Enhancing Web Application Reliability Through Integrated Sbst And Functional Testing

Abstract

This paper proposes an advanced methodology for software defect prediction and functional testing of websites, integrating traditional techniques with Search-Based Software Testing (SBST). The approach combines thorough manual testing, automated test execution, and machine learning-based defect prediction to ensure comprehensive coverage and accurate defect detection. Initial steps include detailed requirement analysis, test planning, and test case development, followed by manual and automated functional testing. The SBST process iteratively refines test cases through initialization, fitness evaluation, selection, crossover, mutation, and survivor selection, optimizing their effectiveness in identifying defects. Integration with CI/CD pipelines ensures continuous validation, while continuous monitoring and feedback facilitate ongoing improvement. Detailed reporting and analysis guide proactive measures, enhancing the overall quality and reliability of web applications.