Reducing the effects of infeasible paths in branch testing
TAV3 Proceedings of the ACM SIGSOFT '89 third symposium on Software testing, analysis, and verification
Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
Analyzing Partition Testing Strategies
IEEE Transactions on Software Engineering
Constraint-Based Automatic Test Data Generation
IEEE Transactions on Software Engineering
Experimental results from an automatic test case generator
ACM Transactions on Software Engineering and Methodology (TOSEM)
Software unit test coverage and adequacy
ACM Computing Surveys (CSUR)
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Automatic test data generation using constraint solving techniques
Proceedings of the 1998 ACM SIGSOFT international symposium on Software testing and analysis
Art of Software Testing
Proportional sampling strategy: a compendium and some insights
Journal of Systems and Software
Program Flow Analysis: Theory and Application
Program Flow Analysis: Theory and Application
An Open-Ended Finite Domain Constraint Solver
PLILP '97 Proceedings of the9th International Symposium on Programming Languages: Implementations, Logics, and Programs: Including a Special Trach on Declarative Programming Languages in Education
New Quality Estimations in Random Testing
ISSRE '03 Proceedings of the 14th International Symposium on Software Reliability Engineering
Symbolic execution of floating-point computations: Research Articles
Software Testing, Verification & Reliability
Directed random reduction of combinatorial test suites
Proceedings of the 2nd international workshop on Random testing: co-located with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007)
A uniform random test data generator for path testing
Journal of Systems and Software
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Test campaigns usually require only a restricted subset of paths in a program to be thoroughly tested. As random testing (RT) offers interesting fault-detection capacities at low cost, we face the problem of building a sequence of random test data that execute only a subset of paths in a program. We address this problem with an original technique based on backward symbolic execution and constraint propagation to generate random test data based on an uniform distribution. Our approach derives path conditions and computes an over-approximation of their associated subdomain to find such a uniform sequence. The challenging problem consists in building efficiently a path-oriented random test data generator by minimizing the number of rejects within the generated random sequence. Our first experimental results, conducted over a few academic examples, clearly show a dramatic improvement of our approach over classical random testing.