Comparing Nature Propelled Meta-Heuristic Mutation Testing Techniques

Abstract— Mutation Testing is a white-box, unit testing technique widely used for the software quality assurance. This technique athough powerful, but is computationally expensive and this expense has barred mutation testing from becoming a popular software testing technique. However the recent engineering advancements have provided us with a number of ways for reducing the cost of mutation testing. There are a number of factors that are making mutation testing an expensive technique, one is high computational cost involved due to execution of large number of generated mutants, second being the huge amount of human effort involved for checking the output of mutant program with original one and for manually detecting the equivalent mutants. In this paper we have tried to closely review and analyze nature propelled meta-heuristic available techniques like ABC, PSO, PeSO for reducing the cost of mutation testing so that we can come up with a feasible and efficient cost reduction technique in mutation testing.

Index Terms— Computational cost, Cost reduction, Equivalent mutants, Mutation testing, Nature propelled techniques -ABC, PeSO, PSO.

INTRODUCTION

Mutation testing is a fault based, white – box unit testing technique that generally involves changing pieces of code to see if the test cases detect these changes and fails. It is a technique for testing software units that has great potential for improving the quality of testing, and thereby increasing the ability to assure the high reliability of critical software. The history of mutation testing can be traced back to 1971 in a student Richard Lipton„s paper. He gave this idea in his term paper titled “Fault Diagnosis of Computer Program” [1]. But there were many issues related to the feasibility of using it for practical applications. Later on in late 1970‟s major work was published on this subject [2] and then finally DeMillo et al. [4] and Hamlet [3] formally introduced mutation as a testing technique in their papers. Recent advances in mutation research have brought a practical mutation testing system closer to reality.
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