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Differential evolution (DE) is a simple and efficient evolutionary algorithm for global optimization. In distributed differential evolution (DDE), the population is divided into several sub-populations and each sub-population evolves independently for enhancing population diversity as well as algorithmic performance. Sub-populations in DDE share their elite individuals with neighborhood through a...
Based on the analysis of inertia weight of the standard PSO, a PSO method is described with self-adaptive stochastic inertia weight based on diversity of individual location and fitness value. Position and fitness value correspond to the axis, based on the difference of location and fitness value from the generation and the current generation to construct a right triangle. It is to modify the inertia...
A major issue in software testing is the automatic generation of the inputs to be applied to the programme under test. To solve this problem, a number of approaches based on search methods have been developed in the last few years, offering promising results for adequacy criteria like, for instance, branch coverage. We devise branch coverage as the satisfaction of a number of constraints. This allows...
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