An approach for the evolutionary discovery of software architectures

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Aurora Ramirez and Jose Raul Romero and 
                 Sebastian Ventura",
  title =        "An approach for the evolutionary discovery of software
  journal =      "Information Sciences",
  year =         "2015",
  volume =       "305",
  pages =        "234--255",
  month =        "1 " # jun,
  keywords =     "genetic algorithms, genetic programming, SBSE, Search
                 based software engineering, Software architecture
                 discovery, Evolutionary algorithms, Ranking aggregation
  ISSN =         "0020-0255",
  URL =          "",
  DOI =          "doi:10.1016/j.ins.2015.01.017",
  size =         "22 pages",
  abstract =     "Software architectures constitute important analysis
                 artifacts in software projects, as they reflect the
                 main functional blocks of the software. They provide
                 high-level analysis artefacts that are useful when
                 architects need to analyse the structure of working
                 systems. Normally, they do this process manually,
                 supported by their prior experiences. Even so, the task
                 can be very tedious when the actual design is unclear
                 due to continuous uncontrolled modifications. Since the
                 recent appearance of search based software engineering,
                 multiple tasks in the area of software engineering have
                 been formulated as complex search and optimisation
                 problems, where evolutionary computation has found a
                 new area of application. This paper explores the design
                 of an evolutionary algorithm (EA) for the discovery of
                 the underlying architecture of software systems.
                 Important efforts have been directed towards the
                 creation of a generic and human-oriented process.
                 Hence, the selection of a comprehensible encoding, a
                 fitness function inspired by accurate software design
                 metrics, and a genetic operator simulating
                 architectural transformations all represent important
                 characteristics of the proposed approach. Finally, a
                 complete parameter study and experimentation have been
                 performed using real software systems, looking for a
                 generic evolutionary approach to help software
                 engineers towards their decision making process.",

Genetic Programming entries for Aurora Ramirez Quesada Jose Raul Romero Salguero Sebastian Ventura