TY  - JOUR
T1  - The Effects of Replacement Strategies of Genetic Algorithm in Regression Test Case Prioritizatoin of Selected Test Cases
AU - Musa, Samaila AU - Sultan, Abu Bakar Md AU - Ghani, Abdul Azim Bin Abd AU - Baharom, Salmi 
JO  - International Journal of Soft Computing
VL  - 10
IS  - 6
SP  - 359
EP  - 368
PY  - 2015
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2015.359.368
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2015.359.368
KW  - Regression testing
KW  -Evolutionary algorithm
KW  -regression test case prioritization
KW  -GA replacement strategy
KW  -Malaysia
AB  - Regression testing is one of the software maintenance activities that is time consuming and expensive. Design-based regression testing approaches have been proposed to address changes at higher levels of abstraction, these approaches may not detect changes in the method body and several of the code based addresses procedural programs. This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. The goal is to compare different replacement strategies of GA and select the best strategy that will make prioritization to order selected test cases based on their fitness. We provide case studies to demonstrate the differences between the strategies. We measured the performances of each replacement strategy in GA by using Average Percentage of rate of Faults Detection (APFD) metric. It was observed from the results that replacement of worst individual and replacing the parent increased the effectiveness of regression testing compared with two other replacement strategies in term of rate of fault detection.
ER  -