An empirical validation of software cost estimation models
Communications of the ACM
Synthesizing Statistical Knowledge from Incomplete Mixed-Mode Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Software engineering metrics and models
Software engineering metrics and models
C4.5: programs for machine learning
C4.5: programs for machine learning
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Software Cost Estimation with Incomplete Data
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Using Rough Sets with Heuristics for Feature Selection
Journal of Intelligent Information Systems
An Empirical Study of Analogy-based Software Effort Estimation
Empirical Software Engineering
Estimating Maintenance Effort by Analogy
Empirical Software Engineering
Class-Dependent Discretization for Inductive Learning from Continuous and Mixed-Mode Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparative Study of Cost Estimation Models for Web Hypermedia Applications
Empirical Software Engineering
Dealing with Missing Software Project Data
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Reliability and Validity in Comparative Studies of Software Prediction Models
IEEE Transactions on Software Engineering
Finding the Right Data for Software Cost Modeling
IEEE Software
A comparative study of attribute weighting heuristics for effort estimation by analogy
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A flexible method for software effort estimation by analogy
Empirical Software Engineering
Selecting Best Practices for Effort Estimation
IEEE Transactions on Software Engineering
Feature weighting heuristics for analogy-based effort estimation models
Expert Systems with Applications: An International Journal
Stable rankings for different effort models
Automated Software Engineering
Finding conclusion stability for selecting the best effort predictor in software effort estimation
Automated Software Engineering
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Effort estimation by analogy (EBA) is an established method for software effort estimation. For this paper, we understand EBA as a meta-method which needs to be instantiated and customized at different stages and decision points regarding a specific context. Some example decision problems are related to the selection of the similarity measures, the selection of analogs for adaptation or the weighting and selection of attributes. This paper proposes a decision-centric process model for EBA by generalizing the existing EBA methods. Typical decision-making problems are identified at different stages of the process as part of the model. Some existing solution alternatives of the decision-making problems are then studied. The results of the decision support analysis can be used for better understanding of EBA related techniques and for providing guidelines for implementation and customization of general EBA. An example case of the process model is finally presented.