Data Mining Library Reuse Patterns in User-Selected Applications
ASE '99 Proceedings of the 14th IEEE international conference on Automated software engineering
Predicting Source Code Changes by Mining Change History
IEEE Transactions on Software Engineering
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Approximate Structural Context Matching: An Approach to Recommend Relevant Examples
IEEE Transactions on Software Engineering
Mining API patterns as partial orders from source code: from usage scenarios to specifications
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Recommending adaptive changes for framework evolution
Proceedings of the 30th international conference on Software engineering
Mining temporal rules for software maintenance
Journal of Software Maintenance and Evolution: Research and Practice - Special Issue on Program Comprehension through Dynamic Analysis (PCODA)
Improving API documentation usability with knowledge pushing
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Learning from examples to improve code completion systems
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
MAPO: Mining and Recommending API Usage Patterns
Genoa Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming
Using structure-based recommendations to facilitate discoverability in APIs
Proceedings of the 25th European conference on Object-oriented programming
A field study of API learning obstacles
Empirical Software Engineering
Temporal analysis of API usage concepts
Proceedings of the 34th International Conference on Software Engineering
Detecting API usage obstacles: a study of iOS and Android developer questions
Proceedings of the 10th Working Conference on Mining Software Repositories
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Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. As developers write client programs, their understanding and usage of APIs change over time. Can we learn from long-term changes in how developers work with APIs in the lifetime of a client program? We propose Temporal API Usage Mining to detect significant changes in API usage. We describe a framework to extract detailed models representing addition and removal of calls to API methods over the change history of a client program. We apply machine learning technique to these models to semi-automatically infer temporal API usage patterns, i.e., coherent addition of API calls at different phases in the life-cycle of the client program.