Please use this identifier to cite or link to this item:
Title: On the problem of attribute selection for software cost estimation: Input backward elimination using artificial neural networks
Authors: Papatheocharous, Efi 
Andreou, Andreas S. 
Keywords: Artificial neural network;Software project;Artificial neural network models;Attribute selection;Backward elimination;Complex software;Connection weights;Cost drivers;Garson's algorithm;Input dimensions;Network weights;Nonlinear interactions;Prediction performance;Saliency measure;Software cost estimations;Software development effort;Software systems;Algorithms;Costs;Estimation;Project management;Software design;Neural networks
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: Oct-2010
Publisher: Springer Berlin Heidelberg
Source: 6th IFIP WG 12.5 International Conference, Larnaca, Cyprus, 6-7 October, 2010.
Conference: International Conference on Artificial Intelligence Applications and Innovations 
Abstract: Many parameters affect the cost evolution of software projects. In the area of software cost estimation and project management the main challenge is to understand and quantify the effect of these parameters, or 'cost drivers', on the effort expended to develop software systems. This paper aims at investigating the effect of cost attributes on software development effort using empirical databases of completed projects and building Artificial Neural Network (ANN) models to predict effort. Prediction performance of various ANN models with different combinations of inputs is assessed in an attempt to reduce the models' input dimensions. The latter is performed by using one of the most popular saliency measures of network weights, namely Garson's Algorithm. The proposed methodology provides an insight on the interpretation of ANN which may be used for capturing nonlinear interactions between variables in complex software engineering environments.
ISSN: 1868-4238
DOI: 10.1007/978-3-642-16239-8_38
Rights: IFIP International Federation for Information Processing
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

Show full item record


checked on Apr 28, 2018

Page view(s) 50

Last Week
Last month
checked on Oct 13, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.