Software engineering metrics and models
Software engineering metrics and models
A Pattern Recognition Approach for Software Engineering Data Analysis
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Dimensionality reduction in software development effort estimation
Journal of Systems and Software
Software Development Productivity of European Space, Military, and Industrial Applications
IEEE Transactions on Software Engineering
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Software Engineering Economics
Software Engineering Economics
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Search Heuristics, Case-based Reasoning And Software Project Effort Prediction
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
Theoretical and Empirical Analysis of ReliefF and RReliefF
Machine Learning
An introduction to variable and feature selection
The Journal of Machine Learning Research
An Evaluation of k-Nearest Neighbour Imputation Using Likert Data
METRICS '04 Proceedings of the Software Metrics, 10th International Symposium
Finding the Right Data for Software Cost Modeling
IEEE Software
Optimal Project Feature Weights in Analogy-Based Cost Estimation: Improvement and Limitations
IEEE Transactions on Software Engineering
Development of a hybrid cost estimation model in an iterative manner
Proceedings of the 28th international conference on Software engineering
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)
An analysis of trends in productivity and cost drivers over years
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
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Managing software development productivity and effort are key issues in software organizations. Identifying the most relevant factors influencing project performance is essential for implementing business strategies by selecting and adjusting proper improvement activities. There is, however, a large number of potential influencing factors. This paper proposes a novel approach for identifying the most relevant factors influencing software development productivity. The method elicits relevant factors by integrating data analysis and expert judgment approaches by means of a multi-criteria decision support technique. Empirical evaluation of the method in an industrial context has indicated that it delivers a different set of factors compared to individual data- and expert-based factor selection methods. Moreover, application of the integrated method significantly improves the performance of effort estimation in terms of accuracy and precision. Finally, the study did not replicate the observation of similar investigations regarding improved estimation performance on the factor sets reduced by a data-based selection method.