Web Development Effort Estimation

2011 ◽  
pp. 26-56 ◽  
Author(s):  
Emilia Mendes ◽  
Silvia Abrahão
Keyword(s):  
Multivariate Regression ◽  
Project Managers ◽  
Case Based Reasoning ◽  
Development Effort ◽  
Web Development ◽  
Effort Estimation ◽  
Estimation Techniques ◽  
Classification And Regression ◽  
Case Based

Effort models and effort estimates help project managers allocate resources, control costs and schedule, and improve current practices, leading to projects that are finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial, and very challenging, given that Web projects have short schedules and a highly fluidic scope. Therefore, the objective of this chapter is to introduce the concepts related to Web effort estimation and effort estimation techniques. In addition, this chapter also details and compares, by means of a case study, three effort estimation techniques, chosen for this chapter because they have been to date the ones mostly used for Web effort estimation: Multivariate regression, Case-based reasoning, and Classification and Regression Trees. The case study uses data on industrial Web projects from Spanish Web companies.

Web Effort Estimation Using Classification and Regression Trees

2008 ◽  
pp. 203-239
Author(s):  
Emilia Mendes
Keyword(s):  
Regression Trees ◽  
Classification And Regression Trees ◽  
Project Managers ◽  
Case Based Reasoning ◽  
Effort Estimation ◽  
Real Effort ◽  
Classification And Regression ◽  
Effort Prediction ◽  
Case Based

The use of realistic effort estimates is fundamental to both software and Web project management as they help project managers allocate resources, control costs and schedule, and improve current practices, leading to projects that are finished on time and within budget. Different effort techniques have been used to obtain effort estimates for Web projects. Two—stepwise regression and case-based reasoning—have already been presented in Chapters V and VI respectively. In this chapter we detail a third technique used to obtain effort estimates for Web projects, known as classification and regression trees (CART), that is considered a machine-learning technique. We detail its use by means of a case study where a real effort prediction model based on data from completed industrial Web projects is constructed step by step.

Web Effort Estimation Using Case-Based Reasoning

2008 ◽  
pp. 158-202
Author(s):  
Emilia Mendes
Keyword(s):  
Prediction Accuracy ◽  
Early Stage ◽  
Real Data ◽  
Project Managers ◽  
Case Based Reasoning ◽  
Effort Estimation ◽  
Software Projects ◽  
Software Practitioners ◽  
Case Based

Software practitioners recognise the importance of realistic effort estimates to the successful management of software projects, the Web being no exception. Having realistic estimates at an early stage in a project’s life cycle allow project managers and development organisations to manage resources effectively. Several techniques have been proposed to date to help organisations estimate effort for new projects. One of these is a machine-learning technique called case-based reasoning. This chapter presents a case study that details step by step, using real data from completed industrial Web projects, how to obtain effort estimates using case-based reasoning, and how to assess the prediction accuracy of this technique. The reason to describe the use of case-based reasoning for effort estimation is motivated by its previous use with promising results in Web effort estimation studies.

Introduction to Web Cost Estimation

2008 ◽  
pp. 25-61
Author(s):  
Emilia Mendes
Keyword(s):  
Cost Estimation ◽  
Project Managers ◽  
Web Development ◽  
Effort Estimation ◽  
Estimation Techniques ◽  
Current Practices

Software effort models and effort estimates help project managers allocate resources, control costs, and schedule and improve current practices, which in theory should allow projects to be finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial and very challenging given that Web projects have short schedules and a highly fluidic scope. Therefore, the objective of this chapter is to introduce the concepts related to Web effort estimation and effort estimation techniques. These concepts will be used in further chapters.

Web Effort Estimation Usiing Regression Analysis

2008 ◽  
pp. 120-157
Author(s):  
Emilia Mendes
Keyword(s):  
Regression Analysis ◽  
Prediction Model ◽  
Statistical Technique ◽  
Project Managers ◽  
Web Development ◽  
Effort Estimation ◽  
Model Based ◽  
Real Effort ◽  
Effort Prediction

Software effort models and estimates help project managers allocate resources, control costs, and schedule and improve current practices, leading to projects that are finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial, and very challenging, given that Web projects have short schedules and a highly fluidic scope. Therefore, this chapter presents a case study where a real effort prediction model based on data from completed industrial Web projects is constructed step by step using a statistical technique called regression analysis.

scholarly journals The Application of Case-Based Reasoning to Estimation of Software Development Effort

2012 ◽  
pp. 239-244
Author(s):  
Ekbal Rashid ◽  
Vandana Bhattacherjee ◽  
Srikanta Patnaik
Keyword(s):  
Software Engineering ◽  
Cost Estimation ◽  
Expert Advice ◽  
Case Based Reasoning ◽  
Development Effort ◽  
Effort Estimation ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Software Development Effort ◽  
Case Based

Accurate project effort estimation is an important goal for the software engineering community. Till date most work has focused upon building algorithmic models of effort estimation for example COCOMO. We describe an alternative approach to estimation based upon the use of analogy. The objective is to estimate the development effort of student programs based on the values of certain attributes. We have developed a case based reasoning model and have validated it upon student data. Due to the nature of the software engineering domain, it is important that software cost estimation models should be able to deal with imprecision and uncertainty associated with such values. It is to serve this purpose that we propose our case based model for software cost estimation. We feel that case based models are particularly useful when it is difficult to define concrete rules about a problem domain in addition to this, expert advice may be used to supplement the existing stored knowledge.

Toward More Effective Transportation Applications of Computational Intelligence Paradigms

2003 ◽  
Vol 1836 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Adel W. Sadek ◽  
Gary Spring ◽  
Brian L. Smith
Keyword(s):  
Computational Intelligence ◽  
Design Parameters ◽  
Case Based Reasoning ◽  
Development Effort ◽  
Processing Technologies ◽  
Real Time Traffic ◽  
Need To Evaluate ◽  
Transportation Applications ◽  
Case Based

While information technology has facilitated the collection of neverbefore-seen quantities of data, these data have not always provided the information needed by transportation professionals to support sound decision making. Computational intelligence (CI) has great potential to support the needs of transportation professionals. CI is a result of synergy among information processing technologies such as artificial neural networks (ANNs), fuzzy sets, and genetic algorithms. As the number of CI applications to transportation problems grows, so does the need to evaluate these systems. The issue of validating and evaluating transportation CI applications is addressed. A case study that evaluates the effectiveness of two CI paradigms, case-based reasoning and ANNs, for estimating the benefits of real-time traffic diversion is presented. The case study illustrates the need for regarding validation and evaluation as a part of the development effort and the need for tuning the design parameters of CI paradigms.

Examining the Feasibility of a Case-Based Reasoning Model for Software Effort Estimation

MIS Quarterly ◽  
1992 ◽  
Vol 16 (2) ◽  
pp. 155 ◽  
Author(s):  
Tridas Mukhopadhyay ◽  
Steven S. Vicinanza ◽  
Michael J. Prietula
Keyword(s):  
Case Based Reasoning ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Case Based

Integrating fuzzy case-based reasoning, parametric and feature-based cost estimation methods for machining process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fentahun Moges Kasie ◽  
Glen Bright
Keyword(s):  
Cost Estimation ◽  
Intelligent System ◽  
Machining Process ◽  
Estimation Methods ◽  
Case Based Reasoning ◽  
Cost Estimates ◽  
Content Type ◽  
Estimation Techniques ◽  
Feature Based ◽  
Case Based

Purpose This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers. Design/methodology/approach The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. Findings The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques. Research limitations/implications The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations. Originality/value Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

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