On the Use of Smelly Examples to Detect Code Smells in JavaScript

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Shoenberger:2017:evoApplications,
  author =       "Ian Shoenberger and Mohamed Wiem Mkaouer and 
                 Marouane Kessentini",
  title =        "On the Use of Smelly Examples to Detect Code Smells in
                 {JavaScript}",
  booktitle =    "20th European Conference on the Applications of
                 Evolutionary Computation",
  year =         "2017",
  editor =       "Giovanni Squillero",
  series =       "LNCS",
  volume =       "10200",
  publisher =    "Springer",
  pages =        "20--34",
  address =      "Amsterdam",
  month =        "19-21 " # apr,
  organisation = "Species",
  keywords =     "genetic algorithms, genetic programming, SBSE",
  DOI =          "doi:10.1007/978-3-319-55792-2_2",
  size =         "16 pages",
  abstract =     "JavaScript has become one of the widely-used
                 languages. However, as the size of JavaScript-based
                 applications grows, the number of defects grows as
                 well. Recent studies have produced a set of manually
                 defined rules to identify these defects. We propose, in
                 this work, the automation of deriving these rules to
                 ensure scalability and potentially the detection of a
                 wider set of defects without requiring any extensive
                 knowledge on rules tuning. To this end, we rely on a
                 base of existing code smells that is used to train the
                 detection rules using Genetic Programming and find the
                 best threshold of metrics composing the rules. The
                 evaluation of our work on 9 JavaScript web projects has
                 shown promising results in terms of detection precision
                 of 92percent and recall of 85percent, with no threshold
                 tuning required.",
  notes =        "EvoApplications2017 held in conjunction with
                 EuroGP'2017, EvoCOP2017 and EvoMusArt2017
                 http://www.evostar.org/2017/cfp_evoapps.php.",
}

Genetic Programming entries for Ian Shoenberger Mohamed Wiem Mkaouer Marouane Kessentini

Citations