A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
A linear regression model using triangular fuzzy number coefficients
Fuzzy Sets and Systems
Software cost estimation with fuzzy models
ACM SIGAPP Applied Computing Review
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A Comparative Study of Cost Estimation Models for Web Hypermedia Applications
Empirical Software Engineering
Do adaptation rules improve web cost estimation?
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
A Replicated Assessment of the Use of Adaptation Rules to Improve Web Cost Estimation
ISESE '03 Proceedings of the 2003 International Symposium on Empirical Software Engineering
A Simulation Study of the Model Evaluation Criterion MMRE
IEEE Transactions on Software Engineering
Realism in Assessment of Effort Estimation Uncertainty: It Matters How You Ask
IEEE Transactions on Software Engineering
ISESE '04 Proceedings of the 2004 International Symposium on Empirical Software Engineering
Using Grey Relational Analysis to Predict Software Effort with Small Data Sets
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
IEEE Transactions on Software Engineering
Fuzzy risk analysis based on measures of similarity between interval-valued fuzzy numbers
Computers & Mathematics with Applications
A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
Expert Systems with Applications: An International Journal
Fuzzy risk analysis based on interval-valued fuzzy numbers
Expert Systems with Applications: An International Journal
Fuzzy grey relational analysis for software effort estimation
Empirical Software Engineering
Software project similarity measurement based on fuzzy C-means
ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
IEEE Transactions on Fuzzy Systems
Recent methods for software effort estimation by analogy
ACM SIGSOFT Software Engineering Notes
Towards an early software estimation using log-linear regression and a multilayer perceptron model
Journal of Systems and Software
Modeling optimal release policy under fuzzy paradigm in imperfect debugging environment
Information and Software Technology
Grey relational effort analysis technique using robust regression methods for individual projects
International Journal of Computational Intelligence Studies
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Background: Early stage software effort estimation is a crucial task for project bedding and feasibility studies. Since collected data during the early stages of a software development lifecycle is always imprecise and uncertain, it is very hard to deliver accurate estimates. Analogy-based estimation, which is one of the popular estimation methods, is rarely used during the early stage of a project because of uncertainty associated with attribute measurement and data availability. Aims: We have integrated analogy-based estimation with Fuzzy numbers in order to improve the performance of software project effort estimation during the early stages of a software development lifecycle, using all available early data. Particularly, this paper proposes a new software project similarity measure and a new adaptation technique based on Fuzzy numbers. Method: Empirical evaluations with Jack-knifing procedure have been carried out using five benchmark data sets of software projects, namely, ISBSG, Desharnais, Kemerer, Albrecht and COCOMO, and results are reported. The results are compared to those obtained by methods employed in the literature using case-based reasoning and stepwise regression. Results: In all data sets the empirical evaluations have shown that the proposed similarity measure and adaptation techniques method were able to significantly improve the performance of analogy-based estimation during the early stages of software development. The results have also shown that the proposed method outperforms some well know estimation techniques such as case-based reasoning and stepwise regression. Conclusions: It is concluded that the proposed estimation model could form a useful approach for early stage estimation especially when data is almost uncertain.