Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Constraint-Based Automatic Test Data Generation
IEEE Transactions on Software Engineering
The chaining approach for software test data generation
ACM Transactions on Software Engineering and Methodology (TOSEM)
Assertion-oriented automated test data generation
Proceedings of the 18th international conference on Software engineering
Automated program flaw finding using simulated annealing
Proceedings of the 1998 ACM SIGSOFT international symposium on Software testing and analysis
Automated test-data generation for exception conditions
Software—Practice & Experience
Symbolic execution and program testing
Communications of the ACM
Fitness Function Design To Improve Evolutionary Structural Testing
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
SELECT—a formal system for testing and debugging programs by symbolic execution
Proceedings of the international conference on Reliable software
Testing the Results of Static Worst-Case Execution-Time Analysis
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
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
Empirical Software Engineering
Branch-Coverage Testability Transformation for Unstructured Programs
The Computer Journal
Data Dependence Based Testability Transformation in Automated Test Generation
ISSRE '05 Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering
Evolutionary Testing Using an Extended Chaining Approach
Evolutionary Computation
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
Automatic Generation of Floating-Point Test Data
IEEE Transactions on Software Engineering
A System to Generate Test Data and Symbolically Execute Programs
IEEE Transactions on Software Engineering
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Evolutionary testing of flag conditions
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
Search-based failure discovery using testability transformations to generate pseudo-oracles
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
An evaluation of differential evolution in software test data generation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
The relationship between search based software engineering and predictive modeling
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
A multiple-population genetic algorithm for branch coverage test data generation
Software Quality Control
Evolutionary algorithms for the multi-objective test data generation problem
Software—Practice & Experience
An orchestrated survey of methodologies for automated software test case generation
Journal of Systems and Software
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Evolutionary testing is an approach to automating test data generation that uses an evolutionary algorithm to search a test object's input domain for test data. Nested predicates can cause problems for evolutionary testing, because information needed for guiding the search only becomes available as each nested conditional is satisfied. This means that the search process can overfit to early information, making it harder, and sometimes near impossible, to satisfy constraints that only become apparent later in the search. The article presents a testability transformation that allows the evaluation of all nested conditionals at once. Two empirical studies are presented. The first study shows that the form of nesting handled is prevalent in practice. The second study shows how the approach improves evolutionary test data generation.