• DocumentCode
    555275
  • Title

    Automatically detecting and describing high level actions within methods

  • Author

    Sridhara, Giriprasad ; Pollock, Lori ; Vijay-Shanker, K.

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. of Delaware, Newark, DE, USA
  • fYear
    2011
  • fDate
    21-28 May 2011
  • Firstpage
    101
  • Lastpage
    110
  • Abstract
    One approach to easing program comprehension is to reduce the amount of code that a developer has to read. Describing the high level abstract algorithmic actions associated with code fragments using succinct natural language phrases potentially enables a newcomer to focus on fewer and more abstract concepts when trying to understand a given method. Unfortunately, such descriptions are typically missing because it is tedious to create them manually. We present an automatic technique for identifying code fragments that implement high level abstractions of actions and expressing them as a natural language description. Our studies of 1000 Java programs indicate that our heuristics for identifying code fragments implementing high level actions are widely applicable. Judgements of our generated descriptions by 15 experienced Java programmers strongly suggest that indeed they view the fragments that we identify as representing high level actions and our synthesized descriptions accurately express the abstraction.
  • Keywords
    Java; natural language processing; program compilers; program diagnostics; Java programmers; Java programs; abstract concepts; automatic technique; code fragments; high level abstract algorithmic actions; high level actions; natural language description; program comprehension; succinct natural language phrases; Documentation; Java; Natural languages; Pragmatics; Semantics; Software; Syntactics; documentation; program comprehension;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (ICSE), 2011 33rd International Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    0270-5257
  • Print_ISBN
    978-1-4503-0445-0
  • Electronic_ISBN
    0270-5257
  • Type

    conf

  • DOI
    10.1145/1985793.1985808
  • Filename
    6032449