ARCLIN: Automated API Mention Resolution for Unformatted Texts
Thu 12 May 2022 13:25 - 13:30 at ICSE room 2-odd hours - Tools and Environments 6 Chair(s): Domenico Bianculli
Fri 27 May 2022 09:40 - 09:45 at Room 306+307 - Papers 18: Recommender Systems, tools and environments Chair(s): Christian Bird
Online technical forums (e.g., StackOverflow) are popular platforms for developers to discuss technical problems such as how to use specific Application Programming Interface (API), how to solve the programming tasks, or how to fix bugs in their codes. These discussions can often provide auxiliary knowledge of how to use the software that is not covered by the official documents. The automatic extraction of such knowledge will support a set of downstream tasks like API searching or indexing. However, unlike official documentation written by experts, discussions in open forums are made by regular developers who write in short and informal texts, including spelling errors or abbreviations. There are three major challenges for the accurate APIs recognition and linking mentioned APIs from unstructured natural language documents to an entry in the API repository: (1) distinguishing API mentions from common words; (2) identifying API mentions without a fully qualified name; and (3) disambiguating API mentions with similar method names but in a different library.
In this paper, to tackle these challenges, we propose an ARCLIN tool, which can effectively distinguish and link APIs without using human annotations. Specifically, we first design an API recognizer to automatically extract API mentions from natural language sentences by a Condition Random Field (CRF) on the top of a Bi-directional Long Short-Term Memory (Bi-LSTM) module, then we apply a context-aware scoring mechanism to compute the mention-entry similarity for each entry in an API repository. Compared to previous approaches with heuristic rules, our proposed tool without manual inspection outperforms by 8% in a high-quality dataset Py-mention, which contains 558 mentions and 2,830 sentences from five popular Python libraries. To our best knowledge, ARCLIN is the first approach to achieving full automation of API mention resolution from unformatted text without manually collected labels.
Wed 11 MayDisplayed time zone: Eastern Time (US & Canada) change
05:00 - 06:00 | Tools and ConfigurationsTechnical Track / SEIP - Software Engineering in Practice at ICSE room 3-odd hours Chair(s): Robert Chatley Imperial College London | ||
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05:10 5mTalk | ARCLIN: Automated API Mention Resolution for Unformatted Texts Technical Track Yintong Huo The Chinese University of Hong Kong, Yuxin Su Sun Yat-sen University, Hongming Zhang The Hong Kong University of Science and Technology, Michael Lyu The Chinese University of Hong Kong DOI Pre-print Media Attached | ||
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Fri 27 MayDisplayed time zone: Eastern Time (US & Canada) change
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09:40 5mTalk | ARCLIN: Automated API Mention Resolution for Unformatted Texts Technical Track Yintong Huo The Chinese University of Hong Kong, Yuxin Su Sun Yat-sen University, Hongming Zhang The Hong Kong University of Science and Technology, Michael Lyu The Chinese University of Hong Kong DOI Pre-print Media Attached | ||