Maintainability prediction: a regression analysis of measures of evolving systems

In order to build predictors of the maintainability of evolving software, we first need a means for measuring maintainability as well as a training set of software modules for which the actual maintainability is known. This paper describes our success at building such a predictor. Numerous candidate...

Full description

Saved in:
Bibliographic Details
Main Authors: Hayes, J.H., Zhao, L.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Computer science
Error correction
Lab-on-a-chip
Performance analysis
Predictive models
Regression analysis
Software maintenance
Software measurement
Software systems
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to build predictors of the maintainability of evolving software, we first need a means for measuring maintainability as well as a training set of software modules for which the actual maintainability is known. This paper describes our success at building such a predictor. Numerous candidate measures for maintainability were examined, including a new compound measure. Two datasets were evaluated and used to build a maintainability predictor. The resulting model, Maintainability Prediction Model (MainPredMo), was validated against three held-out datasets. We found that the model possesses predictive accuracy of 83% (accurately predicts the maintainability of 83% of the modules). A variant of MainPredMo, also with accuracy of 83%, is offered for interested researchers.
ISSN:1063-6773
2576-3148
DOI:10.1109/ICSM.2005.59