Multi-objective code-smells detection using good and bad design examples

Created by W.Langdon from gp-bibliography.bib Revision:1.4472

  author =       "Usman Mansoor and Marouane Kessentini and 
                 Bruce R. Maxim and Kalyanmoy Deb",
  title =        "Multi-objective code-smells detection using good and
                 bad design examples",
  journal =      "Software Quality Journal",
  year =         "2017",
  volume =       "25",
  number =       "2",
  pages =        "529--552",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 Search-based software engineering, Software
                 maintenance, Software metrics, NSGA-2",
  ISSN =         "1573-1367",
  DOI =          "doi:10.1007/s11219-016-9309-7",
  abstract =     "Code-smells are identified, in general, by using a set
                 of detection rules. These rules are manually defined to
                 identify the key symptoms that characterize a
                 code-smell using combinations of mainly quantitative
                 (metrics), structural, and/or lexical information. We
                 propose in this work to consider the problem of
                 code-smell detection as a multi-objective problem where
                 examples of code-smells and well-designed code are used
                 to generate detection rules. To this end, we use
                 multi-objective genetic programming (MOGP) to find the
                 best combination of metrics that maximizes the
                 detection of code-smell examples and minimizes the
                 detection of well-designed code examples. We evaluated
                 our proposal on seven large open-source systems and
                 found that, on average, most of the different five
                 code-smell types were detected with an average of
                 87percent of precision and 92percent of recall.
                 Statistical analysis of our experiments over 51 runs
                 shows that MOGP performed significantly better than
                 state-of-the-art code-smell detectors.",

Genetic Programming entries for Usman Mansoor Marouane Kessentini Bruce R Maxim Kalyanmoy Deb