A neural network approach for web cost estimation

Authors:
Satyananda Reddy;Kvsvn Raju;T. Srinivas;G. Lavanya Devi
Affiliations:
Andhra University, Visakhapatnam, India;Andhra University, Visakhapatnam, India;Bisro Inc.;GITAM University, Visakhapatnam, India
Venue:
SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
Year:
2007

Citing 11
Cited 0

An empirical test of object-based output measurement metrics in a computer aided software engineering (CASE) environment

Journal of Management Information Systems
Machine Learning Approaches to Estimating Software Development Effort

IEEE Transactions on Software Engineering
Estimating software costs

Estimating software costs
Web Development: Estimating Quick-to-Market Software

IEEE Software
Ten Deadly Risks in Internet and Intranet Software Development

IEEE Software
Cost estimation for web applications

Proceedings of the 25th International Conference on Software Engineering
Measuring Functionality and Productivity in Web-Based Applications: A Case Study

METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
A Comparison of Development Effort Estimation Techniques for Web Hypermedia Applications

METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
Using Web Objects for Estimating Software Development Effort for Web Applications

METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Early Web Size Measures and Effort Prediction for Web Costimation

METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Neural Network Approach for Software Cost Estimation

ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02

Quantified Score

Hi-index	0.00

Visualization

Abstract

Accurate cost estimates are an essential element to remain successful in the market, so cost estimation initiatives have been in the center of attention for many firms. Web development projects are certainly different from traditional software development projects and hence, require differently tailored measures for accurate estimation. The use of neural network in estimating software cost by Nasser Tadayon [1] produced accurate results, but it can't be applied to web applications, because they do not take all of the web objects into consideration. In this paper, author explores the use of expert judgment and machine learning techniques using neural network as well as referencing WebMo Estimation model to predict the cost of software. The proposed network improves the accuracy of the estimation as the number of dataset increases with input from expert judgment that affects the learning procedure.