Journal of Computational Physics
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Applying design of experiments to software testing: experience report
ICSE '97 Proceedings of the 19th international conference on Software engineering
The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Model-based testing in practice
Proceedings of the 21st international conference on Software engineering
A Test Generation Strategy for Pairwise Testing
IEEE Transactions on Software Engineering
Determination of Test Configurations for Pair-Wise Interaction Coverage
TestCom '00 Proceedings of the IFIP TC6/WG6.1 13th International Conference on Testing Communicating Systems: Tools and Techniques
Constructing test suites for interaction testing
Proceedings of the 25th International Conference on Software Engineering
An Investigation of the Applicability of Design of Experiments to Software Testing
SEW '02 Proceedings of the 27th Annual NASA Goddard Software Engineering Workshop (SEW-27'02)
Generating Small Combinatorial Test Suites to Cover Input-Output Relationships
QSIC '03 Proceedings of the Third International Conference on Quality Software
Upper bounds for covering arrays by tabu search
Discrete Applied Mathematics - Optimal discrete structure and algorithms (ODSA 2000)
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
Using Artificial Life Techniques to Generate Test Cases for Combinatorial Testing
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
A framework of greedy methods for constructing interaction test suites
Proceedings of the 27th international conference on Software engineering
Covering Arrays for Efficient Fault Characterization in Complex Configuration Spaces
IEEE Transactions on Software Engineering
Algorithms for covering arrays
Algorithms for covering arrays
The density algorithm for pairwise interaction testing: Research Articles
Software Testing, Verification & Reliability
A systematic review of search-based testing for non-functional system properties
Information and Software Technology
A survey of combinatorial testing
ACM Computing Surveys (CSUR)
MiTS: a new approach of tabu search for constructing mixed covering arrays
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Covering arrays generation methods survey
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part II
Construction of mixed covering arrays of variable strength using a tabu search approach
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part I
Evaluating improvements to a meta-heuristic search for constrained interaction testing
Empirical Software Engineering
A survey of methods for constructing covering arrays
Programming and Computing Software
A variable strength interaction test suites generation strategy using Particle Swarm Optimization
Journal of Systems and Software
Information and Software Technology
Evolutionary algorithm for prioritized pairwise test data generation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Mixed optimization combinatorial method for constructing covering arrays
Programming and Computing Software
| Hi-index | 0.00 |
Algorithms for the construction of software interaction test suites have focussed on the special case of pairwise coverage; less is known about efficiently constructing test suites for higher strength coverage. The combinatorial growth of t-tuples associated with higher strength hinders the efficacy of interaction testing. Test suites are inherently large, so testers may not run entire test suites. To address these problems, we combine a simple greedy algorithmallwith heuristic search to construct and dispense one test at a time. Our algorithm attempts to maximize the number of t-tuples covered by the earliest tests so that if a tester only runs a partial test suite, they test as many t-tuples as possible.allHeuristic search is shown to provide effective methods for achieving such coverage.