A Comparative Study Of Regression Test Case Prioritization Methods In Software Quality Assurance

Regression testing plays a critical role in ensuring the continued functionality and quality of software as changes, updates, or bug fixes are implemented. Given the complexity and the growing size of modern software systems, managing large test suites efficiently is becoming increasingly difficult. This paper focuses on the importance of test case prioritization, a technique aimed at ordering test cases in a way that maximizes fault detection early while minimizing resource utilization. The study compares various theoretical models and methods of test case prioritization, including random, requirement-based, code-based, and model-based prioritization. It highlights the benefits of prioritization in improving test efficiency and the challenges associated with its implementation. Additionally, the paper reviews both traditional and advanced prioritization techniques, including risk-based prioritization and AI-driven methods, with a comparison of their effectiveness in different software development contexts. Finally, the paper discusses the challenges and limitations of current prioritization models and suggests future directions for improving prioritization techniques in regression testing.