Paper Info
Title
Neural Network and Statistical Modeling of Software Development Effort.
Abstract
Many modeling studies that aimed at providing an accurate relationship between the software project effort (or cost) and the involved cost drivers have been conducted for effective management of software projects. However, the derived models are only applicable for a specific project and its variables. In this chapter, we present the use of back-propagation neural network (NN) to model the software development (SD) effort of 18 SD NASA projects based on six cost drivers. The performance of the NN model was also compared with a multi-regression model and other models available in the literature.
Year
DOI
Venue
2012
10.1007/978-81-322-1602-5_21
PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2012)
Keywords
Field
DocType
Neural network,Software development,Effort estimation,Regression
Industrial engineering,Computer science,Cost driver,Software,Statistical model,Artificial intelligence,Software construction,Software development,Software sizing,Machine learning,Goal-Driven Software Development Process,Search-based software engineering
Conference
Volume
ISSN
Citations 
236
2194-5357
0
PageRank 
References 
Authors
0.34
13
3
Name
Order
Citations
PageRank
Ruchi Shukla1152.32
Mukul Shukla241.22
Tshilidzi Marwala331176.83