Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Symbolic execution and program testing
Communications of the ACM
Art of Software Testing
Predicting Where Faults Can Hide from Testing
IEEE Software
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
Evolutionary test data generation: a comparison of fitness functions: Research Articles
Software—Practice & Experience
Adaptive software testing with fixed-memory feedback
Journal of Systems and Software
Using Genetic Algorithms to Aid Test-Data Generation for Data-Flow Coverage
APSEC '07 Proceedings of the 14th Asia-Pacific Software Engineering Conference
GA-based multiple paths test data generator
Computers and Operations Research
Automatic, evolutionary test data generation for dynamic software testing
Journal of Systems and Software
SLR: Path-Sensitive Analysis through Infeasible-Path Detection and Syntactic Language Refinement
SAS '08 Proceedings of the 15th international symposium on Static Analysis
Handling Constraints for Search Based Software Test Data Generation
ICSTW '08 Proceedings of the 2008 IEEE International Conference on Software Testing Verification and Validation Workshop
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
IEEE Transactions on Software Engineering
Grouping target paths for evolutionary generation of test data in parallel
Journal of Systems and Software
Heuristic search-based approach for automated test data generation: a survey
International Journal of Bio-Inspired Computation
Cellular automata based test data generation
ACM SIGSOFT Software Engineering Notes
Cellular-genetic test data generation
ACM SIGSOFT Software Engineering Notes
Artificial life and cellular automata based automated test case generator
ACM SIGSOFT Software Engineering Notes
Dynamic stopping criteria for search-based test data generation for path testing
Information and Software Technology
Generating test data for both path coverage and fault detection using genetic algorithms
Frontiers of Computer Science: Selected Publications from Chinese Universities
Automatic generation of basis test paths using variable length genetic algorithm
Information Processing Letters
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Abstract: Path-oriented test data generation is an important issue of software testing, but the efficiency of existing methods needs to be further improved. We focus on the problem of generating test data for many paths coverage, and present a method of evolutionary generation of test data for many paths coverage based on grouping. First, target paths are divided into several groups according to their similarities, and each group forms a sub-optimization problem, which transforms a complicated optimization problem into several simpler sub-optimization problems; then a domain-based fitness is designed when genetic algorithms are employed to solve these problems; finally, these sub-optimization problems are simplified along with the process of generating test data, hence improving the efficiency of generating test data. Having analyzed the performance of our method theoretically, we apply it in some typical programs under test, and compare it with some previous methods. The experimental results show that our method has advantage in the number of evaluations and uncovered target paths.