Estimation of information systems development efforts: a pilot study
Information and Management
Reliability of function points measurement: a field experiment
Communications of the ACM
Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Software Engineering Economics
Software Engineering Economics
Software Development Cost Estimation Using Function Points
IEEE Transactions on Software Engineering
Combining techniques to optimize effort predictions in software project management
Journal of Systems and Software
Preliminary Data Analysis Methods in Software Estimation
Software Quality Control
Reliability and Validity in Comparative Studies of Software Prediction Models
IEEE Transactions on Software Engineering
Journal of Management Information Systems - Special section: Data mining
Performance evaluation of neural network decision models
Journal of Management Information Systems - Special section: Strategic and competitive information systems
Software Effort, Quality, and Cycle Time: A Study of CMM Level 5 Projects
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Improved estimation of software project effort using multiple additive regression trees
Expert Systems with Applications: An International Journal
Why comparative effort prediction studies may be invalid
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Improving effort estimation by voting software estimation models
Advances in Software Engineering
Handling missing data in software effort prediction with naive Bayes and EM algorithm
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
ACM SIGSOFT Software Engineering Notes
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Expert Systems with Applications: An International Journal
Systematic literature review of machine learning based software development effort estimation models
Information and Software Technology
Information and Software Technology
Empirical Software Engineering
Towards an early software estimation using log-linear regression and a multilayer perceptron model
Journal of Systems and Software
Probabilistic size proxy for software effort prediction: A framework
Information and Software Technology
Predicting open IOS adoption in SMEs: An integrated SEM-neural network approach
Expert Systems with Applications: An International Journal
Data stream mining for predicting software build outcomes using source code metrics
Information and Software Technology
Hi-index | 12.06 |
As software becomes more complex and its scope dramatically increases, the importance of research on developing methods for estimating software development efforts has perpetually increased. Such accurate estimation has a prominent impact on the success of projects. Out of the numerous methods for estimating software development efforts that have been proposed, line of code (LOC)-based constructive cost model (COCOMO), function point-based regression model (FP), neural network model (NN), and case-based reasoning (CBR) are among the most popular models. Recent research has tended to focus on the use of function points (FPs) in estimating the software development efforts, however, a precise estimation should not only consider the FPs, which represent the size of the software, but should also include various elements of the development environment for its estimation. Therefore, this study is designed to analyze the FPs and the development environments of recent software development cases. The primary purpose of this study is to propose a precise method of estimation that takes into account and places emphasis on the various software development elements. This research proposes and evaluates a neural network-based software development estimation model.