Association Metrics between Two Continuous Variables for Software Project Data

Takumi Kanehira; Akito Monden; Zeynep Yucel

doi:10.1109/SNPD51163.2021.9704983

Association Metrics between Two Continuous Variables for Software Project Data

Takumi Kanehira, Akito Monden, Zeynep Yucel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The correlation coefficient is commonly used in analyses of software project data sets for the purpose of quantifying the relationship between two variables. However, while there are various types of relationships between two variables, the correlation coefficient cannot distinguish between these types. This study proposes new metrics between two continuous variables that have the potential to characterize the relationship types.

Original language	English
Title of host publication	Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall
Editors	Her-Terng Yau, Roland Stenzel, Mei-Ling Shyu, Hsiung-Cheng Lin
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	242-247
Number of pages	6
ISBN (Electronic)	9781665404037
DOIs	https://doi.org/10.1109/SNPD51163.2021.9704983
Publication status	Published - 2021
Event	22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall - Virtual, Taichung, Taiwan, Province of China Duration: Nov 24 2021 → Nov 26 2021

Publication series

Name	Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall

Conference

Conference	22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall
Country/Territory	Taiwan, Province of China
City	Virtual, Taichung
Period	11/24/21 → 11/26/21

Keywords

correlation coefficient
soft-ware project data analysis
Software metrics

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Vision and Pattern Recognition
Hardware and Architecture
Software
Information Systems and Management

Access to Document

10.1109/SNPD51163.2021.9704983

Cite this

Kanehira, T., Monden, A., & Yucel, Z. (2021). Association Metrics between Two Continuous Variables for Software Project Data. In H-T. Yau, R. Stenzel, M-L. Shyu, & H-C. Lin (Eds.), Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall (pp. 242-247). (Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SNPD51163.2021.9704983

Association Metrics between Two Continuous Variables for Software Project Data. / Kanehira, Takumi; Monden, Akito ; Yucel, Zeynep.

Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall. ed. / Her-Terng Yau; Roland Stenzel; Mei-Ling Shyu; Hsiung-Cheng Lin. Institute of Electrical and Electronics Engineers Inc., 2021. p. 242-247 (Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kanehira, T, Monden, A & Yucel, Z 2021, Association Metrics between Two Continuous Variables for Software Project Data. in H-T Yau, R Stenzel, M-L Shyu & H-C Lin (eds), Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall. Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall, Institute of Electrical and Electronics Engineers Inc., pp. 242-247, 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall, Virtual, Taichung, Taiwan, Province of China, 11/24/21. https://doi.org/10.1109/SNPD51163.2021.9704983

Kanehira T, Monden A , Yucel Z. Association Metrics between Two Continuous Variables for Software Project Data. In Yau H-T, Stenzel R, Shyu M-L, Lin H-C, editors, Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall. Institute of Electrical and Electronics Engineers Inc. 2021. p. 242-247. (Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall). doi: 10.1109/SNPD51163.2021.9704983

Kanehira, Takumi ; Monden, Akito ; Yucel, Zeynep. / Association Metrics between Two Continuous Variables for Software Project Data. Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall. editor / Her-Terng Yau ; Roland Stenzel ; Mei-Ling Shyu ; Hsiung-Cheng Lin. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 242-247 (Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall).

@inproceedings{f2724f225ccc46ceaf74a7b63bbf31e4,

title = "Association Metrics between Two Continuous Variables for Software Project Data",

abstract = "The correlation coefficient is commonly used in analyses of software project data sets for the purpose of quantifying the relationship between two variables. However, while there are various types of relationships between two variables, the correlation coefficient cannot distinguish between these types. This study proposes new metrics between two continuous variables that have the potential to characterize the relationship types. ",

keywords = "correlation coefficient, soft-ware project data analysis, Software metrics",

author = "Takumi Kanehira and Akito Monden and Zeynep Yucel",

note = "Funding Information: Part of this research was supported by JSPS KAKENHI Grant number 20K11749. Publisher Copyright: {\textcopyright} 2021 IEEE.; 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall ; Conference date: 24-11-2021 Through 26-11-2021",

year = "2021",

doi = "10.1109/SNPD51163.2021.9704983",

language = "English",

series = "Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "242--247",

editor = "Her-Terng Yau and Roland Stenzel and Mei-Ling Shyu and Hsiung-Cheng Lin",

booktitle = "Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall",

}

TY - GEN

T1 - Association Metrics between Two Continuous Variables for Software Project Data

AU - Kanehira, Takumi

AU - Monden, Akito

AU - Yucel, Zeynep

PY - 2021

Y1 - 2021

N2 - The correlation coefficient is commonly used in analyses of software project data sets for the purpose of quantifying the relationship between two variables. However, while there are various types of relationships between two variables, the correlation coefficient cannot distinguish between these types. This study proposes new metrics between two continuous variables that have the potential to characterize the relationship types.

AB - The correlation coefficient is commonly used in analyses of software project data sets for the purpose of quantifying the relationship between two variables. However, while there are various types of relationships between two variables, the correlation coefficient cannot distinguish between these types. This study proposes new metrics between two continuous variables that have the potential to characterize the relationship types.

KW - correlation coefficient

KW - soft-ware project data analysis

KW - Software metrics

UR - http://www.scopus.com/inward/record.url?scp=85125699958&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85125699958&partnerID=8YFLogxK

U2 - 10.1109/SNPD51163.2021.9704983

DO - 10.1109/SNPD51163.2021.9704983

M3 - Conference contribution

AN - SCOPUS:85125699958

T3 - Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall

SP - 242

EP - 247

BT - Proceedings - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall

A2 - Yau, Her-Terng

A2 - Stenzel, Roland

A2 - Shyu, Mei-Ling

A2 - Lin, Hsiung-Cheng

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2021-Fall

Y2 - 24 November 2021 through 26 November 2021

ER -

Association Metrics between Two Continuous Variables for Software Project Data

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this