Soft Computing Based Approaches for Software Testing: a Survey
Bipin Pandey1, Rituraj Jain2
1Bipin Pandey, Department of Computer Sc. & Engg., Vyas Institute of Engineering & Technology, Jodhpur, India.
2Rituraj Jain, Department of Computer Sc. & Engg., Vyas Institute of Engineering & Technology, Jodhpur, India.
Manuscript received on May 01, 2014. | Revised Manuscript received on May 03, 2014. | Manuscript published on May 05, 2014. | PP: 4-8 | Volume-4 Issue-2, May 2014. | Retrieval Number: B2170054214/2014©BEIESP
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©The Authors. Published By: 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 process of validation and verification of the software product which in turn deliver the reliable and quality oriented software product to users with lower maintenance cost, and more accurate and reliable results. Software testing effectiveness always depends on issues like generated test cases, prioritization of test cases etc. These issues demands on effort, time and cost of the testing. Many academicians and researchers are using soft computing based approached for better accuracy in testing. The aim of this research paper is to evaluate and compare soft computing approaches to do software testing and determine their usability and effectiveness.
Keywords: Black Box Testing, Fuzzy Logic, Genetic Algorithms, Neural Network, Soft Computing, Software Testing, Tabu Search, White Box testing.