A Way to Predict and Evaluate of Software Maintainability Based on Machine Learning

Abstract

The accurate maintainability prediction and evaluation of software applications can improve the designing management for these applications, thus benefiting designing organizations. Therefore, there is considerable research interest in development and application of sophisticated techniques which can be used to build models for both predicting and evaluating software maintainability. In this paper, we investigate some ideas based on Machine Learning, Natural Language Processing, Fuzzy Logic, and Systematic Model of Software Maintenance. The idea to compute Interactive Index and the maintainability of software system is useful to study the relation between maintainability prediction and maintainability evaluation in the whole software process. An model basing on fuzzy matrix and BP neural network is built up. It’s approved that there are application value of using this model based on BP neural network to predict and evaluate the software maintainability.