Automatic Test Data Generation Based on SAMPSO Algorithm

This paper proposes an automatic test data generation method based on Simple and Adaptive Mutation Particle Swarm Optimization algorithm. According to the particle velocity independency in the evolution, this algorithm removes particle velocity , only the position of particle control the process of...

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Published in:2009 International Conference on Computational Intelligence and Software Engineering pp. 1 - 4
Main Authors: Wei, Fu-qiang, Jiang, Shu-juan
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2009
Subjects:
Automatic control
Automatic testing
Computer science
Electronic mail
Genetic mutations
Iterative algorithms
Logic testing
Paper technology
Particle swarm optimization
Software testing
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Abstract This paper proposes an automatic test data generation method based on Simple and Adaptive Mutation Particle Swarm Optimization algorithm. According to the particle velocity independency in the evolution, this algorithm removes particle velocity , only the position of particle control the process of evolution, avoiding problems such as slow of convergence in the late evolutionary and low-precision radiation of particle that particle velocity brings about; according to fit variance and current optimum solution, we find the current mutation rate of best particle, the operation of mutation can improve ability of global searching in the earlier evolutionary. Test examples show that it is better than basic particle swarm optimization algorithm and can improve the efficiency of automated test data generation.
AbstractList This paper proposes an automatic test data generation method based on Simple and Adaptive Mutation Particle Swarm Optimization algorithm. According to the particle velocity independency in the evolution, this algorithm removes particle velocity , only the position of particle control the process of evolution, avoiding problems such as slow of convergence in the late evolutionary and low-precision radiation of particle that particle velocity brings about; according to fit variance and current optimum solution, we find the current mutation rate of best particle, the operation of mutation can improve ability of global searching in the earlier evolutionary. Test examples show that it is better than basic particle swarm optimization algorithm and can improve the efficiency of automated test data generation.
Author Wei, Fu-qiang
Jiang, Shu-juan
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  givenname: Shu-juan
  surname: Jiang
  fullname: Jiang, Shu-juan
  email: shjjiang@cumt.edu.cn
  organization: Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
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Snippet This paper proposes an automatic test data generation method based on Simple and Adaptive Mutation Particle Swarm Optimization algorithm. According to the...
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StartPage 1
SubjectTerms Automatic control
Automatic testing
Computer science
Electronic mail
Genetic mutations
Iterative algorithms
Logic testing
Paper technology
Particle swarm optimization
Software testing
Title Automatic Test Data Generation Based on SAMPSO Algorithm
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