analyze two software controllers. HECATE successfully identified failure-revealing test cases for 83% (30 out of 36) of our experiments. It required, on average, 1 h 17 min 26 s (min = 11 min 56 s, max = 8 h 16 min 22 s, std = 1 h 50 min 34 s) to compute the failure-revealing test cases. The developer of the e-Bike model confirmed the failures identified by HECATE. We present the lessons learned and discuss the relevance of our results for industrial applications, the state of practice improvement, and the results' generalizability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
