软件系统运行时适应性验证的基于模型的回归测试选择

M. Al-Refai, Sudipto Ghosh, W. Cazzola
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引用次数: 14

摘要

越来越多的现代软件系统需要在不停止其执行的情况下在运行时进行调整。运行时适应可能会在现有功能中引入错误,因此,必须在执行适应之后,但在将适应部署到正在运行的系统之前进行回归测试。回归测试必须在时间和资源限制下完成。因此,需要测试选择技术来减少回归测试的成本。FiGA框架提供了从代码到模型再返回的完整循环,允许在不停止执行的情况下对运行中的Java系统进行细粒度的基于模型的调整和验证。在本文中,我们提出了一种基于模型的测试选择方法,用于在验证活动期间与FiGA框架一起使用的回归测试。评估结果表明,我们的方法能够减少所选择的测试用例的数量,并且所选择的测试用例的模型级故障检测能力从不低于原始测试用例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-Based Regression Test Selection for Validating Runtime Adaptation of Software Systems
An increasing number of modern software systems need to be adapted at runtime without stopping their execution. Runtime adaptations can introduce faults in existing functionality, and thus, regression testing must be conducted after an adaptation is performed but before the adaptation is deployed to the running system. Regression testing must be completed subject to time and resource constraints. Thus, test selection techniques are needed to reduce the cost of regression testing. The FiGA framework provides a complete loop from code to models and back that allows fine-grained model-based adaptation and validation of running Java systems without stopping their execution. In this paper we present a model-based test selection approach for regression testing during the validation activity to be used with the FiGA framework. The evaluation results show that our approach was able to reduce the number of selected test cases, and that the model-level fault detection ability of the selected test cases was never lower than that of the original test cases.
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