Ontology: its transformation from philosophy to information systems
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Supporting reuse by delivering task-relevant and personalized information
Proceedings of the 24th International Conference on Software Engineering
Mining Version Histories to Guide Software Changes
Proceedings of the 26th International Conference on Software Engineering
Using structural context to recommend source code examples
Proceedings of the 27th international conference on Software engineering
IEEE Transactions on Knowledge and Data Engineering
Hipikat: A Project Memory for Software Development
IEEE Transactions on Software Engineering
Using task context to improve programmer productivity
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Suade: Topology-Based Searches for Software Investigation
ICSE '07 Proceedings of the 29th international conference on Software Engineering
Parseweb: a programmer assistant for reusing open source code on the web
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Recommendation Systems for Software Engineering
IEEE Software
Recommending API methods based on identifier contexts
Proceedings of the 3rd International Workshop on Search-Driven Development: Users, Infrastructure, Tools, and Evaluation
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A software developer programming in an object-oriented programming language deals with a source code structure that may contain hundreds of source code elements. These elements are commonly related to each other and working on a specific element may require the developer to access other related elements. We propose a recommendation approach that uses the context of the developer to retrieve and rank recommendations of relevant source code elements in the IDE. These recommendations provide a shortcut to reach the desired elements and increase the awareness of the developer in relation to elements that may be of interest in that moment. We have tested our approach with a group of developers and the results show that context has a promising role in predicting and ranking the source code elements needed by a developer at each moment.