An empirical validation of software cost estimation models
Communications of the ACM
CADET: a case-based synthesis tool for engineering design
International Journal of Expert Systems - Special issue on case-based reasoning
Effort estimation using analogy
Proceedings of the 18th international conference on Software engineering
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
A Controlled Experiment to Assess the Benefits of Estimating with Analogy and Regression Models
IEEE Transactions on Software Engineering
A replicated assessment and comparison of common software cost modeling techniques
Proceedings of the 22nd international conference on Software engineering
An investigation of machine learning based prediction systems
Journal of Systems and Software - Special issue on empirical studies of software development and evolution
Software Engineering Economics
Software Engineering Economics
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ICSM '97 Proceedings of the International Conference on Software Maintenance
Cost Estimation of Software Projects through Case Base Reasoning
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
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METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
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METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
A General Empirical Solution to the Macro Software Sizing and Estimating Problem
IEEE Transactions on Software Engineering
Ensemble missing data techniques for software effort prediction
Intelligent Data Analysis
Predicting software project effort: A grey relational analysis based method
Expert Systems with Applications: An International Journal
PPSS: CBR system for ERP project pre-planning
AIS'04 Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems
Investigating effort prediction of web-based applications using CBR on the ISBSG dataset
EASE'10 Proceedings of the 14th international conference on Evaluation and Assessment in Software Engineering
Forecasting software development project characteristics using meta-modeling
Proceedings of the 9th Central & Eastern European Software Engineering Conference in Russia
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This paper explores some of the practical issues associated with the use of case-based reasoning (CBR) or estimation by analogy for software project effort prediction. Different research teams have reported varying experiences with this technology. We take the view that the problems hindering the effective use of CBR technology are twofold. First, the underlying characteristics of the datasets play a major role in determining which prediction technique is likely to be most effective. Second, when CBR is that technique, we find that configuring a CBR system can also have a significant impact upon predictive capabilities. In this paper we examine the performance of CBR when applied to various datasets using stepwise regression (SWR) as a benchmark. We also explore the impact of the choice of number of analogies and the size of the training dataset when making predictions.