Effective unit-testing in model-based software development

Damodaram Kamma, Pooja Maruthi
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引用次数: 5

Abstract

Model-based software development is extensively used in avionics and automotive safety critical control software applications. In model-based software development, highly optimized code is generated automatically from models. Such code is often hard to understand and this can make it difficult to write test cases. Therefore, in model based software development, test cases have to be derived based on the models to achieve coverage of code auto-generated from the models. Further, safety standards in those domains often demand effective unit-testing method to check functional requirements as well as achieve 100% code coverage. In this paper, we first discuss three methods for unit testing in model based software development, namely Modified Condition & Decision Coverage (MCDC), Classification tree and Exploratory methods. We then discuss results of our field study conducted on 3 live projects at Robert Bosch Engineering & Business Solutions Limited to check on the effectiveness of three approaches. Based on the results from our field study, we conclude that MCDC method along with boundary value analysis is most productive to check functional requirements as well as achieve 100% coverage of auto-generated code.
基于模型的软件开发中的有效单元测试
基于模型的软件开发广泛应用于航空电子和汽车安全关键控制软件应用。在基于模型的软件开发中,高度优化的代码是由模型自动生成的。这样的代码通常很难理解,这使得编写测试用例变得困难。因此,在基于模型的软件开发中,测试用例必须基于模型派生,以实现从模型自动生成的代码的覆盖。此外,这些领域中的安全标准通常需要有效的单元测试方法来检查功能需求以及实现100%的代码覆盖率。本文首先讨论了基于模型的软件开发中的三种单元测试方法,即修正条件与决策覆盖(Modified Condition & Decision Coverage, MCDC)、分类树和探索性方法。然后,我们讨论了我们在罗伯特博世工程与商业解决方案有限公司对3个现场项目进行的实地研究的结果,以检查三种方法的有效性。根据我们实地研究的结果,我们得出结论,MCDC方法以及边界值分析对于检查功能需求以及实现自动生成代码的100%覆盖率是最有效的。
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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