%0 Journal Article %T Software Testing using an Adaptive Genetic Algorithm %J Journal of AI and Data Mining %I Shahrood University of Technology %Z 2322-5211 %A Damia, A.H. %A Esnaashari, M. %A Parvizimosaed, M.R. %D 2021 %\ 11/01/2021 %V 9 %N 4 %P 465-474 %! Software Testing using an Adaptive Genetic Algorithm %K software test %K test data generation %K path coverage %K search algorithms %K Genetic Algorithm %R 10.22044/jadm.2021.10018.2138 %X In the structural software test, test data generation is essential. The problem of generating test data is a search problem, and for solving the problem, search algorithms can be used. Genetic algorithm is one of the most widely used algorithms in this field. Adjusting genetic algorithm parameters helps to increase the effectiveness of this algorithm. In this paper, the Adaptive Genetic Algorithm (AGA) is used to maintain the diversity of the population to test data generation based on path coverage criterion, which calculates the rate of recombination and mutation with the similarity between chromosomes and the amount of chromosome fitness during and around each algorithm. Experiments have shown that this method is faster for generating test data than other versions of the genetic algorithm used by others. %U https://jad.shahroodut.ac.ir/article_2142_5468f75a58341e0dbbd98cf44b82b9a7.pdf