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A reinforcement learning-based approach to testing GUI of moblie applications.

, , , , and . World Wide Web (WWW), 27 (2): 16 (March 2024)

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Supporting maintenance and testing for AI functions of mobile apps based on user reviews: An empirical study on plant identification apps., , , and . J. Softw. Evol. Process., (November 2023)Recovering Semantic Traceability between Requirements and Source Code Using Feature Representation Techniques., , , and . QRS, page 873-882. IEEE, (2021)A reinforcement learning-based approach to testing GUI of moblie applications., , , , and . World Wide Web (WWW), 27 (2): 16 (March 2024)Identifying security issues for mobile applications based on user review summarization., , and . Inf. Softw. Technol., (2020)A Deep Reinforcement Learning-Based Approach for Android GUI Testing., , , and . APWeb/WAIM (3), volume 13423 of Lecture Notes in Computer Science, page 262-276. Springer, (2022)MT4ImgRec: A Metamorphic Testing Tool for Image Recognition Software., , and . SEKE, page 636. KSI Research Inc., (2021)Semantic Feature Learning based on Double Sequences Structure for Software Defect Number Prediction., , , and . QRS, page 157-166. IEEE, (2022)Multi-Objective White-Box Test Input Selection for Deep Neural Network Model Enhancement., , and . ISSRE, page 521-532. IEEE, (2023)DeepTD: Diversity-Guided Deep Neural Network Test Generation., , , and . SETTA, volume 14464 of Lecture Notes in Computer Science, page 419-433. Springer, (2023)FATS: Feature Distribution Analysis-Based Test Selection for Deep Learning Enhancement., , , , and . IEEE Trans. Big Data, 10 (2): 132-145 (April 2024)