|Table of Contents|

Path Test Data Generation Based on Chaos Anneal Particle Swarm Optimization Algorithm

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2011年03期
Page:
376-381
Research Field:
Publishing date:

Info

Title:
Path Test Data Generation Based on Chaos Anneal Particle Swarm Optimization Algorithm
Author(s):
CHEN Ce12ZHAO Chun-xia1
1.School of Computer Science and Technology,NUST,Nanjing 210094,China;2.Unit 63961 of PLA,Beijing 100012,China
Keywords:
particle swarm optimization simulated annealing chaos search prematurity convergence judgment software tests path tests
PACS:
TP311.53
DOI:
-
Abstract:
A kind of evolutionary test method based on the particle swarm optimization(PSO)algorithm is proposed for the automatic generation of appointed path software test data.Path adaptive value for optimization searching is calculated using code insertion of branch functions and control execution strategy of program path.The shortcoming that the standard PSO algorithm is easy to fall into local optima and can ’ t find the test data is overcome by introducing chaos search,simulated annealing and prematurity convergence judgment mechanism.The experiments of the automatic generation of test data on a triangle judgment program show:when the biggest iterative time Tmax is 500,the hit probability of chaos anneal particle swarm optimization(CAPSO)algorithm and standard PSO algorithm is 99% and 95%;when Tmax is 2000,the hit probability of CAPSO algorithm and standard PSO algorithm is 100% and 95%;the increase of Tmax can ’ t improve the hit probability of the standard PSO algorithm,but the CAPSO algorithm can shake off the local extremum and find the test data satisfying the request.

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Last Update: 2012-06-30