Survey on Test Generation Using Machine Learning Technique
Naresh E1, Vijaya Kumar B P2, Madhuri D Naik3
1Naresh E, Shri Ramdeobaba College of Engineering and Management, Ramdeo Tekdi, Gittikhadan, Katol Road, Nagpur (Maharashtra), India.
2Vijaya Kumar B P, Shri Ramdeobaba College of Engineering and Management, Ramdeo Tekdi, Gittikhadan, Katol Road, Nagpur (Maharashtra), India.
3Madhuri D Naik, Shri Ramdeobaba College of Engineering and Management, Ramdeo Tekdi, Gittikhadan, Katol Road, Nagpur (Maharashtra), India.
Manuscript received on 24 March 2019 | Revised Manuscript received on 05 April 2019 | Manuscript Published on 18 April 2019 | PP: 562-566 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03090376S19/2019©BEIESP
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© 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 and maintenance requires a considerable amount of time in the software lifecycle in order to have a quality product. Recent usage of machine learning algorithms in testing has rapidly increased and different testing type uses different machine learning algorithm depending on the test suits, which helps in automating the test cases in order to decrease the manual effort, which in turn helps in reduction of cost and time spent on the project by the software engineer. An overview of advantages are discussed for various software testing and machine learning techniques is provided along with some of the research on various combination used in order to generate test cases and test suites which are more optimized and performance enhanced.
Keywords: Software Testing, Machine Learning, Software Engineering.
Scope of the Article: Machine Learning