Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Prediction of Software Reliability Using Connectionist Models
IEEE Transactions on Software Engineering
Nonlinear black-box modeling in system identification: a unified overview
Automatica (Journal of IFAC) - Special issue on trends in system identification
Handbook of software reliability engineering
Handbook of software reliability engineering
Time-delay neural networks in damage detection of railway bridges
Advances in Engineering Software
On the neural network approach in software reliability modeling
Journal of Systems and Software
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
AICCSA '01 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications
System Software Reliability (Springer Series in Reliability Engineering)
System Software Reliability (Springer Series in Reliability Engineering)
On-line prediction of software reliability using an evolutionary connectionist model
Journal of Systems and Software
Empirical Assessment of Machine Learning based Software Defect Prediction Techniques
WORDS '05 Proceedings of the 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems
Journal of Systems and Software
IEEE Transactions on Software Engineering
Methodology for long-term prediction of time series
Neurocomputing
Ensembles of ARTMAP-based neural networks: an experimental study
Applied Intelligence
A delay damage model selection algorithm for NARX neural networks
IEEE Transactions on Signal Processing
Computational capabilities of recurrent NARX neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Simultaneous optimization of artificial neural networks for financial forecasting
Applied Intelligence
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
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This paper explores a new approach for predicting software faults by means of NARX neural network. Also, a careful analysis has been carried out to determine the applicability of NARX network in software reliability. The validation of the proposed approach has been performed using two real software failure data sets. Comparison has been made with some existing parametric software reliability models as well as some neural network (Elman net and TDNN) based SRGM. The results computed shows that the proposed approach outperformed the other existing parametric and neural network based software reliability models with a reasonably good predictive accuracy.