@inproceedings{87380e2b87e243f8a994c1801cec38af,
title = "Dynamic software maintenance effort estimation modeling using neural network, rule engine and multi-regression approach",
abstract = "The dynamic business environment of software projects typically involves a large number of technical, demographic and environmental variables. This coupled with imprecise data on human, management and dynamic factors makes the objective estimation of software development and maintenance effort a very challenging task. Currently, no single estimation model or tool has been able to coherently integrate and realistically address the above problems. This paper presents a multi-fold modeling approach using neural network, rule engine and multi-regression for dynamic software maintenance effort estimation. The system dynamics modeling tool developed using quantitative and qualitative inputs from real life projects is able to successfully simulate and validate the dynamic behavior of a software maintenance estimation system.",
keywords = "Software maintenance, effort estimation, neural network, regression, system dynamics",
author = "Ruchi Shukla and Mukul Shukla and Misra, {A. K.} and T. Marwala and Clarke, {W. A.}",
year = "2012",
doi = "10.1007/978-3-642-31128-4_12",
language = "English",
isbn = "9783642311277",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 4",
pages = "157--169",
booktitle = "Computational Science and Its Applications - 12th International Conference, ICCSA 2012, Proceedings",
edition = "PART 4",
note = "12th International Conference on Computational Science and Its Applications, ICCSA 2012 ; Conference date: 18-06-2012 Through 21-06-2012",
}