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Context-aware applications are emerging applications in the modern era of computing. These applications can determine and adapt to situational context to provide better user experience. Testing these applications is not straightforward. Constantly changing nature of context makes testing context-aware application is a challenging task. To uncover a defect in context-aware application, a test engineer needs activity (sequence of actions) and context information (context data); this makes test case development a difficult task. Conventional test case development methodologies do not cater for context information. Besides, conventional applications have only one input source, but context-aware application must obtain data from many sources to infer the context. Yet another issue that these applications often face is the noisy data problem as input data collected from physical sensors could be noisy. Test adequacy criteria are used as test stoppage rule and define the quality of testing as well as for generating test suites. Test adequacy criteria is helpful to control the cost of testing as well as determining/establishing confidence in the software product quality. A number of test adequacy criteria exist for testing conventional applications, but the same is not true for context-aware applications. Defining test adequacy criteria and test coverage measures for context-aware applications warrants further research. Several techniques have been developed by researchers to generate and execute test cases for context-aware applications; however, end-to-end testing and result analysis of executed test cases still remains a grueling task for the test engineers. The aim of this study is to automate end-to-end functional testing, analysis of the generated test results as well as functional/requirement coverage assessment. Moreover, we also present a confidence assessment template for result analysis. Test engineers can use our proposed framework to assess the requirement coverage. Our proposed framework will reduce testing time, efforts and cost thus enabling test engineers to execute more testing cycles to attain higher degree of test coverage.

In the modern era of mobile computing, context-aware computing is an emerging paradigm due to its widespread applications. Context-aware applications are gaining increasing popularity in our daily lives since these applications can determine and react according to the situational context and help users to enhance usability experience. However, testing these applications is not straightforward since it poses several challenges, such as generating test data, designing context-coupled test cases, and so on. However, the testing process can be automated to a greater extent by employing model-based testing technique for context-aware applications. To achieve this goal, it is necessary to automate model transformation, test data generation, and test case execution processes. In this paper, we propose an approach for behavior modeling of context-aware application by extending the UML activity diagram. We also propose an automated model transformation approach to transform the development model, i.e., extended UML activity diagram into the testing model in the form of function nets. The objective of this paper is to automate the context-coupled test case generation and execution. We propose a functional testing framework for automated execution of keyword-based test cases. Our functional testing framework can reduce the testing time and cost, thus enabling the test engineers to execute more testing cycles to attain a higher degree of test coverage.