Software engineering metrics and models
Software engineering metrics and models
Machine Learning Approaches to Estimating Software Development Effort
IEEE Transactions on Software Engineering
A replicated assessment and comparison of common software cost modeling techniques
Proceedings of the 22nd international conference on Software engineering
Software cost estimation with fuzzy models
ACM SIGAPP Applied Computing Review
ACM SIGSOFT Software Engineering Notes
A Discipline for Software Engineering
A Discipline for Software Engineering
Software Engineering Economics
Software Engineering Economics
Computational intelligence as an emerging paradigm of software engineering
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Three great challenges for half-century-old computer science
Journal of the ACM (JACM)
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
Estimating Software Project Effort by Analogy Based on Linguistic Values
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
An Empirical Validation of the Relationship Between the Magnitude of Relative Error and Project Size
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
A Neuro-Fuzzy Model for Software Cost Estimation
QSIC '03 Proceedings of the Third International Conference on Quality Software
A Simulation Study of the Model Evaluation Criterion MMRE
IEEE Transactions on Software Engineering
Improved estimation of software project effort using multiple additive regression trees
Expert Systems with Applications: An International Journal
Improving effort estimation by voting software estimation models
Advances in Software Engineering
Multi-variate principal component analysis of software maintenance effort drivers
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
Towards an early software estimation using log-linear regression and a multilayer perceptron model
Journal of Systems and Software
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Regression analysis to generate predictive equations for software development effort estimation has recently been complemented by analyses using less common methods such as fuzzy logic models. On the other hand, unless engineers have the capabilities provided by personal training, they cannot properly support their teams or consistently and reliably produce quality products. In this paper, an investigation aimed to compare personal Fuzzy Logic Models (FLM) with a Linear Regression Model (LRM) is presented. The evaluation criteria were based mainly upon the magnitude of error relative to the estimate (MER) as well as to the mean of MER (MMER). One hundred five small programs were developed by thirty programmers. From these programs, three FLM were generated to estimate the effort in the development of twenty programs by seven programmers. Both the verification and validation of the models were made. Results show a slightly better predictive accuracy amongst FLM and LRM for estimating the development effort at personal level when small programs are developed.