A HYBRID BAT APPROACH WITH TABU SEARCH ALGORITHM FOR TEST CASE SELECTION IN OBJECT ORIENTED TESTING

Abstract
All research made on the Object- Oriented (OO) paradigms focus on the fundamentals of analysis, programming, and design. The primary problem found in testing the systems which are object-oriented is a methodology of standard testing and this may not be very useful. The test case may execute software using a new set consisting of some input values and will then compare them to the output to check if the test has passed. An optimum test case set is obtained using a process of selection that is viewed to be a problem of optimization. Thus, metaheuristic optimizing or searching is a technique used often for optimizing or searching which is used in automated testing of software. The BAT Algorithm is a metaheuristic that is dependent on the property of echolocation of the miniaturized scale bats. The property further controls the conduct of search of the bats of a small-scale and making them discover prey thus enabling them to identify distinctive types of bugs irrespective of the fact they are found to be dull. The work also proposed a new and hybrid Tabu search algorithm using the BAT for the selection of test case.

Authors
B Geetha1, D Jeya Mala2
Anna University, Chennai, India1, Fatima college, India2

Keywords
Object Oriented (OO) Paradigms, Hybrid Tabu Search, Bat Algorithm, Test Case Selection
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 11 , Issue: 1 )
Date of Publication :
October 2020
DOI :

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