Concolic Testing for High Test Coverage and Reduced Human Effort in Automotive Industry

Yunho Kim, Dongju Lee, Junki Baek, Moonzoo Kim
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引用次数: 11

Abstract

The importance of automotive software has been rapidly increasing because software now controls many components in motor vehicles such as window controller, smart-key system, and tire pressure monitoring system. Consequently, the automotive industry spends a large amount of human effort testing automotive software and is interested in automated software testing techniques that can ensure high-quality automotive software with reduced human effort. In this paper, we report our industrial experience applying concolic testing to automotive software developed by Hyundai Mobis. We have developed an automated testing framework MAIST that automatically generates the test driver, stubs, and test inputs to a target task by applying concolic testing. As a result, MAIST has achieved 90.5% branch coverage and 77.8% MC/DC coverage on the integrated body unit (IBU) software. Furthermore, it reduced the cost of IBU coverage testing by reducing the manual testing effort for coverage testing by 53.3%.
在汽车工业中实现高测试覆盖率和减少人力
汽车软件的重要性一直在迅速增加,因为软件现在控制着汽车上的许多部件,如车窗控制器、智能钥匙系统和轮胎压力监测系统。因此,汽车行业花费了大量的人力来测试汽车软件,并且对自动化软件测试技术感兴趣,这种技术可以减少人力来确保高质量的汽车软件。在本文中,我们报告了我们在现代摩比斯开发的汽车软件中应用碰撞测试的工业经验。我们已经开发了一个自动化的测试框架MAIST,它通过应用聚合测试自动生成测试驱动程序、存根和目标任务的测试输入。因此,MAIST在集成体单元(IBU)软件上实现了90.5%的分支覆盖率和77.8%的MC/DC覆盖率。此外,通过减少53.3%的覆盖率测试的手工测试工作,它降低了IBU覆盖率测试的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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