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Characterizing testing methods for context-aware software systems: Results from a quasi-systematic literature review

机译:表征上下文感知软件系统的测试方法:准系统文献综述的结果

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Context-Aware Software Systems (CASS) use environmental information to provide better service to the systems’ actors to fulfill their goals. Testing of ubiquitous software systems can be challenging since it is unlikely that, while designing the test cases, the tester can identify all possible context variations. A quasi-Systematic Literature Review has been undertaken to characterize the methods usually used for testing CASS. The analysis and generation of knowledge in this work rely on classifying the extracted information. Established taxonomies of software testing and context-aware were used to characterize and interpret the findings. The results show that, although it is possible to observe the utilization of some software testing methods, few empirical studies are evaluating such methods when testing CASS. The selected technical literature conveys a lack of consensus on the understanding of context and CASS, and on the meaning of software testing. Furthermore, context variation in CASS has only been partially addressed by the identified approaches. They either rely on simulating context or in fixing the values of context variables during testing. We argue that the tests of context-aware software systems need to deal with the diversity of context instead of mitigating their effects.
机译:上下文感知软件系统(CASS)使用环境信息为系统参与者提供更好的服务,以实现他们的目标。无处不在的软件系统的测试可能具有挑战性,因为在设计测试用例时,测试人员不太可能识别所有可能的上下文变化。进行了准系统文献综述,以表征通常用于测试CASS的方法。这项工作中知识的分析和生成依赖于对提取的信息进行分类。建立的软件测试和上下文感知分类法用于表征和解释发现。结果表明,尽管可以观察到某些软件测试方法的使用,但是在测试CASS时,很少有经验研究对这种方法进行评估。所选的技术文献缺乏对上下文和CASS的理解以及对软件测试的含义的共识。此外,已确定的方法仅部分解决了CASS中的上下文变化。它们要么依赖于模拟上下文,要么依赖于在测试过程中固定上下文变量的值。我们认为,上下文感知软件系统的测试需要处理上下文的多样性,而不是减轻其影响。

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