Comprehensive Evaluation of Software Quality Based on LM-BP Neural Network
2017 International Conference on Dependable Systems and Their Applications (DSA)（2017）
Abstract
In view of the shortcomings of traditional software quality evaluation methods, such as subjective and lack of self-learning ability, a comprehensive evaluation method of software quality based on Levenberg Marquardt Back Propagation (LM-BP) neural network is proposed. Comprehensive evaluation system of software quality is established based on ISO/IEC 9126 software quality model, and LM-BP algorithm is used to solve the problem of standard BP algorithm, such as slow convergence rate. A comprehensive evaluation model of software quality based on LM-BP neural network is established, which provides a new method and idea for comprehensive evaluation of software quality. The experimental results show that the comprehensive evaluation of software quality based on LM-BP neural network can obtain the comprehensive evaluation result of software quality quickly and accurately, and has good objectivity and practicability.
MoreTranslated text
Key words
software quality,comprehensive evaluation,artificial neural network,Levenberg Marquardt Back Propagation algorithm
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined