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Active code search: incorporating user feedback to improve code search relevance

Shaowei Wang, David Lo, Lingxiao Jiang

Abstract

Code search techniques return relevant code fragments given a user query. They typically work in a passive mode: given a user query, a static list of code fragments sorted by the relevance scores decided by a code search technique is returned to the user. A user will go through the sorted list of returned code fragments from top to bottom. As the user checks each code fragment one by one, he or she will naturally form an opinion about the true relevance of the code fragment. In an active model, those opinions will be taken as feedbacks to the search engine for refining result lists.

BibTeX
@inproceedings{Wang-al:ASE14,
  author    = {Shaowei Wang and
               David Lo and
               Lingxiao Jiang},
  title     = {Active code search: incorporating user feedback to improve code search relevance},
  booktitle = {ASE},
  pages     = {677--682},
  publisher = {{ACM}},
  year      = {2014},
}

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