Neural network and statistical modeling of software development effort

Ruchi Shukla, Mukul Shukla, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 effectivemanagement 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.

Original languageEnglish
Title of host publication2nd International Conference on Soft Computing for Problem Solving, SocProS 2012, Proceedings
EditorsB.V. Babu, Atulya Nagar, Jagdish Chand Bansal, Millie Pant, Kusum Deep, Kanad Ray, Umesh Gupta
PublisherSpringer Verlag
Pages189-198
Number of pages10
ISBN (Electronic)9788132216018
DOIs
Publication statusPublished - 2014
Event2nd International Conference on Soft Computing for Problem Solving, SocProS 2012 - Jaipur, India
Duration: 28 Dec 201230 Dec 2012

Publication series

NameAdvances in Intelligent Systems and Computing
Volume236
ISSN (Print)2194-5357

Conference

Conference2nd International Conference on Soft Computing for Problem Solving, SocProS 2012
Country/TerritoryIndia
CityJaipur
Period28/12/1230/12/12

Keywords

  • Effort estimation
  • Neural network
  • Regression
  • Software development

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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