Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2022

Abstract

It is not a trivial problem to collect API-relevant examples, usages, and mentions on venues such as Stack Overflow. It requires efforts to correctly recognize whether the discussion refers to the API method that developers/tools are searching for. The content of the Stack Overflow thread, which consists of both text paragraphs describing the involvement of the API method in the discussion and the code snippets containing the API invocation, may refer to the given API method. Leveraging this observation, we develop ARSeek, a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a discussion. ARSeek combines a syntactic word-based score with a score from a predictive model fine-tuned from CodeBERT. In terms of F1-score, ARSeek achieves an average score of 0.8709 and beats the state-of-the-art approach by 14%.

Keywords

API resource, API embedding, Content classification

Discipline

Databases and Information Systems

Research Areas

Information Systems and Management

Publication

Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension, Pittsburgh, United States, 2022 May 16 - 17

First Page

331

Last Page

342

ISBN

9781450392983

Identifier

10.1145/3524610.3527918

Publisher

IEEE Computer Society

City or Country

Pittsburgh, Pennsylvania

Additional URL

https://doi.org/10.1145/3524610.3527918

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