Web Cost Estimation and Productivity Benchmarking
Software Engineering
A neural network approach for web cost estimation
SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
Applying support vector regression for web effort estimation using a cross-company dataset
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Using Support Vector Regression for Web Development Effort Estimation
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
The use of a Bayesian network for web effort estimation
ICWE'07 Proceedings of the 7th international conference on Web engineering
A replicated study comparing web effort estimation techniques
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
How effective is Tabu search to configure support vector regression for effort estimation?
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
A COSMIC-FFP approach to predict web application development effort
Journal of Web Engineering
Building an expert-based web effort estimation model using bayesian networks
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
Predicting web development effort using a bayesian network
EASE'07 Proceedings of the 11th international conference on Evaluation and Assessment in Software Engineering
The Automatic Evaluation of Website Metrics and State
International Journal of Web-Based Learning and Teaching Technologies
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Size measures for Web costimation proposed in the literature are invariably related to implemented Web applications. Even when targeted at measuring functionality based on function point analysis, researchers only considered the final Web application, rather than requirements documentation generated using any existing Web development methods. This makes their usefulness as early effort predictors questionable.In addition, it is believed that company-specific data provide a better basis for accurate estimates. Many software engineering researchers have compared the accuracy of company-specific data with multiorganisation databases. However the datasets employed were comprised of data from conventional applications. To date no similar comparison has been adopted for Web project datasets.As a result, this paper has two objectives: The first is to present a survey where early size measures for Web costimation were identified using data collected from 133 Web companies worldwide. All companies included in the survey used Web forms to give quotes on Web development projects, based on gathered size measures. The second is to compare the prediction accuracy of a Web company-specific data with data from a multiorganisation database. Both datasets were obtained via Web forms, used as part of a research project called Tukutuku. Our results show that best predictions were obtained for company-specific dataset, for the two estimation techniques employed.