Department of Software Engineering

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Subject: search.filters.subject.Android Application

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    Mutation Testing Techniques for Android Applications: A Comparative Study
    (International Conference on Multidisciplinary Engineering and Applied Science, 2023-02-02) Ibrahim Anka Salihu
    Mobile applications are becoming increasingly used to achieve various computing needs. Hence, it is essential to guarantee quality of the applications. Software testing has been the main activity for ensuring the quality of software, however, it is a critical and costly activity. Furthermore, code coverage is commonly used as metric for verifying the effectiveness of testing technique. However, numerous researchers and experts claimed that considering code coverage only to ascertain the testing quality is not enough to ensure quality of apps. In view of this, mutation testing has been introduced to complement the procedure by assuring that apps behave as expected and are released free of faults. Several techniques/tools were proposed based on different syntax and mutation operators. This study presents a comparative study of six (6) mutation techniques/tools for Android applications to highlight their strengths and weakness which will give an insight to researchers on the directions for further research
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    Comparative Analysis of Fully Automated Testing Techniques for Android Applications
    (International Conference on Multidisciplinary Engineering and Applied Sciences (ICMEAS-2023), 2023-02-02) Ibrahim Anka Salihu
    The software testing community has continued to research and develop new ways of testing Android mobile applications to ensure an application function as expected and serves its purpose. Given that every testing technique/tool has its strengths and weaknesses. This study aims to present a comparative analysis of fully automated techniques which automatically generate and execute test cases concurrently during runtime. We selected 10 fully automated techniques published from 2013 to 2023 techniques to identify the similarities and differences that exist among them. We clearly define the comparative criteria (such as the exploration method, systematic method, termination criterion, extraction criterion, and scheduling method) used for comparing the selected techniques. The analysis shows that most fully automated techniques adopt an active learning exploration approach for exploring the application under test (AUT). We also observed that only the techniques utilizing the active learning approach are capable of modelling and abstracting the graphic user interface (GUI) of the AUT, others randomly select events to be fired into the AUT.