Journal of Robotics, Networking and Artificial Life

Volume 7, Issue 4, March 2021, Pages 270 - 274

Utilizing the Similarity Meaning of Label in Class Cohesion Calculation

Authors
Bayu Priyambadha1, *, Tetsuro Katayama1, Yoshihiro Kita2, Hisaaki Yamaba1, Kentaro Aburada1, Nanoubu Okazaki1
1Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, 1-1 Gakuen-Kibanadai nishi, Miyazaki 889-2192, Japan
2Department of Information Security, Faculty of Information Systems, Siebold Campus, University of Nagasaki, 1-1-1 Manabino, Nagayo-cho, Nishi-Sonogi-gun, Nagasaki 851-2195, Japan
*Corresponding author. Email: bayu@earth.cs.miyazaki-u.ac.jp
Corresponding Author
Bayu Priyambadha
Received 10 November 2019, Accepted 13 November 2020, Available Online 31 December 2020.
DOI
https://doi.org/10.2991/jrnal.k.201215.013How to use a DOI?
Keywords
Software engineering, software quality, design quality, cohesion metric, D3C2 metric
Abstract

The cohesion is one of the design quality indicators in software engineering. The measurement of the value of cohesion is done by looking at the correlation between attributes and methods that are in a class. In Direct Distance Design Class Cohesion (D3C2) metrics, attributes, and methods are assumed to have a good correlation if they have a similar type. But, the similarity of type parameters and attributes do not always indicate that these attributes are managed (correlated) in the method. This study is trying to gain information that can enhance the degree of certainty of a correlation between the methods and attributes. Relatedness between them has been seen from closeness the meaning of the name tag attribute, method, and parameters. The experimental results declared an increase in the value of cohesion produced in line with the similarity of meaning.

Copyright
© 2020 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
7 - 4
Pages
270 - 274
Publication Date
2020/12
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.k.201215.013How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Bayu Priyambadha
AU  - Tetsuro Katayama
AU  - Yoshihiro Kita
AU  - Hisaaki Yamaba
AU  - Kentaro Aburada
AU  - Nanoubu Okazaki
PY  - 2020
DA  - 2020/12
TI  - Utilizing the Similarity Meaning of Label in Class Cohesion Calculation
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 270
EP  - 274
VL  - 7
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.201215.013
DO  - https://doi.org/10.2991/jrnal.k.201215.013
ID  - Priyambadha2020
ER  -