1. web-estimation Sánchez Cantón, Juan José Blázquez González, Isaac Alonso Caballero, David

2. Introduction Massive increased use of the Web since 1989 Web application. Classification: – Business to business, Business to customer – Web hypermedia application, Web software application and Web application Survey “Web-based projects” (Cutter Consortium, 2000) – 53% of surveyed delivered projects did not provide the required functionality – 84% of surveyed delivered projects did not meet business needs – 79% of surveyed projects presented schedule delays – 63% of surveyed projects exceeded their budget “Web engineering”: Murugesan & Deshpande, 2001: -“the use of scientific, engineering, and management principles and systematic approaches with the aim of successfully developing, deploying and maintaining high quality Web-based systems and applications”

3. Differences between Web Application and Common Software Application characteristics and availibity – Integration of a higher number of distinct components in Web. – In common, except for a few application domain, there is no need for availability 24/7/365 Technology and architecture: – Web: distributed architecture applications. Network gets importance Quality – Web: main quality drivers are reliability, usability, and security. – Common: time to market takes priority over quality

4. Differences between Web Application and Common Software II Structuring and manteinance – Web: use of hyperlinks to build navigational structures. – Web: maintenance cycles are frequent without specific releases and often take days or even hours. Disciplines, and people involved in development - Web: usually wider range of people involved than common Legal,social and ethical issues -Web: Content can be easier copied and distributed without permission or acknowledgement of copyright and intellectual property rights.

5. Differentiates between Effort Estimation: Web Vs Software There is no standard for sizing Web applications as Web companies vary widely Numerous Web companies are too small to provide a stable environment from which they can develop and maintain their applications and rarely use standards like CCM so the can`t reuse the experience in future projects. Except for the Tukutuku database (Mendes, Mosley, & Counsell, 2003), there are practically no existing benchmark databases that can be used to obtain and then compare Web effort estimates and to benchmark Web projects’ productivity. Despite the proposal of numerous Web development methodologies, there is no single, unifying methodology that entirely captures all the intricacies of Web development projects and project management.

6.  2 points of view: ◦ Dhyani, NG and Bhowmick (2001)

7. ◦ Calero et. AI (2004):classified 385 measures from 40 studies according to a framework called the Web quality model (WQM). This framework is structured according to three orthogonal dimensions.(Web features,Web life-cycle processes and Web quality characteristics:

9.  General purpose: ◦ To predict the effort our development require to carry out the customer requirements (black box metaphor)

10. Effort Estimation Techniques  Expert-based: it is often based on previous experience with developing and/or managing similar Projects. Braingstorming session y CMM – drawbacks: rapidly evolution of technologies, the datas on their own don’t give enough guarantee, Developers and project managers are known for providing optimistic effort estimates To cope with uderestimation, it is provided a formula: E = (o + 4r + p) / 6 o,r,p: optimistic,realistic,pessimistic estimate

11. Effort Estimation Techniques II AlgorithmicTechniques: The inputs are function points, number of lines of source code, number of Web pages, etc. and the effort is the relationship between both sizes. It is translated into a equation (the most popular is WebMo - WQM): E = a·S^b·CostDrivers : a,b: constants S: estimated size of an application CostDrivers: cost drivers

12. Effort Estimation Techniques II  Artificial Intelligence: ◦ In the last decade, it has been used as a complement to the previous two categories. Some examples: fuzzy logic, regression trees, neural networks and cased-based reasoning (CBR) ◦ CBR: similar problems proved similar solutions

13. Effort Estimation Techniques II o Classification and Regression Trees (CARTS): use independent variables (predictors) to build binary trees.

14.  This abstract provide us a light revision of the special characteristics of software projects based on Internet and then define lines of performance that allow to obtain a model of cost estimation obtained from the study of several authors. Those models have main importance on the market, although the most popular are Algorithmic.Techniques yet.

15.  -“Cost Estimation Techniques for Web Projects” Emilia Mendes. University of Auckland, New Zealand  -“Página Web de Almatali” www.almatali.com.ar  -“Página Web de Bournemouth University”. Dan Snell http://www.ecfc.u- net.com/cost/index.htm  -“Web hypermedia cost estimation: further assessment and comparison of cost estimation modelling techniques : Hypermedia and the World Wide Web = Hypermedia and the World Wide Web” MENDES Emilia, COUNSELL Steve y MOSLEY Nile