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A Simple Predictive Method for Discriminating Costly Classes Using Class Size Metric
Hirohisa AMAN Naomi MOCHIDUKI Hiroyuki YAMADA Matu-Tarow NODA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2005/06/01
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Software Engineering
object oriented software, modification effort, prediction, class size, metrics,
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Larger object classes often become more costly classes in the maintenance phase of object-oriented software. Consequently class would have to be constructed in a medium or small size. In order to discuss such desirable size, this paper proposes a simple method for predictively discriminating costly classes in version-upgrades, using a class size metric, Stmts. Concretely, a threshold value of class size (in Stmts) is provided through empirical studies using many Java classes. The threshold value succeeded as a predictive discriminator for about 73% of the sample Java classes.