Effort estimation of software project
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gp-bibliography.bib Revision:1.7954
- @Article{Merugu:2012:IJARCET,
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title = "Effort estimation of software project",
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author = "R Raja Ramesh Merugu and Venkat Ravi Kumar Dammu",
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journal = "International Journal of Advanced Research in Computer
Engineering \& Technology",
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publisher = "Shri Pannalal Research Institute of Technology",
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year = "2012",
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keywords = "genetic algorithms, genetic programming, SBSE, effort
estimation, fuzzy logic, particle swarm optimisation,
MMRE, neural networks",
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ISSN = "22781323",
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bibsource = "OAI-PMH server at www.doaj.org",
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oai = "oai:doaj-articles:65e54283cfc94cdfd7b789a43a65f1b0",
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URL = "http://ijarcet.org/wp-content/uploads/IJARCET-VOL-1-ISSUE-10-33-41.pdf",
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URL = "http://ijarcet.org/?p=1249",
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abstract = "The effort invested in a software project is probably
one of the most important and most analysed variables
in recent years in the process of project management.
The limitation of algorithmic effort prediction models
is their inability to cope with uncertainties and
imprecision surrounding software projects at the early
development stage. More recently attention has turned
to a variety of machine learning methods, and soft
computing in particular to predict software development
effort. Soft computing is a consortium of methodologies
centering in fuzzy logic, artificial neural networks
and evolutionary computation. It is important to
mention here that these methodologies are complementary
and synergistic rather than competitive. They provide
in one form or another flexible information processing
capability for handling real life ambiguous situations.
These methodologies are currently used for reliable and
accurate estimate of software development effort which
has always been a challenge for both the software
industry and academia. The aim of this study is to
analyse soft computing techniques in the existing
models and to provide in depth review of software and
project estimation techniques existing in industry and
literature based on the different test datasets along
with their strength and weaknesses.",
- }
Genetic Programming entries for
R Raja Ramesh Merugu
Venkat Ravi Kumar Dammu
Citations