Raheja Sumedha, Singh Rajvir; International Journal of Advance Research, Ideas and Innovations in Technology © 2018, www.IJARIIT.com All Rights Reserved Page | 1504 ISSN: 2454-132X Impact factor: 4.295 (Volume 4, Issue 3) Available online at: www.ijariit.com A mapping study on test case selection based on nature-inspired algorithms Sumedha Raheja sumedharaheja@gmail.com Deenbandhu Chhotu Ram University of Science and Technology, Sonipat, Haryana Rajvir Singh rajvirsingh.cse@dcrustm.org Deenbandhu Chhotu Ram University of Science and Technology, Sonipat, Haryana ABSTRACT After delivery of software product for modification, in order to correct faults or for improving the performance or other attributes, we calculate software maintenance. For this there is need for regression testing, regression testing is used to check that no upcoming errors have been found throughout the maintenance phase. The abundant number of test suites consist of some repetitions/redundancies as the same fault/error may be covered by many test cases. Hence, it is recommended /advisable to decrease/reduce the test suite. Test case selection is one of the techniques used for reducing the number of test cases by selecting only those test cases from test suite which can detect all those faults which were detected by the whole test. This paper calculates the execution/performance of two Meta heuristic algorithm – Cuckoo search and Bat algorithm for selecting test cases. Performance evaluation deciding factors are no. of faults detected and execution time. Results are achieved by conducting experiments on a large scale. Keywords: Software Testing, Regression Testing, Bat Algorithm, Cuckoo Search Algorithm, Software Maintenance 1. INTRODUCTION Enhancement is required in each domain of life. A large portion of genuine enhancement issues is multi-objective. Relapse experiment determination is one such multi-target enhancement issue that has pulled in the analysts since most recent three decades due to the following reasons: a) Executing all the Test cases will require an unsuitable measure of time though there will be the weight of conveyance courses of events. b) Many Team Members should be adjusted for testing which is again impractical. c) Both the above will prompt a critical measure of time each time the Regression Testing is finished. More current metagraphy calculations roused by nature are developing and they turn out to be progressively famous. For instance, particles swarm optimization (PSO) was roused by fish and winged creature swarm insight, while the Firefly Algorithm was motivated by the glimmering example of tropical fireflies [2], [3], [6], [19], [20]. These nature-motivated metagraphy calculations have been utilized as, part of an extensive variety of improvement issues, including NP-difficult issues, for example, the voyaging salesperson issue [2], [3], [6]. The energy of all advanced metagraphy originates from the way that they copy the best element in nature, particularly organic frameworks developed from regular choice more than millions of years. Two vital qualities are a determination of the fittest and adjustment to nature. Numerically, these can be converted into two pivotal qualities of the cutting edge metagraphy: increase and expansion [3]. Heightening plans to look around the present best arrangements and select the best competitors or arrangements, while enhancement ensures the calculation can investigate the inquiry space effectively. This paper intends to plan another calculation, called Cuckoo Search (CS), in light of the intriguing rearing behavior for example, brood parasitism of specific types of cuckoos. We will initially present the rearing behavior of cuckoos, what's more, the attributes of L'evy flights of a few fowls and natural product flies, and afterward figure the new CS, trailed by its usage. At long last, we will