Title :
A comparative study of Genetic Algorithms for its applications in Object oriented testing
Author :
Vats, Prashant ; Mandot, Manju ; Gosain, Anjana
Author_Institution :
AIMACT, Banasthali Univ., Banasthali, India
Abstract :
Genetic Algorithms are heuristic approach for forming the bases of search based algorithms. It applies the mechanism of the natural selection of genes & the phenomena´s associated with the genetics like mutation, crossover, and replication to provide solutions in some complex searches. In this paper, we have reviewed their applications in context of the Object oriented paradigm thus proving their usefulness in providing solutions to the various issues related to their testing.
Keywords :
genetic algorithms; object-oriented methods; program testing; crossover; evolutionary algorithm; fitness function; genetic algorithms; mutation; natural gene selection; object oriented testing; replication; search based algorithms; Encoding; Evolutionary computation; Genetic algorithms; Genetics; Java; Testing; Unified modeling language; Evolutionary algorithm; Fitness function; Genetic algorithms; Heuristic; Mutation; Object oriented;
Conference_Titel :
Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on
Conference_Location :
Ghaziabad
DOI :
10.1109/ICICICT.2014.6781342
