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A Software Reliability Combination Model Based on Genetic Optimization BP Neural Network

  • Runan Wang
  • Fusheng Jin
  • Li Yang
  • Xiangyu Han
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 849)

Abstract

The software reliability model is the basis for the quantitative analysis and prediction of software reliability. In recent years, neural networks due to its generalization and learning ability have been widely applied in the field of software reliability modeling. However, the slow convergence and local minimum of neural networks may cause unsuccessful prediction. Therefore, this paper presents a software reliability combination model based on genetic optimization BP neural network. This model uses three classical software reliability models as the input of BP neural network, and then uses the genetic algorithm optimization to automatically configure and optimize the weight and the thresholds. The results of experiments show that the model proposed has better fitting effect and prediction ability than other similar models.

Keywords

Software reliability model Combination model BP neural network Genetic algorithm 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of SoftwareBeijing Institute of TechnologyBeijingChina
  2. 2.Beijing Aerospace Automatic Control InstituteBeijingChina

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