论文标题
基于测试序列和测试评估块的Simulink模型基于模拟测试
Simulation-based Testing of Simulink Models with Test Sequence and Test Assessment Blocks
论文作者
论文摘要
基于模拟的软件测试支持工程师在Simulink模型中查找故障。它通常依赖于搜索算法,该算法迭代生成用于在模拟中锻炼模型以检测设计错误的测试输入。尽管基于模拟的软件测试技术在许多实际情况下都是有效的,但它们通常不完全集成在Simulink环境中,需要额外的手动努力。许多技术要求工程师使用Simulink既不直观也不完全支持的逻辑语言来指定要求,从而限制了他们在行业中的采用。 这项工作提出了Hecate,这是一种使用Simulink测试的测试序列和测试评估块的Simulink模型的测试方法。与现有的测试技术不同,Hecate使用Simulink模型中的信息来指导基于搜索的探索。具体而言,Hecate依赖于测试顺序和测试评估块提供的信息来指导搜索程序。在来自不同领域和行业的16个Simulink模型的基准中,我们将Hecate与最先进的测试工具S-Taliro的比较表明,与〜94%和〜81%的BENCHMBMERMMBLECM模型相比,Hecate既有效率更有效(更多的失败测试用例),又比S-Taliro的有效(更少的迭代和计算时间)。此外,Hecate成功地为来自汽车领域的代表性案例研究生成了避开失败的测试案例,证明了其实际实用性。
Simulation-based software testing supports engineers in finding faults in Simulink models. It typically relies on search algorithms that iteratively generate test inputs used to exercise models in simulation to detect design errors. While simulation-based software testing techniques are effective in many practical scenarios, they are typically not fully integrated within the Simulink environment and require additional manual effort. Many techniques require engineers to specify requirements using logical languages that are neither intuitive nor fully supported by Simulink, thereby limiting their adoption in industry. This work presents HECATE, a testing approach for Simulink models using Test Sequence and Test Assessment blocks from Simulink Test. Unlike existing testing techniques, HECATE uses information from Simulink models to guide the search-based exploration. Specifically, HECATE relies on information provided by the Test Sequence and Test Assessment blocks to guide the search procedure. Across a benchmark of 16 Simulink models from different domains and industries, our comparison of HECATE with the state-of-the-art testing tool S-TALIRO indicates that HECATE is both more effective (more failure-revealing test cases) and efficient (less iterations and computational time) than S-TALIRO for ~94% and ~81% of benchmark models respectively. Furthermore, HECATE successfully generated a failure-revealing test case for a representative case study from the automotive domain demonstrating its practical usefulness.