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

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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Bibliographic Details
Main Authors: Israel González-Carrasco, Ricardo Colomo-Palacios, José Luis López-Cuadrado, Francisco José García Peñalvo
Format: Article
Language:English
Published: Atlantis Press 2012-08-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Fuzzy Logic
Neural Networks
Software Engineering
Effort Estimation
Online Access:https://www.atlantis-press.com/article/25868001.pdf
Description
Summary: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.
ISSN:1875-6883

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