Jul 24, 2012 � The main goal of this paper is to introduce a complete methodology, supported by tools, that addresses this issue by representing the test data�...
The main goal of this paper is to introduce a complete methodology, supported by tools, that addresses this issue by representing the test data generation�...
We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search�...
This paper introduces a complete methodology, supported by tools, that addresses the test data generation problem as an optimization problem by using�...
The main goal of this paper is to introduce a complete methodology, supported by tools, that addresses this issue by representing the test data generation�...
A case study on the use of genetic algorithms to generate test cases for temporal systems⋆. Karnig Derderian1, Mercedes G. Merayo2,. Robert M. Hierons1�...
Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs show to outperform random search and seem to scale well�...
GAs show to outperform random search and seem to scale well as the problem size increases. We consider a very simple fitness function that can be used with�...
In this work, we describe a GA framework for sequential circuit test generation. The GA evolves candidate test vectors and sequences, using a fault simulator to�...
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This paper presents a method of generating optimized sequences of tests within a battery of tests using a genetic algorithm.