Improving automated source code summarization via an eye-tracking study of programmers

Paige Rodeghero, Collin McMillan, Paul W. McBurney, Nigel Bosch, Sidney D'Mello

Research output: Contribution to journalConference articlepeer-review


Source Code Summarization is an emerging technology for automatically generating brief descriptions of code. Current summarization techniques work by selecting a subset of the statements and keywords from the code, and then including information from those statements and keywords in the summary. The quality of the summary depends heavily on the process of selecting the subset: a high-quality selection would contain the same statements and keywords that a programmer would choose. Unfortunately, little evidence exists about the statements and keywords that programmers view as important when they summarize source code. In this paper, we present an eye-tracking study of 10 professional Java programmers in which the programmers read Java methods and wrote English summaries of those methods. We apply the findings to build a novel summarization tool. Then, we evaluate this tool and provide evidence to support the development of source code summarization systems.

Original languageEnglish (US)
Pages (from-to)390-401
Number of pages12
JournalProceedings - International Conference on Software Engineering
Issue number1
StatePublished - May 31 2014
Externally publishedYes
Event36th International Conference on Software Engineering, ICSE 2014 - Hyderabad, India
Duration: May 31 2014Jun 7 2014


  • program comprehension
  • source code summaries

ASJC Scopus subject areas

  • Software


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