DocumentCode :
2355482
Title :
A methodology for evaluating predictive metrics
Author :
Rosenberg, Jarrett
Author_Institution :
Sun Microsystems, Palo Alto, CA, USA
fYear :
1998
fDate :
20-21 Nov 1998
Firstpage :
181
Abstract :
For over thirty years, software engineers have been interested in the ability to accurately measure characteristics of software and its production which could lead to improvements in both. In that time, a large number of metrics have been proposed, some with attempts at empirical validation of their effectiveness. Unfortunately, many if not most of these laudable efforts at empirical validation have foundered on a lack of knowledge about the appropriate methods to use. For example, a central goal in software metrics is the prediction of software characteristics based on other metrics of the software or its production process. This prediction problem is a quintessentially statistical one, but the lack of statistical training in the typical crowded engineering curriculum leaves most engineers uncertain about how to proceed. The result has been many well-intentioned but poorly executed empirical studies. This paper addresses this problem by providing a simple methodology for the predictive evaluation of metrics
Keywords :
software metrics; statistical analysis; empirical validation; predictive metrics evaluation methodology; software engineers; software metrics; statistics; Data analysis; Information analysis; Logistics; Production; Signal detection; Software measurement; Software metrics; Statistics; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Metrics Symposium, 1998. Metrics 1998. Proceedings. Fifth International
Conference_Location :
Bethesda, MD
Print_ISBN :
0-8186-9201-4
Type :
conf
DOI :
10.1109/METRIC.1998.731244
Filename :
731244
Link To Document :
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