Test Case Generation Approach for Android Applications using Reinforcement Learning
Received: 5 April 2024 2024 | Revised: 25 April 2024 | Accepted: 27 April 2024 | Online: 2 August 2024
Corresponding author: Asmau Usman
Abstract
Mobile applications can recognize their computational setting and adjust and respond to actions in the context. This is known as context-aware computing. Testing context-aware applications is difficult due to their dynamic nature, as the context is constantly changing. Most mobile testing tools and approaches focus only on GUI events, adding to the deficient coverage of applications throughout testing. Generating test cases for various context events in Android applications can be achieved using reinforcement learning algorithms. This study proposes an approach for generating Android application test cases based on Expected State-Action-Reward-State-Action (E-SARSA), considering GUI and context events for effective testing. The proposed method was experimentally evaluated on eight Android applications, showing 48-96% line of code coverage across them, which was higher than Q-testing and SARSA.
Keywords:
Android app, GUI event, test case generation, context event, reinforcement learning, expected SarsaDownloads
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Copyright (c) 2024 Asmau Usman, Moussa Mahamat Boukar, Muhammed Aliyu Suleiman, Ibrahim Anka Salihu
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