Empirically guided software development using metric-based classification trees

The identification of high-risk components early in the life cycle is addressed. A solution that casts this as a classification problem is examined. The proposed approach derives models of problematic components, based on their measurable attributes and those of their development processes. The mode...

Full description

Saved in:
Bibliographic Details
Published in:IEEE software 1990-03, Vol.7 (2), p.46-54
Main Authors: Porter, A.A., Selby, R.W.
Format: Article
Language:English
Subjects:
Algorithms
Automation
Calibration
Classification
Classification tree analysis
Costs
Feedback
Methods
Predictive models
Programming
Software
Software development
Trees
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The identification of high-risk components early in the life cycle is addressed. A solution that casts this as a classification problem is examined. The proposed approach derives models of problematic components, based on their measurable attributes and those of their development processes. The models provide a basis for forecasting which components are likely to share the same high-risk properties, such as being error-prone or having a high development cost. Developers can use these classification techniques to localize the troublesome 20% of the system. The method for generating the models, called automatic generation of metric-based classification trees, uses metrics from previous releases or projects to identify components that are historically high-risk.< >
ISSN:0740-7459
1937-4194
DOI:10.1109/52.50773