Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study

Mustafa Ghaleb; Mohamed Alasow; Azzah AlGhamdi; Mosab Hamdan; Sajjad Mahmood

doi:10.1007/978-3-031-95127-5_22

Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study

Mustafa Ghaleb^*
, Mohamed Alasow
, Azzah AlGhamdi
, Mosab Hamdan
, Sajjad Mahmood

^*Corresponding author for this work

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

Abstract

This study addresses the challenges introduced by the shift from procedural-oriented to object-oriented paradigms, focusing on the need to maintain consistent design while satisfying market demands, particularly in achieving software stability. While previous research has explored various factors affecting software stability, a gap remains in understanding the correlation between class stability and C&K and evolution-based metrics. To fill this gap, we conducted an empirical investigation using two open-source Java projects, Android and Eclipse, across three versions each. Our approach involved collecting C&K and evolution metrics using two different tools, calculating the stability metric for classes, and analyzing the data with SPSS to determine correlations. The results show a significant negative correlation between the class stability metric (CSM) and nine other metrics, confirming that C&K and evolution metrics are generally negatively correlated with CSM, although three C&K metrics exhibit weak correlations. These findings enhance our understanding of the relationship between various metrics and class stability, contributing to more stable and maintainable software systems.

Original language	English
Title of host publication	Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings
Editors	Hamid R. Arabnia, Leonidas Deligiannidis, Farzan Shenavarmasouleh, Soheyla Amirian, Farid Ghareh Mohammadi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	300-313
Number of pages	14
ISBN (Print)	9783031951268
DOIs	https://doi.org/10.1007/978-3-031-95127-5_22
State	Published - 2025
Event	11th International Conference on Computational Science and Computational Intelligence, CSCI 2024 - Las Vegas, United States Duration: 11 Dec 2024 → 13 Dec 2024

Publication series

Name	Communications in Computer and Information Science
Volume	2505 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	11th International Conference on Computational Science and Computational Intelligence, CSCI 2024
Country/Territory	United States
City	Las Vegas
Period	11/12/24 → 13/12/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

C&K metrics
Class Stability
Evolution metrics
Object Oriented Programming

ASJC Scopus subject areas

General Computer Science
General Mathematics

Access to Document

10.1007/978-3-031-95127-5_22

Cite this

Ghaleb, M., Alasow, M., AlGhamdi, A., Hamdan, M., & Mahmood, S. (2025). Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study. In H. R. Arabnia, L. Deligiannidis, F. Shenavarmasouleh, S. Amirian, & F. Ghareh Mohammadi (Eds.), Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings (pp. 300-313). (Communications in Computer and Information Science; Vol. 2505 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-95127-5_22

Ghaleb, Mustafa ; Alasow, Mohamed ; AlGhamdi, Azzah et al. / Analyzing Class Stability Through C&K and Evolution Metrics : An Empirical Study. Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Farzan Shenavarmasouleh ; Soheyla Amirian ; Farid Ghareh Mohammadi. Springer Science and Business Media Deutschland GmbH, 2025. pp. 300-313 (Communications in Computer and Information Science).

@inproceedings{da9b374006e446769e552781e6d1aaad,

title = "Analyzing Class Stability Through C\&K and Evolution Metrics: An Empirical Study",

abstract = "This study addresses the challenges introduced by the shift from procedural-oriented to object-oriented paradigms, focusing on the need to maintain consistent design while satisfying market demands, particularly in achieving software stability. While previous research has explored various factors affecting software stability, a gap remains in understanding the correlation between class stability and C\&K and evolution-based metrics. To fill this gap, we conducted an empirical investigation using two open-source Java projects, Android and Eclipse, across three versions each. Our approach involved collecting C\&K and evolution metrics using two different tools, calculating the stability metric for classes, and analyzing the data with SPSS to determine correlations. The results show a significant negative correlation between the class stability metric (CSM) and nine other metrics, confirming that C\&K and evolution metrics are generally negatively correlated with CSM, although three C\&K metrics exhibit weak correlations. These findings enhance our understanding of the relationship between various metrics and class stability, contributing to more stable and maintainable software systems.",

keywords = "C\&K metrics, Class Stability, Evolution metrics, Object Oriented Programming",

author = "Mustafa Ghaleb and Mohamed Alasow and Azzah AlGhamdi and Mosab Hamdan and Sajjad Mahmood",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 11th International Conference on Computational Science and Computational Intelligence, CSCI 2024 ; Conference date: 11-12-2024 Through 13-12-2024",

year = "2025",

doi = "10.1007/978-3-031-95127-5\_22",

language = "English",

isbn = "9783031951268",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "300--313",

editor = "Arabnia, \{Hamid R.\} and Leonidas Deligiannidis and Farzan Shenavarmasouleh and Soheyla Amirian and \{Ghareh Mohammadi\}, Farid",

booktitle = "Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings",

address = "Germany",

}

Ghaleb, M, Alasow, M, AlGhamdi, A, Hamdan, M & Mahmood, S 2025, Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study. in HR Arabnia, L Deligiannidis, F Shenavarmasouleh, S Amirian & F Ghareh Mohammadi (eds), Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings. Communications in Computer and Information Science, vol. 2505 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 300-313, 11th International Conference on Computational Science and Computational Intelligence, CSCI 2024, Las Vegas, United States, 11/12/24. https://doi.org/10.1007/978-3-031-95127-5_22

Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study. / Ghaleb, Mustafa; Alasow, Mohamed; AlGhamdi, Azzah et al.
Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Farzan Shenavarmasouleh; Soheyla Amirian; Farid Ghareh Mohammadi. Springer Science and Business Media Deutschland GmbH, 2025. p. 300-313 (Communications in Computer and Information Science; Vol. 2505 CCIS).

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

TY - GEN

T1 - Analyzing Class Stability Through C&K and Evolution Metrics

T2 - 11th International Conference on Computational Science and Computational Intelligence, CSCI 2024

AU - Ghaleb, Mustafa

AU - Alasow, Mohamed

AU - AlGhamdi, Azzah

AU - Hamdan, Mosab

AU - Mahmood, Sajjad

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - This study addresses the challenges introduced by the shift from procedural-oriented to object-oriented paradigms, focusing on the need to maintain consistent design while satisfying market demands, particularly in achieving software stability. While previous research has explored various factors affecting software stability, a gap remains in understanding the correlation between class stability and C&K and evolution-based metrics. To fill this gap, we conducted an empirical investigation using two open-source Java projects, Android and Eclipse, across three versions each. Our approach involved collecting C&K and evolution metrics using two different tools, calculating the stability metric for classes, and analyzing the data with SPSS to determine correlations. The results show a significant negative correlation between the class stability metric (CSM) and nine other metrics, confirming that C&K and evolution metrics are generally negatively correlated with CSM, although three C&K metrics exhibit weak correlations. These findings enhance our understanding of the relationship between various metrics and class stability, contributing to more stable and maintainable software systems.

AB - This study addresses the challenges introduced by the shift from procedural-oriented to object-oriented paradigms, focusing on the need to maintain consistent design while satisfying market demands, particularly in achieving software stability. While previous research has explored various factors affecting software stability, a gap remains in understanding the correlation between class stability and C&K and evolution-based metrics. To fill this gap, we conducted an empirical investigation using two open-source Java projects, Android and Eclipse, across three versions each. Our approach involved collecting C&K and evolution metrics using two different tools, calculating the stability metric for classes, and analyzing the data with SPSS to determine correlations. The results show a significant negative correlation between the class stability metric (CSM) and nine other metrics, confirming that C&K and evolution metrics are generally negatively correlated with CSM, although three C&K metrics exhibit weak correlations. These findings enhance our understanding of the relationship between various metrics and class stability, contributing to more stable and maintainable software systems.

KW - C&K metrics

KW - Class Stability

KW - Evolution metrics

KW - Object Oriented Programming

UR - https://www.scopus.com/pages/publications/105013625068

U2 - 10.1007/978-3-031-95127-5_22

DO - 10.1007/978-3-031-95127-5_22

M3 - Conference contribution

AN - SCOPUS:105013625068

SN - 9783031951268

T3 - Communications in Computer and Information Science

SP - 300

EP - 313

BT - Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings

A2 - Arabnia, Hamid R.

A2 - Deligiannidis, Leonidas

A2 - Shenavarmasouleh, Farzan

A2 - Amirian, Soheyla

A2 - Ghareh Mohammadi, Farid

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 11 December 2024 through 13 December 2024

ER -

Ghaleb M, Alasow M, AlGhamdi A, Hamdan M, Mahmood S. Analyzing Class Stability Through C&K and Evolution Metrics: An Empirical Study. In Arabnia HR, Deligiannidis L, Shenavarmasouleh F, Amirian S, Ghareh Mohammadi F, editors, Computational Science and Computational Intelligence - 11th International Conference, CSCI 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2025. p. 300-313. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-95127-5_22