Application of Genetic Algorithm and Particle Swarm Optimization in Software Testing

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Provided by: Iosrjournals
Topic: Software
Format: PDF
In this paper, the authors will describe a method for optimizing software testing by finding the most error prone paths in the program. This can be achieved by a meta-heuristic technique that is by using genetic algorithm and particle swarm optimization. As exhaustive software testing is not possible where software is tested with all the possible inputs, those parts of software are also tested which are not error prone. This paper is to generate test cases using both the algorithms and then comparative study is done between Particle swarm optimization and genetic algorithm.
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