Artificial Intelligence based effective algorithm for Software Testing
A Genetic Algorithm perspective
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Artificial Intelligence algorithms were great in their use in practical life. After successful application of various computation techniques, a strong need arose for development of Intelligent Systems and thus started a new era of Soft Computing. Genetic Algorithm is one such soft computing technique that mimics the nature and has all the potential of a computation technique. Genetic algorithms are computing algorithms constructed in analogy with the process of evolution. Genetic Algorithms are a class of stochastic search methods that try to find good solutions to difficult optimization probl...
Artificial Intelligence algorithms were great in their use in practical life. After successful application of various computation techniques, a strong need arose for development of Intelligent Systems and thus started a new era of Soft Computing. Genetic Algorithm is one such soft computing technique that mimics the nature and has all the potential of a computation technique. Genetic algorithms are computing algorithms constructed in analogy with the process of evolution. Genetic Algorithms are a class of stochastic search methods that try to find good solutions to difficult optimization problems by mimicking natural evolution. Over the past three decades, genetic algorithms have proved themselves successful in solving multitudinous problems from highly diverse domains including optimization, automatic programming, electronic-circuit design, telecommunications, networks, finance, economics, image analysis, signal processing, music and art. With these applications of genetic algorithms it is possible to use genetic algorithms in Software Engineering to automate testing process.
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