Function Points Analysis: An Empirical Study of Its Measurement Processes
IEEE Transactions on Software Engineering
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
Software Engineering Economics
Software Engineering Economics
An Empirical Study of Analogy-based Software Effort Estimation
Empirical Software Engineering
A Simulation Tool for Efficient Analogy Based Cost Estimation
Empirical Software Engineering
Estimating Maintenance Effort by Analogy
Empirical Software Engineering
A Comparative Study of Cost Estimation Models for Web Hypermedia Applications
Empirical Software Engineering
A Simulation Study of the Model Evaluation Criterion MMRE
IEEE Transactions on Software Engineering
Software effort estimation by analogy and "regression toward the mean"
Journal of Systems and Software - Special issue: Best papers on Software Engineering from the SEKE'01 Conference
Further Comparison of Cross-Company and Within-Company Effort Estimation Models for Web Applications
METRICS '04 Proceedings of the Software Metrics, 10th International Symposium
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
The adjusted analogy-based software effort estimation based on similarity distances
Journal of Systems and Software
A flexible method for software effort estimation by analogy
Empirical Software Engineering
A Systematic Review of Software Development Cost Estimation Studies
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Improving analogy-based software cost estimation by a resampling method
Information and Software Technology
Replicating studies on cross- vs single-company effort models using the ISBSG Database
Empirical Software Engineering
Comparing cost prediction models by resampling techniques
Journal of Systems and Software
The Sinkhorn-Knopp Algorithm: Convergence and Applications
SIAM Journal on Matrix Analysis and Applications
A study of project selection and feature weighting for analogy based software cost estimation
Journal of Systems and Software
Why comparative effort prediction studies may be invalid
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Fuzzy grey relational analysis for software effort estimation
Empirical Software Engineering
An empirical analysis of linear adaptation techniques for case-based prediction
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Adaptive ridge regression system for software cost estimating on multi-collinear datasets
Journal of Systems and Software
A replicated assessment and comparison of adaptation techniques for analogy-based effort estimation
Empirical Software Engineering
Exploiting the Essential Assumptions of Analogy-Based Effort Estimation
IEEE Transactions on Software Engineering
Hi-index | 0.00 |
A large variety of methods has been proposed in the literature about Software Cost Estimation, in order to increase accuracy when predicting the effort of developing new projects. Estimation by Analogy is one of the most studied techniques in this area the last 20 years. The popularity of the methodology can be explained by its accordance to human problem thinking and solving, the straightforward interpretation and the usually comparable accuracy to other methodologies. Furthermore, the methodology is essentially a special case of non-parametric regression, easily implementable and free of theoretical assumptions, based on the notion of "similarity" which is used to define "neighbors". All of these reasons led us to study the technique in more depth, considering alternative ways to exploit similarities, in order to assign weights to neighbors. In this paper, our aim is to review the existing weighting practices and explore some new iterative procedures from matrix algebra, which transform a similarity matrix to a bi-stochastic matrix (a matrix with row and column summing to 1). Specifically, we apply algorithms such as the Sinkhorn--Knopp and the Bregmanian Bi-Stochastication to similarity matrices of well-known software cost datasets in order to derive matrices that assign weights to the neighbors used for effort estimates. We investigate the sensitivity of the results with respect to the similarity function, focusing on a Gaussian kernel matrix with a tuning parameter. The promising results show that the new methods deserve a more thorough investigation and can be considered as generalization of the Estimation by Analogy method.