American Journal of Information Science and Computer Engineering Vol. 1, No. 1, 2015, pp. 10-20 http://www.aiscience.org/journal/ajisce * Corresponding author Email address: er.aakanksha24@gmail.com (A. Pandey), Jayant_shekhar@hotmail.com (J. Shekher) Optimization the Test Suite of Regression Testing Using Metaherustic Searching Technique Aakanksha Pandey 1, * , Jayant Shekher 2 1 Computer Science & Engineering, SRM University, NCR Campus, Modinagar, Ghaziabad, India 2 Computer Science & Engineering, Subharti University, Meerut, India Abstract This proposed technique investigates is for the reduction of the test suit with the use of metaheuristic approach this technique is known as genetic algorithm. The result is showing like with the help of regression testing we can reduce the size n cost of the test suit significantly the very important features of the test suit that we need to take in consideration is “test suit reduction”. Here we have uses the algorithm that is the combination of the test-execution cost criteria and block based coverage criteria, these new criteria with that we can make the prominent decision for reducing the test suit. Here for the test-suit coverage criteria other criteria such as risk or fault-detection effectiveness, or combination of this criterion we have used the approach is greedy algorithm that is the sub set selection problem which is NP complete. Keywords Metaheuristic Approach, Genetic Algorithm, Regression Testing, Test Suite Received: April 16, 2015 / Accepted: May 3, 2015 / Published online: June 3, 2015 @ 2015 The Authors. Published by American Institute of Science. This Open Access article is under the CC BY-NC license. http://creativecommons.org/licenses/by-nc/4.0/ 1. Introduction The software testing basically depends on three factors test case generation, test execution, and test evaluation. As the prevasiness of software has increased over decades, testing has become a business – critical part of the software lifecycle. Testing is the very important and unavoidable part of the any software life cycle, testing cannot guarantee the absence of defects. The problem at hand is to select a subset of test cases for all possible test cases with a high chance of detecting defects. Standard design for the test cases allows measurements of testing performed. The main aim of the testing is to detect the failure of the software that detect may be discovered or corrected. Although testing can precisely determine the correctness of software under the assumption of some specific hypotheses. A very basic and fundamental problem with testing is like it might be possible that testing is feasible with all the combinations of input and preconditions. In order to “retest all” is the very expensive and time taking task so here we are using regression test selection is perform to optimize the cost . if we are talking about the classification of RTS that we can divide this into three categories Coverage techniques, Minimization techniques and Safe techniques. One more technique we are using here for the optimization of the test suits i.e. Genetic algorithm. This technique we can apply on all kind of problems even we can use this for the NP hard also. Here we are using the metaheuristic approach to reduce the test suit in optimal (minimum) time.‘Meta‘ means abstract and a ‘heuristic‘ is a search, Metaheuristic have played a very important role to optimize the test suits , this is strategy to guide all the search process in order to provide sub optional solution in a perfect reasonable time . Generally the metaheuristic approach is approximate and non-