Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Proceedings of the third international conference on Genetic algorithms
Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Crossover, Macromutationand, and Population-Based Search
Proceedings of the 6th International Conference on Genetic Algorithms
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Fitness Function Design To Improve Evolutionary Structural Testing
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Instrumenting Programs With Flag Variables For Test Data Search By Genetic Algorithms
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Improving Evolutionary Testing By Flag Removal
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An Automated Framework for Structural Test-Data Generation
ASE '98 Proceedings of the 13th IEEE international conference on Automated software engineering
IEEE Transactions on Software Engineering
Evolutionary testing in the presence of loop-assigned flags: a testability transformation approach
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Branch-Coverage Testability Transformation for Unstructured Programs
The Computer Journal
Proceedings of the 2007 international symposium on Software testing and analysis
The impact of input domain reduction on search-based test data generation
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Handling dynamic data structures in search based testing
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Ignoble Trails - Where Crossover Is Provably Harmful
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Empirical evaluation of a nesting testability transformation for evolutionary testing
ACM Transactions on Software Engineering and Methodology (TOSEM)
Real royal road functions-where crossover provably is essential
Discrete Applied Mathematics - Special issue: Boolean and pseudo-boolean funtions
Evolutionary testing of flag conditions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
The state problem for evolutionary testing
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
IEEE Transactions on Software Engineering
Testability transformation: program transformation to improve testability
Formal methods and testing
It Does Matter How You Normalise the Branch Distance in Search Based Software Testing
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
An empirical investigation into branch coverage for C programs using CUTE and AUSTIN
Journal of Systems and Software
SSBSE '10 Proceedings of the 2nd International Symposium on Search Based Software Engineering
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Search based software test data generation for structural testing: a perspective
ACM SIGSOFT Software Engineering Notes
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Context: Genetic Algorithms are a popular search-based optimisation technique for automatically generating test inputs for structural coverage of a program, but there has been little work investigating the class of programs for which they will perform well. Objective: This paper presents and evaluates a series of program factors that are hypothesised to affect the performance of crossover, a key search operator in Genetic Algorithms, when searching for inputs that cover the branching structure of a C function. Method: Each program factor is evaluated with example programs using Genetic Algorithms with and without crossover. Experiments are also performed to test whether crossover is acting as macro-mutation operator rather than usefully recombining the component parts of input vectors when searching for test data. Results: The results show that crossover has an impact for each of the program factors studied. Conclusion: It is concluded crossover plays an increasingly important role for programs with large, multi-dimensional input spaces, where the target structure's input condition breaks down into independent sub-problems for which solutions may be sought in parallel. Furthermore, it is found that crossover can be inhibited when the program under test is unstructured or involves nested conditional statements; and when intermediate variables are used in branching conditions, as opposed to direct input values.