Computer Science ›› 2019, Vol. 46 ›› Issue (2): 159-165.doi: 10.11896/j.issn.1002-137X.2019.02.025

• Software & Database Technology • Previous Articles     Next Articles

Approach for Generating Class Integration Test Sequence Based on Dream Particle Swarm Optimization Algorithm

ZHANG Yue-ning1, JIANG Shu-juan1, ZHANG Yan-mei1,2   

  1. Mine Digitization Engineering Research Center of the Ministry of Education,School of Computer Science and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China1
    Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China2
  • Received:2018-08-11 Online:2019-02-25 Published:2019-02-25

Abstract: Determination of class integration test sequence is an important topic in object-oriented software integration testing.Reasonable class integration test sequence can reduce the overall complexity of test stub,and then reduce test cost.For particle swarm optimization algorithm,it is easy to be precocious.So a class integration test sequence determination method based on dream particle swarm optimization algorithm was proposed in this paper.First,each sequence is taken as a particle in one dimensional space.Then,every particle is considered to be a dreamer.Each iteration cycle is divided into two phases:day and night.In the daytime,particles move to new locations,and during the night,they contort the locations gained at day phase according to dreaming ability.In this way,particle has the opportunity to search near the current location,so that the algorithm can converge slowly and avoid falling into local optimum too early.The experimental results show that the proposed approach takes a lower test cost in most cases.

Key words: Dream particle swarm optimization algorithm, Integration testing, Local optimum, Test cost, Test sequence

CLC Number: 

  • TP311
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