Description: Evolutionary optimization algorithms often used to generate structured test cases. When generating test cases, existing methods generally focus on a target and generate a test case to cover the target. In order to cover all targets, the optimization process must be executed many times. A new method for test case generation is implemented based on set evolution. In the implemented algorithm, a chromosome represents many cases, thus generating a set of test cases which satisfy the testing requirements in a running.
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File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| set | 0 | 2016-01-31
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| set\chromosome | 0 | 2016-01-31
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| set\chromosome\Chromosome.java | 1380 | 2013-11-18
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| set\crossover | 0 | 2016-01-31
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| set\crossover\InnerSetCross.java | 2032 | 2015-06-01
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| set\crossover\InterSetCross.java | 1193 | 2015-06-01
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| set\crossover\SimpleCross.java | 1993 | 2013-10-15
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| set\gene | 0 | 2016-01-31
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| set\gene\Gene.java | 1323 | 2013-11-18
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| set\mutation | 0 | 2016-01-31
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| set\mutation\Mutation.java | 661 | 2015-06-01
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| set\mutation\NewGene.java | 174 | 2016-01-31
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| set\mutation\SimpleMutation.java | 739 | 2013-09-12
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| set\population | 0 | 2016-01-31
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| set\population\Population.java | 3496 | 2015-06-01
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| set\selection | 0 | 2016-01-31
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| set\selection\Selection.java | 778 | 2015-06-01 |
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