How can we understand FOSS collaboration better? Can social issues that emerge be identified and addressed as they happen? Can the community heal itself, become more transparent and inclusive, and promote diversity? We propose a technique to address these issues by quantitative analysis and temporal visualization of social dynamics in FOSS communities. We used social network analysis metrics to identify growth patterns and unhealthy dynamics; This gives the community a heads-up when they can still take action to ensure the sustainability of the project.
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Recent Posts
- ICST 2017: The Theory of Composite Faults 10/12/2016
- FSE 2016: Can Testedness be Effectively Measured? 29/05/2016
- Software Quality Journal 2016: Does The Choice of Mutation Tool Matter? 08/05/2016
- ICSTW 2016: Measuring Effectiveness of Mutant Sets 08/05/2016
- ICSE 2016: On the limits of mutation reduction strategies 15/12/2015
- ISSRE 2015: How hard does mutation analysis have to be, anyway? 20/08/2015
- ASE 2015: How Verified is My Code? Falsification-Driven Verification 20/07/2015
- ESEM 2015: An empirical study of design degradation: how software projects get worse over time 20/05/2015
- ISSRE 2014: Mutations How close are they to real faults? 06/08/2014
- Sunbelt 2014: Temporal Visualization of Dynamic Collaboration Graphs of OSS Software Forks 28/01/2014
- ICSE 2014: Code Coverage for Suite Evaluation by Developers 28/01/2014
- OSS 2014: An Exploration of Factors Affecting Code Quality in FOSS Projects 20/01/2014
- OSS 2014: Drawing the Big Picture: Temporal Visualization of Dynamic Collaboration Graphs of OSS Software Forks 10/01/2014
- CHI 2014: Abandonment of Social Networks: Shift from Use to Non-Use and Experiences of Technology Non-Use 01/01/2014
- Entries 31/12/2013