An empirical validation of software cost estimation models
Communications of the ACM
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
Calibrating the COCOMO II post-architecture model
Proceedings of the 20th international conference on Software engineering
Explaining the cost of European space and military projects
Proceedings of the 21st international conference on Software engineering
Bayesian Analysis of Empirical Software Engineering Cost Models
IEEE Transactions on Software Engineering
Empirical Data Modeling in Software Engineering Using Radial Basis Functions
IEEE Transactions on Software Engineering
Software cost estimation with fuzzy models
ACM SIGAPP Applied Computing Review
Fuzzy Modeling for Control
Software Engineering Economics
Software Engineering Economics
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
A meta-model for software development resource expenditures
ICSE '81 Proceedings of the 5th international conference on Software engineering
Software Cost Estimation: an experimental study of model performances
Software Cost Estimation: an experimental study of model performances
The effects of case tools on software development effort
The effects of case tools on software development effort
COCOMO-Based Effort Estimation for Iterative and Incremental Software Development
Software Quality Control
Validation methods for calibrating software effort models
Proceedings of the 27th international conference on Software engineering
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Bidding for contracts depends mainly on estimated costs of a given project, which makes an accurate estimation of effort and time required very important with great impact on budget computation and project success. Inaccurate estimates are likely lead to one or all of the following negative outcomes: failure in making a profit, increased probability of incomplete project and delay of project delivery date. In this paper, we provide a comparison between models developed for software cost estimation using particle swarm optimisation (PSO) algorithm, fuzzy logic (FL), and well-known cost estimation models such as Halstead, Walston-Felix, Bailey-Basili and Doty models. The performance of the developed models is evaluated based on the mean magnitude of relative error (MMRE) for NASA software projects.