Versioning Systems for Evolution Research
IWPSE '05 Proceedings of the Eighth International Workshop on Principles of Software Evolution
How do APIs evolve? A story of refactoring: Research Articles
Journal of Software Maintenance and Evolution: Research and Practice - IEEE International Conference on Software Maintenance (ICSM2005)
Refactoring-Aware Configuration Management for Object-Oriented Programs
ICSE '07 Proceedings of the 29th international conference on Software Engineering
Mining framework usage changes from instantiation code
Proceedings of the 30th international conference on Software engineering
Recommending adaptive changes for framework evolution
Proceedings of the 30th international conference on Software engineering
Module connection analysis: a tool for scheduling software debugging activities
AFIPS '72 (Fall, part I) Proceedings of the December 5-7, 1972, fall joint computer conference, part I
AURA: a hybrid approach to identify framework evolution
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Customized awareness: recommending relevant external change events
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Recovering inter-project dependencies in software ecosystems
Proceedings of the IEEE/ACM international conference on Automated software engineering
Extensions during software evolution: do objects meet their promise?
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Towards modeling and analyzing variability in evolving software ecosystems
Proceedings of the Seventh International Workshop on Variability Modelling of Software-intensive Systems
Software ecosystems - A systematic literature review
Journal of Systems and Software
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When the Application Programming Interface (API) of a framework or library changes, its clients must be adapted. This change propagation - known as a ripple effect - is a problem that has garnered interest: several approaches have been proposed in the literature to react to these changes. Although studies of ripple effects exist at the single system level, no study has been performed on the actual extent and impact of these API changes in practice, on an entire software ecosystem associated with a community of developers. This paper reports on early results of such an empirical study of API changes that led to ripple effects across an entire ecosystem. Our case study subject is the development community gravitating aroung the Squeak and Pharo software ecosystems: six years of evolution, nearly 3,000 contributors, and close to 2,500 distinct systems.