Early Web size measures and effort prediction for Web costimation

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. It 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.

[1]  Ioannis Stamelos,et al.  A Simulation Tool for Efficient Analogy Based Cost Estimation , 2000, Empirical Software Engineering.

[2]  Michelle Cartwright,et al.  Issues on the Effective Use of CBR Technology for Software Project Prediction , 2001, ICCBR.

[3]  Shari Lawrence Pfleeger,et al.  Software Metrics : A Rigorous and Practical Approach , 1998 .

[4]  Stephen G. MacDonell,et al.  Early Experiences in Measuring Multimedia Systems Development Effort , 1996, Multimedia Technology and Applications.

[5]  D. Ross Jeffery,et al.  A comparative study of two software development cost modeling techniques using multi-organizational and company-specific data , 2000, Inf. Softw. Technol..

[6]  Isabella Wieczorek,et al.  How valuable is company-specific data compared to multi-company data for software cost estimation? , 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

[7]  Lionel C. Briand,et al.  An assessment and comparison of common software cost estimation modeling techniques , 1999, Proceedings of the 1999 International Conference on Software Engineering (IEEE Cat. No.99CB37002).

[8]  Barbara A. Kitchenham,et al.  A Further Empirical Investigation of the Relationship Between MRE and Project Size , 2003, Empirical Software Engineering.

[9]  Barbara Kitchenham,et al.  The MERMAID Approach to software cost estimation , 1990 .

[10]  Barbara A. Kitchenham,et al.  An investigation of analysis techniques for software datasets , 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).

[11]  Norman E. Fenton,et al.  Software Metrics: A Rigorous Approach , 1991 .

[12]  Barbara A. Kitchenham,et al.  A Procedure for Analyzing Unbalanced Datasets , 1998, IEEE Trans. Software Eng..

[13]  Isabella Wieczorek,et al.  Resource Estimation in Software Engineering , 2002 .

[14]  Barbara A. Kitchenham,et al.  Effort estimation using analogy , 1996, Proceedings of IEEE 18th International Conference on Software Engineering.

[15]  Martin J. Shepperd,et al.  Estimating Software Project Effort Using Analogies , 1997, IEEE Trans. Software Eng..

[16]  Rachel Harrison,et al.  Applying measurement principles to improve hypertext authoring , 1999, New Rev. Hypermedia Multim..

[17]  D. Ross Jeffery,et al.  Using public domain metrics to estimate software development effort , 2001, Proceedings Seventh International Software Metrics Symposium.

[18]  Emilia Mendes,et al.  Investigating Early Web Size Measures for Web Cost Estimation , 2005 .

[19]  Martin Shepperd,et al.  Using Simulation to Evaluate Prediction Techniques , 2001 .

[20]  H. E. Dunsmore,et al.  Software engineering metrics and models , 1986 .

[21]  Lionel C. Briand,et al.  Resource modeling in software engineering , 2002 .

[22]  Emilia Mendes,et al.  Measurement and Effort Prediction for Web Applications , 2001, Web Engineering.

[23]  Larry Schroeder,et al.  Understanding Regression Analysis: An Introductory Guide , 2016 .

[24]  Adrian J. C. Cowderoy,et al.  A metrics framework for multimedia creation , 1998, Proceedings Fifth International Software Metrics Symposium. Metrics (Cat. No.98TB100262).

[25]  Ingunn Myrtveit,et al.  Assessing the benefits of imputing ERP projects with missing data , 2001, Proceedings Seventh International Software Metrics Symposium.

[26]  Martin J. Shepperd,et al.  Making inferences with small numbers of training sets , 2002, IEE Proc. Softw..

[27]  Donald J. Reifer.  Ten Deadly Risks in Internet and Intranet Software Development , 2002, IEEE Softw..

[28]  R. S. Pressman,et al.  What a tangled Web we weave [Web engineering] , 2000 .

[29]  Emilia Mendes,et al.  Web Metrics-Estimating Design and Authoring Effort , 2001, IEEE Multim..

[30]  Peter Whalley,et al.  Models of hypertext structure and learning , 1990 .

[31]  Adrian Cowderoy.  Measures of size and complexity for web-site content , 2000 .

[32]  Lionel C. Briand,et al.  A replicated assessment and comparison of common software cost modeling techniques , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[33]  Tim Bray,et al.  Measuring the Web , 1996, World Wide Web J..

[34]  Donald J. Reifer,et al.  Web Development: Estimating Quick-to-Market Software , 2000, IEEE Softw..

[35]  Emilia Mendes,et al.  A comparison of development effort estimation techniques for Web hypermedia applications , 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

[36]  Scott W. Ambler,et al.  Lessons in Agility From Internet-Based Development , 2002, IEEE Softw..