SEffEst: Effort estimation in software projects using fuzzy logic and neural networks

Academia and practitioners confirm that software project effort prediction is crucial for an accurate software project management. However, software development effort estimation is uncertain by nature. Literature has developed methods to improve estimation correctness, using artificial intelligence...

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Main Authors: Israel González-Carrasco, Ricardo Colomo-Palacios, José Luis López-Cuadrado, Francisco José García Peñalvo
Format: Article
Language:English
Published: Springer 2012-08-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/25868001.pdf
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author Israel González-Carrasco
Ricardo Colomo-Palacios
José Luis López-Cuadrado
Francisco José García Peñalvo
author_facet Israel González-Carrasco
Ricardo Colomo-Palacios
José Luis López-Cuadrado
Francisco José García Peñalvo
author_sort Israel González-Carrasco
collection DOAJ
description Academia and practitioners confirm that software project effort prediction is crucial for an accurate software project management. However, software development effort estimation is uncertain by nature. Literature has developed methods to improve estimation correctness, using artificial intelligence techniques in many cases. Following this path, this paper presents SEffEst, a framework based on fuzzy logic and neural networks designed to increase effort estimation accuracy on software development projects. Trained using ISBSG data, SEffEst presents remarkable results in terms of prediction accuracy.
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spelling doaj.art-45d8e33a2e144b32b8bfccaee547f68b2022-12-22T00:25:59ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832012-08-015410.1080/18756891.2012.718118SEffEst: Effort estimation in software projects using fuzzy logic and neural networksIsrael González-CarrascoRicardo Colomo-PalaciosJosé Luis López-CuadradoFrancisco José García PeñalvoAcademia and practitioners confirm that software project effort prediction is crucial for an accurate software project management. However, software development effort estimation is uncertain by nature. Literature has developed methods to improve estimation correctness, using artificial intelligence techniques in many cases. Following this path, this paper presents SEffEst, a framework based on fuzzy logic and neural networks designed to increase effort estimation accuracy on software development projects. Trained using ISBSG data, SEffEst presents remarkable results in terms of prediction accuracy.https://www.atlantis-press.com/article/25868001.pdfFuzzy LogicNeural NetworksSoftware EngineeringEffort Estimation
spellingShingle Israel González-Carrasco
Ricardo Colomo-Palacios
José Luis López-Cuadrado
Francisco José García Peñalvo
SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
International Journal of Computational Intelligence Systems
Fuzzy Logic
Neural Networks
Software Engineering
Effort Estimation
title SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
title_full SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
title_fullStr SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
title_full_unstemmed SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
title_short SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
title_sort seffest effort estimation in software projects using fuzzy logic and neural networks
topic Fuzzy Logic
Neural Networks
Software Engineering
Effort Estimation
url https://www.atlantis-press.com/article/25868001.pdf
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AT ricardocolomopalacios seffesteffortestimationinsoftwareprojectsusingfuzzylogicandneuralnetworks
AT joseluislopezcuadrado seffesteffortestimationinsoftwareprojectsusingfuzzylogicandneuralnetworks
AT franciscojosegarciapenalvo seffesteffortestimationinsoftwareprojectsusingfuzzylogicandneuralnetworks