Title :
Optimization of test suite-test case in regression test
Author :
Ansari, Ahlam S. A. ; Devadkar, Kailas K. ; Gharpure, Prachi
Author_Institution :
Dept. of Comput. Eng., Univ. of Mumbai, Mumbai, India
Abstract :
Exhaustive product evolution and testing is required to ensure the quality of product. Regression testing is crucial to ensure software excellence. Regression test cases are applied to assure that new or adapted features do not relapse the existing features. As innovative features are included, new test cases are generated to assess the new functionality, and then included in the existing pool of test cases, thus escalating the cost and the time required in performing regression test and this unswervingly impacts the release, laid plan and the quality of the product. Hence there is a need to select minimal test cases that will test all the functionalities of the engineered product and it must rigorously test the functionalities that have high risk exposure. Test Suite-Test Case Refinement Technique will reduce regression test case pool size, reduce regression testing time, cost & effort and also ensure the quality of the engineered product. This technique is a regression test case optimization technique that is a hybrid of Test Case Minimization based on specifications and Test Case Prioritization based on risk exposure. This approach will facilitate achievement of quality product with decreased regression testing time and cost yet uncover same amount of errors as the original test cases.
Keywords :
program testing; software quality; product quality; regression test; risk exposure; software excellence; test case minimization; test case prioritization; test suite-test case optimization; test suite-test case refinement technique; Conferences; Fault detection; Minimization; Optimization; Software; Software reliability; Testing; Regression Test; Risk Based Prioritization; Specification Based Selection; Test Case Optimization; Test Suite Minimization; Test Suite Prioritization;
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on
Conference_Location :
Enathi
Print_ISBN :
978-1-4799-1594-1
DOI :
10.1109/ICCIC.2013.6724206