Test Case Generation Process using Soft Computing Techniques
Baswaraju Swathi1, Harshvardhan Tiwari2

1Baswaraju Swathi*, Research Scholar, CSE, Jain University Bangalore, Karnataka, India.
2Dr.Harshvardhan Tiwari, Associate Professor, Centre for Incubation, Innovation, Research and Consultancy, Jyothy Institute of Technology, Bengaluru, Karnataka, India. 

Manuscript received on October 19, 2019. | Revised Manuscript received on 25 October, 2019. | Manuscript published on November 10, 2019. | PP: 4824-4831 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4302119119/2019©BEIESP | DOI: 10.35940/ijitee.A4302.119119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Software testing is the SDLC’s important and most expensive step. Software testing is difficult and time-consuming work requiring a great deal of money for software development. Testing is both an operation that is static and adaptive. Software testing process deals with the creation of test cases, checking and validating either passed or failed test cases. It is unidealistic to check only the discerning parts of the material as a whole at once. It is not possible to test the whole system once, so selected parts of the code are considered for analysis. Since the input space of the Product Under Test (PUT) can be very large, it is important to analyze a representative subset of test cases. During software testing, the most important task is to build appropriate test cases. An effective set of test cases can detect more errors. Software testing always requires high deficiencies. Test cases are constructed using the test data. In the automation of software testing, the important task is to generate test data according to a given level of competence. The improved test data are determined using the test case development methodology and the test data adequacy criterion being applied. For increase the level of automation and performance, these aspects of test case development need to be studied. This paper studies the various test case generation techniques using soft computing techniques like Genetic Algorithm, Artificial Bee colony methods. Further an evaluation criterion for the test case generation process, empirical study of Code Coverage and its importance is discussed.
Keywords: Program Under Test, Test Case Generation, Test Data, Soft Computing, Genetic Algorithm, Artificial Bee Colony
Scope of the Article: Algorithm Engineering