A Genetic Programming approach to Software Cost Modeling and Estimation

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Papatheocharous:2010:ICEIS,
  author =       "Efi Papatheocharous and Angela Iasonos and 
                 Andreas S. Andreou",
  title =        "A Genetic Programming approach to Software Cost
                 Modeling and Estimation",
  booktitle =    "Proceedings of the 12th International Conference on
                 Enterprise Information Systems (ICEIS 2010)",
  year =         "2010",
  editor =       "Joaquim Filipe and Jos{\'e} Cordeiro",
  pages =        "281--287",
  address =      "Funchal, Madeira, Portugal",
  month =        "8-12 " # jun,
  publisher =    "SciTePress",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 Software Cost Estimation, Software Engineering,
                 Software Measurement",
  isbn13 =       "978-989-8425-04-1",
  URL =          "http://ktisis.cut.ac.cy/jspui/handle/10488/3843",
  DOI =          "doi:10.5220/0002911602810287",
  size =         "7 pages",
  abstract =     "This paper investigates Genetic Programming (GP) as a
                 method to facilitate better software cost modeling and
                 estimation. The aim is to produce and examine candidate
                 solutions which use operators and operands, which are
                 then used in algorithmic cost estimation. These
                 solutions essentially constitute regression equations
                 of software cost factors, used to effectively estimate
                 the dependent variable, that is, the effort spent for
                 developing software projects. The GP application
                 generates representative rules through which the
                 usefulness of various project characteristics as
                 explanatory variables, and ultimately as predictors of
                 development effort is investigated. The experiments
                 conducted are based on two publicly available empirical
                 datasets typically used in software cost estimation and
                 indicate that the proposed approach provides consistent
                 and successful results.",
  notes =        "short paper http://www.iceis.org/iceis2010/index.htm
                 http://www.iceis.org/Abstracts/2010/ICEIS_2010_Abstracts.htm

                 isbn 978-989-8425-08-9, pages 281-287",
}

Genetic Programming entries for Efi Papatheocharous Angela L Iasonos Andreas S Andreou

Citations