Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Software unit test coverage and adequacy
ACM Computing Surveys (CSUR)
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Evolutionary Testing Using an Extended Chaining Approach
Evolutionary Computation
Applying particle swarm optimization to software testing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A tabu search algorithm for structural software testing
Computers and Operations Research
Automatic, evolutionary test data generation for dynamic software testing
Journal of Systems and Software
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
A quantum-modeled K-means clustering algorithm for multi-band image segmentation
Proceedings of the 2012 ACM Research in Applied Computation Symposium
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In this paper we have described an application of the discrete quantum (inspired) particle swarm optimization (QPSO) technique proposed by Yang, Wang and Jiao [7] to the problem of automated software test data generation. The application has been experimentally evaluated on benchmark programs and results of these experiments are presented. The role of critical QPSO parameters on test data generation performance has been studied and based on the observations an adaptive version (AQPSO) has been designed and its performance compared with QPSO.