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Application of genetic algorithm in automatic software testing

Babamir, F. S ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-642-14306-9_54
  3. Abstract:
  4. One of the major challenge and time-consuming work is optimum test data generation to assure software quality. Researchers have proposed several methods over years to generate automatically solution which have different drawbacks. In this paper, we propose Genetic Algorithm (GA) based tester with different parameters to automate the structural-oriented test data generation on the basis of internal program structure. Our proposed fitness function is intended to traverse paths of the program as more as possible. This integration improves the GA performance in search space exploration and exploitation fields with faster convergence. At last, we present some results according to our experiment which were promising in term of structural coverage and time order
  5. Keywords:
  6. Genetic algorithm ; Path coverage ; Faster convergence ; Fitness functions ; Program structures ; Search spaces ; Structural testing ; Test data generation ; Data communication systems ; Function evaluation ; Genetic algorithms ; Software testing ; Space research ; Test facilities ; Computer software selection and evaluation
  7. Source: Communications in Computer and Information Science, 7 July 2010 through 9 July 2010 ; Volume 88 CCIS, Issue PART 2 , 2010 , Pages 545-552 ; 18650929 (ISSN) ; 9783642143052 (ISBN)
  8. URL: http://link.springer.com/chapter/10.1007/978-3-642-14306-9_54