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GECCO
2004
Springer
259views Optimization» more  GECCO 2004»
13 years 10 months ago
Evaluation of Different Fitness Functions for the Evolutionary Testing of an Autonomous Parking System
The method of evolutionary functional testing allows for the automation of testing by transforming test case design into an optimization problem. To this end it is necessary to def...
Joachim Wegener, Oliver Bühler
GECCO
2008
Springer
129views Optimization» more  GECCO 2008»
13 years 5 months ago
Fitness calculation approach for the switch-case construct in evolutionary testing
A well-designed fitness function is essential to the effectiveness and efficiency of evolutionary testing. Fitness function design has been researched extensively. For fitness ...
Yan Wang, Zhiwen Bai, Miao Zhang, Wen Du, Ying Qin...
EH
2002
IEEE
112views Hardware» more  EH 2002»
13 years 9 months ago
Evolving Circuits in Seconds: Experiments with a Stand-Alone Board-Level Evolvable System
The purpose of this paper is twofold: first, to illustrate a stand-alone board-level evolvable system (SABLES) and its performance, and second to illustrate some problems that occ...
Adrian Stoica, Ricardo Salem Zebulum, Michael I. F...
GECCO
2003
Springer
148views Optimization» more  GECCO 2003»
13 years 10 months ago
Structural and Functional Sequence Test of Dynamic and State-Based Software with Evolutionary Algorithms
Evolutionary Testing (ET) has been shown to be very successful for testing real world applications [10]. The original ET approach focusesonsearching for a high coverage of the test...
André Baresel, Hartmut Pohlheim, Sadegh Sad...
CEC
2003
IEEE
13 years 10 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
Neural networks and the Kriging method are compared for constructing £tness approximation models in evolutionary optimization algorithms. The two models are applied in an identica...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...