AI-Driven Test Case Generation and Optimization

-, Mohammad Saif (2024) AI-Driven Test Case Generation and Optimization. Masters thesis, Dublin, National College of Ireland.

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Abstract

The aim of this research is to develop an AI-Driven model to enhance efficiency and effectiveness of software testing by generating and ordering testcases using Natural language Processing (NLP) and Reinforcement Learning (RL) techniques. The traditional software testing methods are time-consuming and require significant manual effort, which often leads to inefficiency and missing test coverage. This study utilizes NLP to automatically extract test cases from software requirements documents and applies RL to order test execution sequence. The integration of these technologies aims to maximize test coverage, improve testing efficiency and saving time. Through automated test case generation and optimization, this research aims to reduce test execution time and enhance test coverage, thereby supporting more reliable and efficient software development practices. The findings from this study highlight the potential impact of combining NLP and RL in automating software testing process, promising substantial improvements in software quality assurance and development workflows.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Kazmi, Aqeel UNSPECIFIED
Uncontrolled Keywords:	AI; ML; NLP; RL; Test cases; DQN; A2C; SRS
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence T Technology > T Technology (General) > Information Technology > Cloud computing P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	03 Jul 2025 08:18
Last Modified:	03 Jul 2025 08:25
URI:	https://norma.ncirl.ie/id/eprint/8004

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