AMAP: automatically mining abbreviation expansions in programs to enhance software maintenance tools

  • Authors:

  • Emily Hill;Zachary P. Fry;Haley Boyd;Giriprasad Sridhara;Yana Novikova;Lori Pollock;K. Vijay-Shanker

  • Affiliations:

  • University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA;University of Delaware, Newark, DE, USA

  • Venue:
  • Proceedings of the 2008 international working conference on Mining software repositories
  • Year:
  • 2008

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Abstract

When writing software, developers often employ abbreviations in identifier names. In fact, some abbreviations may never occur with the expanded word, or occur more often in the code. However, most existing program comprehension and search tools do little to address the problem of abbreviations, and therefore may miss meaningful pieces of code or relationships between software artifacts. In this paper, we present an automated approach to mining abbreviation expansions from source code to enhance software maintenance tools that utilize natural language information. Our scoped approach uses contextual information at the method, program, and general software level to automatically select the most appropriate expansion for a given abbreviation. We evaluated our approach on a set of 250 potential abbreviations and found that our scoped approach provides a 57% improvement in accuracy over the current state of the art.