Automating the Testing and Maintenance Phases of Java Applications with Advanced Data Analysis Techniques.
DOI:
https://doi.org/10.56472/ICCSAIML25-161Keywords:
Automated Testing, Java Applications, Data Analysis Techniques, Artificial Intelligence, Machine Learning, Test Case Generation, Test Maintenance, Software Testing ChallengesAbstract
The increasing complexity of Java applications necessitates efficient strategies for testing and maintenance. This paper explores the integration of advanced data analysis techniques into the automation of testing and maintenance phases of Java applications. We examine the benefits and limitations of automated testing, emphasizing aspects such as test reusability, repeatability, coverage, and the reduction of manual effort. Additionally, we analyze the role of artificial intelligence and machine learning in enhancing test case generation, execution, and maintenance. By leveraging large language models and other AI-driven tools, developers can achieve more efficient and effective testing processes. The paper also addresses the challenges associated with implementing automated testing, including initial setup costs, tool selection, and training requirements. Through a comprehensive review of current practices and future trends, we provide insights into optimizing the testing and maintenance lifecycle of Java applications
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