A tractable Walsh analysis of SAT and its implications for genetic algorithms
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
SIAM Review
Empirical Software Engineering
Pareto efficient multi-objective test case selection
Proceedings of the 2007 international symposium on Software testing and analysis
Understanding elementary landscapes
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A polynomial time computation of the exact correlation structure of k-satisfiability landscapes
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Applying Elementary Landscape Analysis to Search-Based Software Engineering
SSBSE '10 Proceedings of the 2nd International Symposium on Search Based Software Engineering
Elementary bit string mutation landscapes
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
A methodology to find the elementary landscape decomposition of combinatorial optimization problems
Evolutionary Computation
Regression testing minimization, selection and prioritization: a survey
Software Testing, Verification & Reliability
Dynamic adaptive search based software engineering
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Testing of concurrent programs using genetic algorithms
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
Hi-index | 0.00 |
Landscape theory provides a formal framework in which combinatorial optimization problems can be theoretically characterized as a sum of a special kind of landscape called elementary landscape. The decomposition of the objective function of a problem into its elementary components provides additional knowledge on the problem that can be exploited to create new search methods for the problem. We analyze the Test Suite Minimization problem in Regression Testing from the point of view of landscape theory. We find the elementary landscape decomposition of the problem and propose a practical application of such decomposition for the search.