@article {16330,
	title = {Empirically guided software development using metric-based classification trees},
	journal = {IEEE Software},
	volume = {7},
	year = {1990},
	month = {1990/03//},
	pages = {46 - 54},
	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 = {Application software, Area measurement, automatic generation, classification problem, Classification tree analysis, Costs, empirically guided software development, Error correction, life cycle, measurable attributes, metric-based classification trees, Predictive models, Programming, software engineering, Software measurement, software metrics, Software systems},
	isbn = {0740-7459},
	doi = {10.1109/52.50773},
	author = {Porter, Adam and Selby,R. W}
}
