Inferring Resource Specifications from Natural Language API Documentation

  • Authors:

  • Hao Zhong;Lu Zhang;Tao Xie;Hong Mei

  • Affiliations:

  • -;-;-;-

  • Venue:
  • ASE '09 Proceedings of the 2009 IEEE/ACM International Conference on Automated Software Engineering
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Typically, software libraries provide API documentation, through which developers can learn how to use libraries correctly. However, developers may still write code inconsistent with API documentation and thus introduce bugs, as existing research shows that many developers are reluctant to carefully read API documentation. To find those bugs, researchers have proposed various detection approaches based on known specifications. To mine specifications, many approaches have been proposed, and most of them rely on existing client code. Consequently, these mining approaches would fail to mine specifications when client code is not available. In this paper, we propose an approach, called Doc2Spec, that infers resource specifications from API documentation. For our approach, we implemented a tool and conducted an evaluation on Javadocs of five libraries. The results show that our approach infers various specifications with relatively high precisions, recalls, and F-scores. We further evaluated the usefulness of inferred specifications through detecting bugs in open source projects. The results show that specifications inferred by Doc2Spec are useful to detect real bugs in existing projects.