Performance analysis of intelligent Techniques for test suite Minimization

Abstract

Regression testing is a significant testing process performed over newlinemodified software It is essential to ensure that the software will behave newlinecorrectly and the modifications have not impaired the quality of the software newlineAlthough regression testing is widely used in industry it is often performed newlineInadequately As a result software quality decreases over the software s newlineLifetime Regression test suites tend to grow over time as new test cases are newlineadded to exercise new functionality or to target newly discovered faults As newlinethe size of the test suites increases the complexity for managing and running newlinethose test suites also increases Therefore it is necessary to minimize the size newlineof the test suits newlineTo address this problem researchers have spent a great deal of effort newlinefor creating and studying various methodologies to improve the effectiveness newlineof regression testing In the literature Test Suite Minimization TSM has newlinebeen widely used to minimize the size of the test suites In general TSM newlinetechniques eliminate the redundant test cases from the test suite based on newlinesome criteria However reducing the size of a test suite might affect its newlineability to reveal faults Hence new approaches are needed to overcome the newlineshortcomings of the existing approaches This thesis proposes three different newlinetechniques to reduce the test suite of modern applications using intelligent newlinetechniques newlineIn the first technique this thesis presents a modified Search Based newlineSoftware Engineering SBSE technique known as Conceptual Genetic newlineAlgorithm CGA for TSM while trying to maintain the overall effectiveness newlineof the reduced test suite newline newline