Mining fine-grained code changes to detect unknown change patterns

Stas Negara, Mihai Codoban, Danny Dig, Ralph E. Johnson

Abstract

Identifying repetitive code changes benefits developers, tool builders, and researchers. Tool builders can automate the popular code changes, thus improving the productivity of developers. Researchers can better understand the practice of code evolution, advancing existing code assistance tools and benefiting developers even further. Unfortunately, existing research either predominantly uses coarse-grained Version Control System (VCS) snapshots as the primary source of code evolution data or considers only a small subset of program transformations of a single kind - refactorings.

BibTeX

@inproceedings{Negara-al:ICSE14,
  author    = {Stas Negara and
               Mihai Codoban and
               Danny Dig and
               Ralph E. Johnson},
  title     = {Mining fine-grained code changes to detect unknown change patterns},
  booktitle = {ICSE},
  pages     = {803--813},
  publisher = {{ACM}},
  year      = {2014},
}

Mining fine-grained code changes to detect unknown change patterns

Abstract

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