Empirically guided software development using metric-based classification trees
- 1 March 1990
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Software
- Vol. 7 (2) , 46-54
- https://doi.org/10.1109/52.50773
Abstract
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.Keywords
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