Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2021

Abstract

Developers often rely on API documentation to learn API directives, i.e., constraints and guidelines related to API usage. Failing to follow API directives may cause defects or improper implementations. Since there are no industry-wide standards on how to document API directives, they take many forms and are often hard to understand by developers or challenging to parse with tools. In this paper, we propose a learning based approach for extracting first-order logic representations of API directives (FOL directives for short). The approach, called LeadFOL, uses a joint learning method to extract atomic formulas by identifying the predicates and arguments involved in directive sentences, and recognizes the logical relations between atomic formulas, by parsing the sentence structures. It then parses the arguments and uses a learning based method to link API references to their corresponding API elements. Finally, it groups the formulas of the same class or method together and transforms them into conjunctive normal form. Our evaluation shows that LeadFOL can accurately extract more FOL directives than a state-of-the-art approach and that the extracted FOL directives are useful in supporting code reviews.

Keywords

API Documentation, Directive, First Order Logic

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '21), Virtual Online, August 23-28

First Page

491

Last Page

502

ISBN

9781450385626

Identifier

10.1145/3468264.3468618

Publisher

ACM

City or Country

New York

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1145/3468264.3468618

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