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» OptiTest: Optimizing Test Case Using Hybrid Intelligence
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CEC
2007
IEEE
14 years 1 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
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
PROMISE
2010
13 years 2 months ago
Case-based reasoning vs parametric models for software quality optimization
Background: There are many data mining methods but few comparisons between them. For example, there are at least two ways to build quality optimizers, programs that find project o...
Adam Brady, Tim Menzies
GECCO
2010
Springer
172views Optimization» more  GECCO 2010»
14 years 5 days ago
Designing better fitness functions for automated program repair
Evolutionary methods have been used to repair programs automatically, with promising results. However, the fitness function used to achieve these results was based on a few simpl...
Ethan Fast, Claire Le Goues, Stephanie Forrest, We...
EVOW
2009
Springer
14 years 2 months ago
Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm
We apply evolutionary computation to calibrate the parameters of a morphogenesis model of Drosophila early development. The model aims to describe the establishment of the steady g...
Rui Dilão, Daniele Muraro, Miguel Nicolau, ...