Dynamic Radius Species Conserving Genetic Algorithm for Test Generation for Structural Testing

Michael Scott Brown, Michael J. Pelosi
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
more » ... ture to store optima. Each individual of the NGA represents the inputs for a test case. The fitness function encourages the algorithm to locate test cases that cover large areas of the structure of the program. A shared fitness encourages the NGA to locate other areas of the structure. DSGA is a novel approach to structurally complete test case generation.
doi:10.5121/ijsea.2017.8208 fatcat:b2vnabspjnbyxpb54rhpmoq2oe