Test Case Generation and Prioritization Using Embedded Auto Encoder Model for Continuous Integration Environment

Abstract

Software testing plays a crucial role in ensuring the quality and reliability of newlinesoftware systems. Among various testing techniques, regression testing stands out as newlinean essential process for verifying that modifications to software do not adversely newlineaffect existing functionality. Despite its importance, regression testing faces newlinechallenges due to the escalating complexity of software systems and the sheer volume newlineof test cases involved. Our project aims to revolves around enhancing regression newlinetesting practices to address these challenges and optimize efficiency and newlineeffectiveness. By delving into innovative approaches such as model-based, code newlinebased, and specification-based regression testing, the research seeks to provide newlineinsights into improving the quality and reliability of software systems.Also by newlineacknowledging the drawbacks associated with regression testing, such as its resource newlineintensive nature, low prioritisation of test cases, increased human efforts, delayed newlinefeedback loops, and the risk of false positives or negatives, the research aims to make newlinesignificant strides, offering strategies to optimize regression testing efficiency, reduce newlineresource consumption, enhancing prioritization of test cases, decreasing human efforts newlineand also mitigate the risk of inaccurate test results by various optimisation techniques newlinelike newlineNeural newlineNetwork-Driven newlineRegression newlineTesting newlinePrioritization newlineand newlineVisualization(NND-RTP) with the objective of optimizing test case prioritization. newlineNND-RTP predicts relevant test cases post-codebase alterations, aiming to expedite newlinefault detection and resource optimization within software testing paradigms newline