A Review of Artificial Intelligence Techniques in Software Testing and Quality Assurance

This review investigates the recent advances in Artificial Intelligence techniques applied to software testing and quality assurance. The study aims to analyze how machine learning, deep learning, and reinforcement learning models enhance test automation and defect prediction. Using ten Q۱/Q۲ research articles published between ۲۰۲۳ and ۲۰۲۵, a systematic literature review was conducted to identify trends, benefits, and challenges in AI-driven testing. The findings highlight improved efficiency, adaptability, and fault detection accuracy, alongside persistent issues in data quality, explainability, and ethical integration across modern testing pipelines.

کلیدواژه ها:

Artificial Intelligence ، Software Testing ، Quality Assurance ، Machine Learning ، Test Automation