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» Breeding Software Test Cases with Genetic Algorithms
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GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 8 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
TSE
2011
144views more  TSE 2011»
13 years 2 months ago
Genetic Algorithms for Randomized Unit Testing
—Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing varies widely according to the settings of certain parameters, such...
James H. Andrews, Tim Menzies, Felix Chun Hang Li
IWANN
2009
Springer
14 years 2 months ago
Aiding Test Case Generation in Temporally Constrained State Based Systems Using Genetic Algorithms
Generating test data for formal state based specifications is computationally expensive. This paper improves a framework that addresses this issue by representing the test data ge...
Karnig Derderian, Mercedes G. Merayo, Robert M. Hi...
PPSN
1994
Springer
13 years 11 months ago
A Representation Scheme To Perform Program Induction in a Canonical Genetic Algorithm
This paper studies Genetic Programming (GP) and its relation to the Genetic Algorithm (GA). GP uses a GA approach to breed successive populations of programs, represented in the ch...
Mark Wineberg, Franz Oppacher
KBSE
2007
IEEE
14 years 1 months ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies