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Title: NEAT Algorithm for Testsuite generation in Automated Software Testing
Authors: Raj, H.L.P.
Chandrasekaran, K.
Issue Date: 2019
Citation: Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018, 2019, Vol., , pp.2361-2368
Abstract: Software testing is one of the most essential and an indispensable part of Software production life cycle. Software testing helps in validating if the product meets with the requirements or not, and also testing helps to validate the performance of the product. Unfortunately, this process takes up about 50% of the production time and budget, due to its laboriosity. Hence, in order to reduce the time it takes, Automated Software Testing becomes essential. Here we propose a novel idea of using Machine Learning for automatically generating the test suites. In this paper we present an approach that uses NEAT (Neuroevolution of Augmenting Topologies) Algorithm to automatically generate new test suites or for improving the coverage of already produced test suite. Our approach automatically generates test suites for white box testing. White box testing refers to testing of the internal structure and the working of the Software Under Test. � 2018 IEEE.
Appears in Collections:2. Conference Papers

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