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Title: API recognition and linking in stack overflow
Authors: Foo, Chee Yong
Keywords: DRNTU::Engineering::Computer science and engineering::Information systems
Issue Date: 2016
Abstract: Stack Overflow, one of the most popular programming Q&A forum has become a wealth of information on software engineering. This textual content provides rich and up-to-date learning resources for developers to learn the usage of application programming interface (API). However, it can be insufficient on its own and developers often need to do further reading on the API documentation. APIs mentioned in natural language texts are rarely fully qualified, so simple matching of the names may be linked to many potential code elements declared by different classes and/or different libraries. In this report, we propose a filter based method of linking API terms in Stack Overflow posts to API documentation by leveraging the context in which an API is mentioned. We also present the implementation of a web application, called LinkAPI, to automatically incorporate online API documentation links into the API terms in Stack Overflow posts. In an evaluation study with three popular Python libraries, we found that our linking technique can resolve most of the ambiguities.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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