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ASE 2022

Are Neural Bug Detectors Comparable to Software Developers on Variable Misuse Bugs?

Cedric Richter, Jan Haltermann, Marie-Christine Jakobs, Felix Pauck, Stefan Schott, Heike Wehrheim

PDFDOI 10.1145/3551349.3561156dblp

Abstract

Debugging, that is, identifying and fixing bugs in software, is a central part of software development. Developers are therefore often confronted with the task of deciding whether a given code snippet contains a bug, and if yes, where. Recently, data-driven methods have been employed to learn this task of bug detection, resulting (amongst others) in so called neural bug detectors. Neural bug detectors are trained on millions of buggy and correct code snippets.

BibTeX
@inproceedings{Richter-al:ASE22,
  author    = {Cedric Richter and
               Jan Haltermann and
               Marie{-}Christine Jakobs and
               Felix Pauck and
               Stefan Schott and
               Heike Wehrheim},
  title     = {Are Neural Bug Detectors Comparable to Software Developers on Variable Misuse Bugs?},
  booktitle = {ASE},
  pages     = {9:1--9:12},
  publisher = {{ACM}},
  year      = {2022},
}

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