A Simple Predictive Method for Discriminating Costly Classes Using Class Size Metric

Hirohisa AMAN  Naomi MOCHIDUKI  Hiroyuki YAMADA  Matu-Tarow NODA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E88-D   No.6   pp.1284-1288
Publication Date: 2005/06/01
Online ISSN: 
DOI: 10.1093/ietisy/e88-d.6.1284
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Software Engineering
Keyword: 
object oriented software,  modification effort,  prediction,  class size,  metrics,  

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Summary: 
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.