Distinguishing Software Aging from Stability in Open Source Projects: An Empirical Analysis of Activity Indicators

• Tassio Sirqueira UERJ
• Jessica Faciroli UERJ
• Vera Werneck UERJ

Resumo

Open-source software projects may experience variations in development activity over time. However, a decline in activity does not necessarily indicate software aging, as mature projects may require fewer changes over time. This study aims to distinguish software aging from stable maturity by analyzing activity indicators empirically. We conducted a longitudinal analysis of three open source projects, examining monthly trends in commits, active contributors, issues, and releases. The results show that stable projects exhibit low but consistent activity, whereas aging projects are characterized by abrupt and sustained declines across multiple indicators. The joint analysis of longitudinal activity indicators enables distinguishing between stability and software aging.

Referências

Bogart, C., Kästner, C., Herbsleb, J., and Thung, F. (2021). When and how to make breaking changes: Policies and practices in 18 open source software ecosystems. ACM Transactions on Software Engineering and Methodology (TOSEM), 30(4):1–56.

Calefato, F., Gerosa, M. A., Iaffaldano, G., Lanubile, F., and Steinmacher, I. (2022). Will you come back to contribute? investigating the inactivity of oss core developers in github. Empirical Software Engineering, 27(3):76.

Cotroneo, D., Natella, R., Pietrantuono, R., and Russo, S. (2014). A survey of software aging and rejuvenation studies. ACM Journal on Emerging Technologies in Computing Systems (JETC), 10(1):1–34.

Franco-Bedoya, O., Ameller, D., Costal, D., and Franch, X. (2014). Queso a quality model for open source software ecosystems. In 2014 9th International Conference on Software Engineering and Applications (ICSOFT-EA), pages 209–221. IEEE.

Jansen, S. (2014). Measuring the health of open source software ecosystems: Beyond the scope of project health. Information and Software Technology, 56(11):1508–1519. Special issue on Software Ecosystems.

Juntura, P. (2025). Degradation of openness? a comparative study on the evolution of open source in software and large language models. Master’s thesis, School of Business, Aalto University, Espoo, Finland.

Lehman, M. M. (1996). Laws of software evolution revisited. In Montangero, C., editor, Software Process Technology, pages 108–124, Berlin, Heidelberg. Springer Berlin Heidelberg.

Mens, T. and Goeminne, M. (2011). Analysing the evolution of social aspects of open source software ecosystems. In IWSECO@ ICSOB, pages 1–14.

Mens, T., Wermelinger, M., Ducasse, S., Demeyer, S., Hirschfeld, R., and Jazayeri, M. (2005). Challenges in software evolution. In Eighth International Workshop on Principles of Software Evolution (IWPSE’05), pages 13–22. IEEE.

Mockus, A., Fielding, R. T., and Herbsleb, J. D. (2002). Two case studies of open source software development: Apache and mozilla. ACM Transactions on Software Engineering and Methodology (TOSEM), 11(3):309–346.

Mukala, P. (2025). Exploring data analytics on open-source software repositories: A review of development activities and tools for mining logs. Available at SSRN 5391607.

Wu, X. (2024). A Fact-Based Approach to Software Evolution. Doctoral thesis, School of Computer Science and Engineering, Nanyang Technological University, Singapore.

Yazvinskyi, Y., Bogatinovski, J., Cardoso, J., and Kao, O. (2024). On software ageing indicators in openstack. arXiv preprint arXiv:2404.16446.