Date of Publication :18th May 2017

Abstract: In software development life cycle (SDLC), testing phase is the most important phase. Without testing we can’t give quality software or risk free software to the client. Software testing process typically consumes at least 50% of the total cost involved in software development. In regression testing there evolves the number of test cases. Due to some constraints, it is impractical to test all of them. Therefore to overcome this problem, testing is done using selected test cases to reduce the testing effort and get the desired result accurately. In this paper, the algorithms which are discussed imitate the processes running in nature. And due to this these process are named as “Nature Inspired Algorithms”. The algorithms inspired from human body and its working and the algorithms inspired from the working of groups of social agents like ants, bees, and insects are the two classes of solving such Problems. This emerging new era is highly unexplored young for the research. The Algorithm proposed here uses swarm based intelligence technique on Maximum coverage to select the best of breed test case to evaluate any errors in the development cycle therefore the BCO produce optimal no. of test cases solving optimization problem.

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