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- W2913120293 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." @default.
- W2913120293 created "2019-02-21" @default.
- W2913120293 creator A5014194740 @default.
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- W2913120293 date "2018-11-01" @default.
- W2913120293 modified "2023-09-27" @default.
- W2913120293 title "NEAT Algorithm for Testsuite generation in Automated Software Testing" @default.
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- W2913120293 doi "https://doi.org/10.1109/ssci.2018.8628668" @default.
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