Towards a semantic metrics suite for object-oriented design

被引:25
作者
Etzkorn, L [1 ]
Delugach, H [1 ]
机构
[1] Univ Alabama, Dept Comp Sci, Huntsville, AL 35899 USA
来源
TECHNOLOGY OF OBJECT-ORIENTED LANGUAGES AND SYSTEMS - TOOLS 34, PROCEEDINGS | 2000年
关键词
object-oriented metrics; program understanding; natural language processing; knowledge-based systems; semantic networks; conceptual graphs;
D O I
10.1109/TOOLS.2000.868960
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years much work has been. performed in developing suites of metrics that are targeted for object-oriented software, rather than functionality-oriented software. This is necessary since good object-oriented software has several characteristics, such as inheritance and polymorphism, that are not usually present in functionally-oriented software. However, all of these object-oriented metrics suites have been defined using only syntactic aspects of object-oriented software; indeed, the earlier functionally-oriented metrics were also calculated using only syntactic information. All syntactically-oriented metrics have the problem that the mapping from the metric to the quality the metric purports to measure, such as the software quality factor "cohesion," is indirect, and often arguable. Thus, a substantial amount of research effort goes into proving that these syntactically-oriented metrics actually do measure their associated quality factors. This paper introduces a new suite of semantically-derived object-oriented metrics, which provide a more direct mapping from the metric to its associated quality factor than is possible using syntactic metrics. These semantically-derived metrics are calculated using knowledge-based, program understanding, and natural language processing techniques.
引用
收藏
页码:71 / 80
页数:10
相关论文
共 50 条
[21]   SAM: Simple API for object-oriented code metrics [J].
Edelman, Adam ;
Frakes, William ;
Lillie, Charles .
HIGH CONFIDENCE SOFTWARE REUSE IN LARGE SYSTEMS, PROCEEDINGS, 2008, 5030 :347-359
[22]   Metrics for quality analysis and improvement of object-oriented software [J].
Ebert, C ;
Morschel, I .
INFORMATION AND SOFTWARE TECHNOLOGY, 1997, 39 (07) :497-509
[23]   Mining the impact of evolution categories on object-oriented metrics [J].
Henrique Rocha ;
Cesar Couto ;
Cristiano Maffort ;
Rogel Garcia ;
Clarisse Simoes ;
Leonardo Passos ;
Marco Tulio Valente .
Software Quality Journal, 2013, 21 :529-549
[24]   A model-based approach to object-oriented software metrics [J].
Hong Mei ;
Tao Xie ;
Fuqing Yang .
Journal of Computer Science and Technology, 2002, 17 :757-769
[25]   Empirical Study on the Distribution of Object-Oriented Metrics in Software Systems [J].
Muthukumaran, K. ;
Murthy, N. L. Bhanu ;
Janani, P. Sarguna .
INFORMATION AND SOFTWARE TECHNOLOGIES, ICIST 2019, 2019, 1078 :299-317
[26]   An Outlier Detection Algorithm Based on Object-Oriented Metrics Thresholds [J].
Alan, Oral ;
Catal, Cagatay .
2009 24TH INTERNATIONAL SYMPOSIUM ON COMPUTER AND INFORMATION SCIENCES, 2009, :565-568
[27]   An extensible metrics extraction environment for object-oriented programming languages [J].
Harmer, TJ ;
Wilkie, FG .
SCAM 2002: SECOND IEEE INTERNATIONAL WORKSHOP ON SOURCE CODE ANALYSIS MANIPULATION, PROCEEDINGS, 2002, :26-35
[28]   The confounding effect of class size on the validity of object-oriented metrics [J].
Emam, KE ;
Benlarbi, S ;
Goel, N ;
Rai, SN .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2001, 27 (07) :630-650
[29]   The confounding effect of class size on the validity of object-oriented metrics [J].
Evanco, WM .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2003, 29 (07) :670-672
[30]   A model-based approach to object-oriented software metrics [J].
Mei, H ;
Xie, T ;
Yang, FQ .
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2002, 17 (06) :757-769