Two case studies of open source software development: Apache and Mozilla
ACM Transactions on Software Engineering and Methodology (TOSEM)
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Evolution in Open Source Software: A Case Study
ICSM '00 Proceedings of the International Conference on Software Maintenance (ICSM'00)
Characteristics of Open Source Projects
CSMR '03 Proceedings of the Seventh European Conference on Software Maintenance and Reengineering
Toward Understanding the Rhetoric of Small Source Code Changes
IEEE Transactions on Software Engineering
Measuring Fine-Grained Change in Software: Towards Modification-Aware Change Metrics
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
A study of the contributors of PostgreSQL
Proceedings of the 2006 international workshop on Mining software repositories
How we refactor, and how we know it
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Gathering refactoring data: a comparison of four methods
Proceedings of the 2nd Workshop on Refactoring Tools
An exploratory study of the evolution of software licensing
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Proceedings of the 1st Workshop on Web 2.0 for Software Engineering
Automatically identifying changes that impact code-to-design traceability during evolution
Software Quality Control
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Do time of day and developer experience affect commit bugginess?
Proceedings of the 8th Working Conference on Mining Software Repositories
Visualizing collaboration and influence in the open-source software community
Proceedings of the 8th Working Conference on Mining Software Repositories
An empirical investigation into the role of API-level refactorings during software evolution
Proceedings of the 33rd International Conference on Software Engineering
On mining sensor network software repositories
Proceedings of the 2nd Workshop on Software Engineering for Sensor Network Applications
Failure is a four-letter word: a parody in empirical research
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
On the difficulty of computing the truck factor
PROFES'11 Proceedings of the 12th international conference on Product-focused software process improvement
ReLink: recovering links between bugs and changes
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Factors affecting the success of Open Source Software
Journal of Systems and Software
FASE'12 Proceedings of the 15th international conference on Fundamental Approaches to Software Engineering
Is it dangerous to use version control histories to study source code evolution?
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Multi-layered approach for recovering links between bug reports and fixes
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Are Developers Fixing Their Own Bugs?: Tracing Bug-Fixing and Bug-Seeding Committers
International Journal of Open Source Software and Processes
Gerrit software code review data from Android
Proceedings of the 10th Working Conference on Mining Software Repositories
The impact of tangled code changes
Proceedings of the 10th Working Conference on Mining Software Repositories
The MSR cookbook: mining a decade of research
Proceedings of the 10th Working Conference on Mining Software Repositories
Empirical Software Engineering
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Research in the mining of software repositories has frequently ignored commits that include a large number of files (we call these large commits). The main goal of this paper is to understand the rationale behind large commits, and if there is anything we can learn from them. To address this goal we performed a case study that included the manual classification of large commits of nine open source projects. The contributions include a taxonomy of large commits, which are grouped according to their intention. We contrast large commits against small commits and show that large commits are more perfective while small commits are more corrective. These large commits provide us with a window on the development practices of maintenance teams.