Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Dominators, super blocks, and program coverage
POPL '94 Proceedings of the 21st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
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Proceedings of the 1998 ACM SIGSOFT international symposium on Software testing and analysis
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ATS '00 Proceedings of the 9th Asian Test Symposium
Generating Test Data for Branch Coverage
ASE '00 Proceedings of the 15th IEEE international conference on Automated software engineering
ICSTW '08 Proceedings of the 2008 IEEE International Conference on Software Testing Verification and Validation Workshop
Automatic Path-Oriented Test Data Generation Using a Multi-population Genetic Algorithm
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
The economics of software quality assurance
AFIPS '76 Proceedings of the June 7-10, 1976, national computer conference and exposition
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A new method called EPDG-GA which utilizes the Edge Partitions Dominator Graph (EPDG) and Genetic Algorithm (GA) for branch coverage testing is presented in this paper. First, a set of Critical Branches (CBs) are obtained by analyzing the EPDG of the tested program, while covering all the CBs implies covering all the branches of the Control Flow Graph (CFG). Then, the fitness functions are instrumented in the right position by analyzing the Pre-Dominator Tree (PreDT), and two metrics are developed to prioritize the CBs. Coverage-Table is established to record the CBs information and keeps track of whether a branch is executed or not. GA is used to generate test data to cover CBs so as to cover all the branches. The comparison results show that this approach is more efficient than random testing approach.