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Neural network for software reliability analysis of dynamically weighted NHPP growth models with imperfect debugging
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/qre.1216openalex-snapshot
Adaboosting‐based dynamic weighted combination of software reliability growth models
inferredcites →https://doi.org/10.1002/qre.1301openalex-snapshot
Discrete Nonhomogeneous Poisson Process Software Reliability Growth Models Based on Test Coverage
inferredcites →https://doi.org/10.1002/qre.827openalex-snapshot
A study of the modeling and analysis of software fault‐detection and fault‐correction processes
inferredcites →https://doi.org/10.1002/stvr.1575openalex-snapshot
Assessing and generating test sets in terms of behavioural adequacy
inferredcites →https://doi.org/10.1002/stvr.1600openalex-snapshot
A general modeling and analysis framework for software fault detection and correction process
inferredcites →https://doi.org/10.1002/stvr.391openalex-snapshot
The determination of optimal software release times at different confidence levels with consideration of learning effects
inferredcites →https://doi.org/10.1002/stvr.4370050305openalex-snapshot
Evaluating the reliability of the software of a switching system with a multi‐variable model
inferredcites →https://doi.org/10.1007/978-3-642-30223-7_87openalex-snapshot
Brief Introduction of Back Propagation (BP) Neural Network Algorithm and Its Improvement
inferredcites →https://doi.org/10.1016/0893-6080(92)90008-7openalex-snapshot
Improving the convergence of the back-propagation algorithm
inferredcites →https://doi.org/10.1016/j.apm.2015.04.036openalex-snapshot
On the conditional and partial trade credit policy with capital constraints: A Stackelberg model
inferredcites →https://doi.org/10.1016/j.asoc.2012.08.015openalex-snapshot
Hybrid intelligent systems for predicting software reliability
inferredcites →https://doi.org/10.1016/j.asoc.2014.04.012openalex-snapshot
Robust feedforward and recurrent neural network based dynamic weighted combination models for software reliability prediction
inferredcites →https://doi.org/10.1016/j.eswa.2007.12.029openalex-snapshot
Predicting software reliability with neural network ensembles
inferredcites →https://doi.org/10.1016/j.eswa.2015.01.043openalex-snapshot
Neuro-genetic approach on logistic model based software reliability prediction
inferredcites →https://doi.org/10.1016/j.jss.2004.08.023openalex-snapshot
On-line prediction of software reliability using an evolutionary connectionist model
inferredcites →https://doi.org/10.1016/j.jss.2006.06.017openalex-snapshot
Neural-network-based approaches for software reliability estimation using dynamic weighted combinational models
inferredcites →https://doi.org/10.1016/j.jss.2007.05.005openalex-snapshot
Software reliability prediction by soft computing techniques
inferredcites →https://doi.org/10.1016/j.ress.2006.04.007openalex-snapshot
Robust recurrent neural network modeling for software fault detection and correction prediction
inferredcites →https://doi.org/10.1016/s0164-1212(01)00027-9openalex-snapshot
On the neural network approach in software reliability modeling
inferredcites →https://doi.org/10.1016/s0164-1212(99)00065-5openalex-snapshot
Software reliability prediction incorporating information from a similar project
inferredcites →https://doi.org/10.1016/s0898-1221(03)90117-9openalex-snapshot
A study of the connectionist models for software reliability prediction
inferredcites →https://doi.org/10.1109/24.784276openalex-snapshot
A general imperfect-software-debugging model with S-shaped fault-detection rate
inferredcites →https://doi.org/10.1109/24.799900openalex-snapshot
Comparison of software-reliability-growth predictions: neural networks vs parametric-recalibration
inferredcites →https://doi.org/10.1109/32.148475openalex-snapshot
Prediction of software reliability using connectionist models
inferredcites →https://doi.org/10.1109/34.107014openalex-snapshot
On the problem of local minima in backpropagation
inferredcites →https://doi.org/10.1109/52.143107openalex-snapshot
Using neural networks in reliability prediction
inferredcites →https://doi.org/10.1109/fose.2007.24openalex-snapshot
Software Reliability Engineering: A Roadmap
inferredcites →https://doi.org/10.1109/tr.1979.5220566openalex-snapshot
Time-Dependent Error-Detection Rate Model for Software Reliability and Other Performance Measures
inferredcites →https://doi.org/10.1109/tr.1983.5221735openalex-snapshot
S-Shaped Reliability Growth Modeling for Software Error Detection
inferredcites →https://doi.org/10.1109/tse.1975.6312856openalex-snapshot
A theory of software reliability and its application
inferredcites →https://doi.org/10.1109/tse.1985.232177openalex-snapshot
Software Reliability Models: Assumptions, Limitations, and Applicability
inferredcites →https://doi.org/10.1109/tse.1985.232179openalex-snapshot
Software Reliability Growth Modeling: Models and Applications
inferredcites →https://doi.org/10.1109/tse.2003.1183936openalex-snapshot
A unified scheme of some nonhomogenous poisson process models for software reliability estimation
inferredcites →https://doi.org/10.1142/s0218539306002094openalex-snapshot
ON USING SOFT COMPUTING TECHNIQUES IN SOFTWARE RELIABILITY ENGINEERING
inferredcites →https://doi.org/10.1142/s0218539311004135openalex-snapshot
ENHANCING SOFTWARE RELIABILITY OF A COMPLEX SOFTWARE SYSTEM ARCHITECTURE USING ARTIFICIAL NEURAL-NETWORKS ENSEMBLE
inferredcites →https://doi.org/10.1142/s0218539314500089openalex-snapshot
AN NHPP SOFTWARE RELIABILITY GROWTH MODEL WITH IMPERFECT DEBUGGING AND ERROR GENERATION
inferredcites →https://doi.org/10.1504/ijrs.2013.057423openalex-snapshot
An S-shaped software reliability model with imperfect debugging and improved testing learning process
inferredcites →https://doi.org/10.4304/jsw.7.6.1296-1306openalex-snapshot
A Detailed Study of NHPP Software Reliability Models (Invited Paper)
inferredcites →https://doi.org/10.5120/7451-0534openalex-snapshot
Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/qre.3220openalex-snapshot
Software reliability prediction: A survey
inferred← citeshttps://doi.org/10.1002/stvr.1710openalex-snapshot
An improved software reliability prediction model by using high precision error iterative analysis method
inferred← citeshttps://doi.org/10.1002/stvr.1765openalex-snapshot
Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation
inferred← citeshttps://doi.org/10.1002/stvr.1895openalex-snapshot
Software Reliability Prediction by Adaptive Gated Recurrent Unit‐Based Encoder‐Decoder Model With Ensemble Empirical Mode Decomposition
inferred← citeshttps://doi.org/10.1002/stvr.70028openalex-snapshot
DSC‐SRGM: A Deep Synthetic Cross‐Project Software Reliability Growth Model
inferred← citeshttps://doi.org/10.1007/s10479-023-05240-6openalex-snapshot
Stochastic debugging based reliability growth models for Open Source Software project
inferred← citeshttps://doi.org/10.1007/s11219-025-09718-3openalex-snapshot
Predictive framework of software reliability analysis under multiple change points and imperfect debugging
inferred← citeshttps://doi.org/10.1007/s11270-023-06117-xopenalex-snapshot
Water quality prediction based on IGRA-ISSA-LSTM model
inferred← citeshttps://doi.org/10.1016/j.anucene.2020.107589openalex-snapshot
Research on the software reliability quantitative evaluation of nuclear power plant digital control system based on non-homogeneous poisson process model
inferred← citeshttps://doi.org/10.1016/j.heliyon.2019.e02082openalex-snapshot
A novel approach of NPSO on dynamic weighted NHPP model for software reliability analysis with additional fault introduction parameter
inferred← citeshttps://doi.org/10.1016/j.ress.2020.107097openalex-snapshot
Power–law nonhomogeneous Poisson process with a mixture of latent common shape parameters
inferred← citeshttps://doi.org/10.1109/icct-pacific63901.2025.11012813openalex-snapshot
Noise Analysis for OSS Stochastic Differential Equation Model as Training Data of Deep Learning
inferred← citeshttps://doi.org/10.1109/phm-shanghai49105.2020.9280964openalex-snapshot
Change Point Reliability Modelling for Open Source Software with Masked Data Using Expectation Maximization Algorithm
inferred← citeshttps://doi.org/10.1109/prdc63035.2024.00044openalex-snapshot
An Alternative Boosting-based Software Reliability Prediction Method
inferred← citeshttps://doi.org/10.1109/ubmk52708.2021.9558998openalex-snapshot
Ensemble and Cross-Project Software Reliability Growth Models for Safety-Critical Systems
inferred← citeshttps://doi.org/10.1145/3477535openalex-snapshot
On the Reproducibility and Replicability of Deep Learning in Software Engineering
inferred← citeshttps://doi.org/10.1177/1748006x19844784openalex-snapshot
A neuro-particle swarm optimization logistic model fitting algorithm for software reliability analysis
inferred← citeshttps://doi.org/10.23919/indiacom61295.2024.10499182openalex-snapshot
Suggesting Exit Path in a Multi-Path in Case of an Emergency
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