Genetic algorithm based multi-agent system applied to test generation

  • Authors:

  • Anbo Meng;Luqing Ye;Daniel Roy;Pierre Padilla

  • Affiliations:

  • Faculty of Hydroelectric and Digital Engineering, Huazhong University of Science of Technology, 430074 Wuhan, China and Laboratoire de Génie Industriel et de Production Mécanique (LGIPM) ...;Faculty of Hydroelectric and Digital Engineering, Huazhong University of Science of Technology, 430074 Wuhan, China;Laboratoire de Génie Industriel et de Production Mécanique (LGIPM), ícole National d' Ingénieur de METZ 570045 Metz, France;Laboratoire de Génie Industriel et de Production Mécanique (LGIPM), ícole National d' Ingénieur de METZ 570045 Metz, France

  • Venue:
  • Computers & Education
  • Year:
  • 2007

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Abstract

Automatic test generating system in distributed computing context is one of the most important links in on-line evaluation system. Although the issue has been argued long since, there is not a perfect solution to it so far. This paper proposed an innovative approach to successfully addressing such issue by the seamless integration of genetic algorithm (GA) and multi-agent system. In the design phase, a test ontology was firstly defined for smoothing the communication among agents. For the implementation of GA, The fitness function and the structure of chromosome were identified on the basis of the analysis of constraint conditions associated with a test. To demonstrate the task execution flow and messages passing among agents, the activity diagram and sequence diagram were also shown on the AUML basis. In the phase of implementation, the JADE based agent behavior model was described in detail and the implementation platform was also demonstrated. The final simulation results validated the feasibility of the proposed approach.