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
2013 ◽  
Vol 16 (3) ◽  
Author(s):  
Katia Cristina A. Damaceno Borges ◽  
Iris Fabiana De Barcelos Tronto ◽  
Renato De Aquino Lopes ◽  
José Demisio Simões da Silva

Software effort estimates is an important part of software development work and provides essential input to project feasibility analyses, bidding, budgeting and planning. Analogy-based estimates models emerge as a promising approach, with comparable accuracy to arithmetic methods, and it is potentially easier to understand and apply. Studies show all the models are sensitive to the quality and availability data, thus requiring a systematic data treatment. In this paper, it is proposed a data pre-processing method for use in software effort estimate. The results of it on applying on applying Case Based Reasoning - CBR that enables us to enhance the precision of the estimates.


Author(s):  
Emilia Mendes ◽  
Silvia Abrahão

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.


Author(s):  
Emilia Mendes

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.


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