Understanding and Controlling Software Costs
IEEE Transactions on Software Engineering
Robust regression for developing software estimation models
Journal of Systems and Software
Estimating Software Project Effort Using Analogies
IEEE Transactions 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
Comparing case-based reasoning classifiers for predicting high risk software components
Journal of Systems and Software
Software development cost estimation approaches – A survey
Annals of Software Engineering
Applying Reliability Models More Effectively
IEEE Software
Combining techniques to optimize effort predictions in software project management
Journal of Systems and Software
Estimating the development cost of custom software
Information and Management
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
An empirical study of predicting software faults with case-based reasoning
Software Quality Control
The adjusted analogy-based software effort estimation based on similarity distances
Journal of Systems and Software
A Systematic Review of Software Development Cost Estimation Studies
IEEE Transactions on Software Engineering
Reducing biases in individual software effort estimations: a combining approach
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Expert Systems with Applications: An International Journal
Gaussian case-based reasoning for business failure prediction with empirical data in China
Information Sciences: an International Journal
Developing a business failure prediction model via RST, GRA and CBR
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A Study of Improving the Accuracy of Software Effort Estimation Using Linearly Weighted Combinations
COMPSACW '10 Proceedings of the 2010 IEEE 34th Annual Computer Software and Applications Conference Workshops
User preferences based software defect detection algorithms selection using MCDM
Information Sciences: an International Journal
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Since software development has become an essential investment for many organizations recently, both the software industry and academic communities are more and more concerned about a reliable and accurate estimation of the software development effort. This study puts forward six widely used case-based reasoning (CBR) methods with optimized weights derived from the particle swarm optimization (PSO) method to estimate the software effort. Meanwhile, four combination methods are adopted to assemble the results of independent CBR methods. The experiments are carried out using two datasets of software projects from Desharnais dataset and Miyazaki dataset. Experimental results show that different CBR methods can get the best results in different parameters settings, and there is not a best method for the software effort estimation among the six different CBR methods. Currently, combination methods proposed in this study outperform independent methods, and the weighted mean combination (WMC) method can get the better result.