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http://dx.doi.org/10.5392/JKCA.2010.10.6.134

Taxonomy Framework for Metric-based Software Quality Prediction Models  

Hong, Euy-Seok (성신여자대학교 IT학부)
Publication Information
The Journal of the Korea Contents Association / v.10, no.6, 2010 , pp. 134-143 More about this Journal
Abstract
This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.
Keywords
Software quality; Prediction model; Taxonomy framework;
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Times Cited By KSCI : 1  (Citation Analysis)
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