Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
OSF DCE application development reference, revision 1.0
OSF DCE application development reference, revision 1.0
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolving Turing-Complete Programs for a Register Machine with Self-modifying Code
Proceedings of the 6th International Conference on Genetic Algorithms
Crossover, Macromutationand, and Population-Based Search
Proceedings of the 6th International Conference on Genetic Algorithms
Evolutionary Computation
Evolutionary software engineering, a review
Applied Soft Computing
Advances in Software Engineering
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A major strength of GAs is the ability to search large problem spaces, given a suitable fitness function. The feasibility of exploiting this strength of GAs to find software errors was explored by focusing on software APIs and commands that have completed development, hence are assumed to contain no, or very few, errors. A testing facility was developed in which a GA is used to generate API tests. The design of a fitness function which usefully guides the GA selection to find API errors, was the challenge. Initial results using the testing facility found two previously unreported exceptions in the test target API implementation, demonstrating this approach does appear to have potential.