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Dynamic Radius Species Conserving Genetic Algorithm for Test Generation for Structural Testing
2017
International Journal of Software Engineering & Applications
Software testing is a critical and labor-intensive activity in software engineering. Much research has been done to help automate test case generation. This research proposes a new approach to structural test case generation. It uses a specialized genetic algorithm called Dynamic-radius Species-conserving Genetic Algorithm (DSGA) to find a structurally complete set of test cases for the Triangle Classification algorithm. DSGA is a Niche Genetic Algorithm (NGA) that uses a short-term memory
doi:10.5121/ijsea.2017.8208
fatcat:b2vnabspjnbyxpb54rhpmoq2oe