Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Chavoya:2012:PLOS,
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author = "Arturo Chavoya and Cuauhtemoc Lopez-Martin and
Irma R. Andalon-Garcia and M. E. Meda-Campana",
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title = "Genetic Programming as Alternative for Predicting
Development Effort of Individual Software Projects",
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journal = "PLoS ONE",
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year = "2012",
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volume = "7",
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number = "11",
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pages = "e50531",
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month = nov # " 30",
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keywords = "genetic algorithms, genetic programming, SBSE",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.1035.6477",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1035.6477",
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URL = "http://europepmc.org/backend/ptpmcrender.fcgi?accid%3DPMC3511534%26blobtype%3Dpdf",
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URL = "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0050531.pdf",
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DOI = "doi:10.1371/journal.pone.0050531",
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size = "10 pages",
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abstract = "Statistical and genetic programming techniques have
been used to predict the software development effort of
large software projects. In this paper, a genetic
programming model was used for predicting the effort
required in individually developed projects. Accuracy
obtained from a genetic programming model was compared
against one generated from the application of a
statistical regression model. A sample of 219 projects
developed by 71 practitioners was used for generating
the two models, whereas another sample of 130 projects
developed by 38 practitioners was used for validating
them. The models used two kinds of lines of code as
well as programming language experience as independent
variables. Accuracy results from the model obtained
with genetic programming suggest that it could be used
to predict the software development effort of
individual projects when these projects have been
developed in a disciplined manner within a
development-controlled environment.",
- }
Genetic Programming entries for
Arturo Chavoya-Pena
Cuauhtemoc Lopez-Martin
Irma R Andalon-Garcia
Maria Elena Meda-Campana
Citations