Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (5): 31-37.doi: 10.11896/jsjkx.220900283

• Explainable AI • Previous Articles     Next Articles

Study on Reliability Prediction Model Based on BASFPA-BP

LI Honghui1,2, CHEN Bo1, LU Shuyi1, ZHANG Junwen1   

  1. 1 School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China
    2 China Engineering Research Center of Network Management Technology for High Speed Railway of MOE,Beijing 100044,China
  • Received:2022-09-30 Revised:2023-02-19 Online:2023-05-15 Published:2023-05-06
  • About author:LI Honghui,born in 1964,master,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include software testing technology,big data analysis and mining.
    CHEN Bo,born in 1998,master,is a member of China Computer Federation.Her main research interests include software test verification and analysis techniques.
  • Supported by:
    National Key Research and Development Program of China(2019YFB2102500).

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Abstract: Software reliability prediction is based on software reliability prediction model,which analyzes,evaluates and predicts software reliability and reliability-related measures.Using the failure data collected in software operation to predict the future software reliability.It has become an important means to evaluate software failure behavior and guarantee software reliability.BP neural network has been widely used in software reliability prediction because of its simple structure and few parameters.How-ever,the prediction accuracy of the software reliability prediction model built based on the traditional BP neural network cannot reach the expected target.Therefore,this paper proposes a software reliability prediction model based on BASFPA-BP.This model utilizes software failure data and utilizes BASFPA algorithm to optimize network weights and thresholds in the training process of BP neural network.Thus,the prediction accuracy of the model is improved.In this paper,three groups of public software failure data are selected,and the mean square error between the actual value and the predicted value is taken as the measurement standard of the predicted results.Meanwhile,BASFPA-BP is compared with FPA-BP,BP and Elman models.Experimental results show that the software reliability prediction model based on BASFPA-BP achieves high prediction accuracy in the same type of model.

Key words: Software reliability prediction model, Beetle antennae search algorithm, Flower pollination algorithm, BASFPA

CLC Number: 

  • TP311
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