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

ICTACT Journal on Soft Computing ( Volume: 11 , Issue: 1 )

Abstract

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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
Pages
2227-2231

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