Symbolic interpretation and tracing of PASCAL-programs
ICSE '78 Proceedings of the 3rd international conference on Software engineering
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
Observations in using parallel and sequential evolutionary algorithms for automatic software testing
Computers and Operations Research
Fitness calculation approach for the switch-case construct in evolutionary testing
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Empirical evaluation of a nesting testability transformation for evolutionary testing
ACM Transactions on Software Engineering and Methodology (TOSEM)
MC/DC automatic test input data generation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Dealing with inheritance in OO evolutionary testing
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Search-based failure discovery using testability transformations to generate pseudo-oracles
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Test-data generation guided by static defect detection
Journal of Computer Science and Technology
Evolutionary testing of software with function-assigned flags
Journal of Systems and Software
Comparing algorithms for search-based test data generation of matlab® simulink® models
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Iterative execution-feedback model-directed GUI testing
Information and Software Technology
An empirical investigation into branch coverage for C programs using CUTE and AUSTIN
Journal of Systems and Software
FloPSy: search-based floating point constraint solving for symbolic execution
ICTSS'10 Proceedings of the 22nd IFIP WG 6.1 international conference on Testing software and systems
A study of the bi-objective next release problem
Empirical Software Engineering
Ten years of search based software engineering: a bibliometric analysis
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Divide-by-zero exception raising via branch coverage
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Software testing with evolutionary strategies
RISE'05 Proceedings of the Second international conference on Rapid Integration of Software Engineering Techniques
Test data regeneration: generating new test data from existing test data
Software Testing, Verification & Reliability
Survey: A survey on search-based software design
Computer Science Review
Evolutionary algorithm for prioritized pairwise test data generation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
AUSTIN: An open source tool for search based software testing of C programs
Information and Software Technology
Evolutionary algorithms for the multi-objective test data generation problem
Software—Practice & Experience
Boosting search based testing by using constraint based testing
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
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
Diversity oriented test data generation using metaheuristic search techniques
Information Sciences: an International Journal
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For numerical programs, or more generally for programs with floating-point data, it may be that large savings of time and storage are made possible by using numerical maximization methods instead of symbolic execution to generate test data. Two examples, a matrix factorization subroutine and a sorting method, illustrate the types of data generation problems that can be successfully treated with such maximization techniques.