Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Automated test data generation for programs with procedures
ISSTA '96 Proceedings of the 1996 ACM SIGSOFT international symposium on Software testing and analysis
Automatic test data generation for path testing using GAs
Information Sciences: an International Journal
Semi-proving: an integrated method based on global symbolic evaluation and metamorphic testing
ISSTA '02 Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
The Elements of Programming Style
The Elements of Programming Style
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
Suitability of Evolutionary Algorithms for Evolutionary Testing
COMPSAC '02 Proceedings of the 26th International Computer Software and Applications Conference on Prolonging Software Life: Development and Redevelopment
Fitness Function Design To Improve Evolutionary Structural Testing
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A new approach to program testing
Proceedings of the international conference on Reliable software
Breeding Software Test Cases with Genetic Algorithms
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 9 - Volume 9
Consistency techniques for interprocedural test data generation
Proceedings of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering
The Art of Software Testing
Software Testing Research: Achievements, Challenges, Dreams
FOSE '07 2007 Future of Software Engineering
GA-based multiple paths test data generator
Computers and Operations Research
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
Comparison of Two Fitness Functions for GA-Based Path-Oriented Test Data Generation
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 04
Evolutionary testing: a case study
HVC'06 Proceedings of the 2nd international Haifa verification conference on Hardware and software, verification and testing
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Automatic path-oriented test data generation is not only a key problem but a hot issue in the research area of software testing today. Genetic algorithm (GA) has been used to path-oriented test data generation since 1992 and outperforms other approaches. A fitness function based on branch distance (BDBFF) has been applied in GA-based pathoriented test data generation. To investigate performance of this method, a triangle classification program was chosen as the benchmark. Using binary string coding, four combinations of selection and crossover operations were used to study performance of this method. Furthermore, the relationship between size of search space and average number of test data or average time was analyzed.