Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
A Simulation Study of the Model Evaluation Criterion MMRE
IEEE Transactions on Software Engineering
Experiments with Analogy-X for Software Cost Estimation
ASWEC '08 Proceedings of the 19th Australian Conference on Software Engineering
Analogy-X: Providing Statistical Inference to Analogy-Based Software Cost Estimation
IEEE Transactions on Software Engineering
StatREC: a graphical user interface tool for visual hypothesis testing of cost prediction models
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Size doesn't matter?: on the value of software size features for effort estimation
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Building a second opinion: learning cross-company data
Proceedings of the 9th International Conference on Predictive Models in Software Engineering
Finding conclusion stability for selecting the best effort predictor in software effort estimation
Automated Software Engineering
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This paper reports on the empirical evaluation of a novel approach called Analogy-X, which is an extension to the classical analogy-based software cost estimation. The Analogy-X approach is a set of procedures that utilize the principles of the Mantel randomization test to provide inferential statistics to Analogy. Our previous studies have clearly demonstrated the novelty and effectiveness of this technique. This paper provides further empirical evaluation of Analogy-X using different kinds of datasets. Our results show that the prediction accuracy of Analogy-X is similar to the one of ANGEL. Analogy-X has the additional advantage of allowing the use of Mantel statistics to select project features and detect abnormal data points, which provides a sound statistical basis for analogy-based systems.