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
An experimental study of individual subjective effort estimation and combinations of the estimates
Proceedings of the 20th international conference 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 Metrics: Measurement for Software Process Improvement
Software Metrics: Measurement for Software Process Improvement
Software Engineering Economics
Software Engineering Economics
Empirical Software Engineering
On Building Prediction Systems for Software Engineers
Empirical Software Engineering
An empirical study of maintenance and development estimation accuracy
Journal of Systems and Software
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
An Investigation of Analysis Techniques for Software Datasets
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Using Simulation to Evaluate Prediction Techniques
METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
Using Public Domain Metrics To Estimate Software Development Effort
METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
Controlling Software Projects: Management, Measurement, and Estimates
Controlling Software Projects: Management, Measurement, and Estimates
Effort estimation of use cases for incremental large-scale software development
Proceedings of the 27th international conference on Software engineering
A Systematic Review of Software Development Cost Estimation Studies
IEEE Transactions on Software Engineering
Software project economics: a roadmap
FOSE '07 2007 Future of Software Engineering
Mining software repositories for comprehensible software fault prediction models
Journal of Systems and Software
Combining probabilistic models for explanatory productivity estimation
Information and Software Technology
An empirical validation of a neural network model for software effort estimation
Expert Systems with Applications: An International Journal
Reducing biases in individual software effort estimations: a combining approach
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
A study of project selection and feature weighting for analogy based software cost estimation
Journal of Systems and Software
Empirical Software Engineering
Combining techniques for software quality classification: An integrated decision network approach
Expert Systems with Applications: An International Journal
Systematic literature review of machine learning based software development effort estimation models
Information and Software Technology
Information Sciences: an International Journal
Computational intelligence in software cost estimation: an emerging paradigm
ACM SIGSOFT Software Engineering Notes
A parametric emergency response project management system
International Journal of Advanced Intelligence Paradigms
Expert Systems with Applications: An International Journal
Functional Link Artificial Neural Networks for Software Cost Estimation
International Journal of Applied Evolutionary Computation
The Journal of Supercomputing
On the value of outlier elimination on software effort estimation research
Empirical Software Engineering
Information and Software Technology
LMES: A localized multi-estimator model to estimate software development effort
Engineering Applications of Artificial Intelligence
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This paper tackles two questions related to software effort prediction. First, is it valuable to combine prediction techniques? Second, if so, how? Many commentators have suggested the use of more than one technique in order to support effort prediction, but to date there has been little or no empirical investigation to support this recommendation. Our analysis of effort data from a medical records information system reveals that there is little, or even negative, covariance between the accuracy of our three chosen prediction techniques, namely, expert judgment, least squares regression and case-based reasoning. This indicates that when one technique predicts poorly, one or both of the others tends to perform significantly better. This is a particularly striking result given the relative homogeneity of our data set. Consequently, searching for the single "best" technique, at least in this case, leads to a sub-optimal prediction strategy. The challenge then becomes one of identifying a means of determining a priori which prediction technique to use. Unfortunately, despite using a range of techniques including rule induction, we were unable to identify any simple mechanism for doing so. Nevertheless, we believe this remains an important research goal.