Conference proceeding
The Birth, Growth, Death and Rejuvenation of Software Maintenance Communities
PROCEEDINGS OF THE 12TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT (ESEM 2018)
01 Jan 2018
Abstract
Background: Though much research has been conducted to investigate software maintenance activities, there has been little work charactering maintenance files as a community and exploring the evolution of this community. Aims: The goal of our research is to identify maintenance communities and monitor their evolution-birth, growth, death and rejuvenation. Method: In this paper, we leveraged a social community detection algorithm-clique prelocation method (CPM)-to identify file communities. Then we implemented an algorithm to detect new communities, active communities, inactive communities and reactivated communities by cumulatively detecting and constantly comparing communities in time sequences. Results: Based on our analysis of 14 open-source projects, we found that new communities are mostly caused by bug and improvement issues. An active community can be vigorous, on and off, through the entire life of a system, and so does an inactive community. In addition, an inactive community can be reactivated again, mostly through bug issues. Conclusions: These findings add to our understanding of software maintenance communities and help us identify the most expensive maintenance spots by identifying constantly active communities.
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Details
- Title
- The Birth, Growth, Death and Rejuvenation of Software Maintenance Communities
- Creators
- Qiong Feng - Drexel UniversityYuanfang Cai - Drexel UniversityRick Kazman - University of Hawaii SystemRan Mo - Drexel UniversityACM
- Publication Details
- PROCEEDINGS OF THE 12TH ACM/IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT (ESEM 2018)
- Publisher
- Assoc Computing Machinery
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000469776800005
- Scopus ID
- 2-s2.0-85061484364
- Other Identifier
- 991019167691504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Software Engineering
- Computer Science, Theory & Methods