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Ten years of hunting for similar code for fun and profit (keynote)

Stéphane Glondu, Lingxiao Jiang, Zhendong Su

Abstract

In 2007, the Deckard paper was published at ICSE. Since its publication, it has led to much follow-up research and applications. The paper made two core contributions: a novel vector embedding of structured code for fast similarity detection, and an application of the embedding for clone detection, resulting in the Deckard tool. The vector embedding is simple and easy to adapt. Similar code detection is also fundamental for a range of classical and emerging problems in software engineering, security, and computer science education (e.g., code reuse, refactoring, porting, translation, synthesis, program repair, malware detection, and feedback generation). Both have buttressed the paper’s influence.

BibTeX
@inproceedings{Glondu-al:FSE18,
  author    = {St{\'{e}}phane Glondu and
               Lingxiao Jiang and
               Zhendong Su},
  title     = {Ten years of hunting for similar code for fun and profit (keynote)},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {2},
  publisher = {{ACM}},
  year      = {2018},
}

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