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Artificial Neural Network-Based Approach for Forecasting Software Reliability: An Empirical Study

https://doi.org/10.2139/ssrn.4581146
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1 of the 33 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-04): 10.1007/s00500-019-04047-7 (notice 2024-09-03).

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/1097-024x(20001125)30:14<1587::aid-spe352>3.0.co;2-1openalex-extracted
Applying design metrics to predict fault-proneness: a case study on a large-scale software system
inferredcites →https://doi.org/10.1002/qre.2653openalex-extracted
Software reliability prediction and management: A multiple change‐point model approach
inferredcites →https://doi.org/10.1002/spe.1075openalex-extracted
Agile methods for open source safety‐critical software
inferredcites →https://doi.org/10.1002/spe.1146openalex-extracted
A consensus‐based strategy to improve the quality of fault localization
inferredcites →https://doi.org/10.1002/spe.2784openalex-extracted
Software fault prediction using particle swarm algorithm with genetic algorithm and support vector machine classifier
inferredcites →https://doi.org/10.1002/spe.726openalex-extracted
Establishing structural testing criteria for Java bytecode
inferredcites →https://doi.org/10.1007/978-3-030-28957-7_26openalex-extracted
Software Development Metrics Prediction Using Time Series Methods
inferredcites →https://doi.org/10.1007/978-981-15-4992-2_56openalex-extracted
A Novel Data Prediction Technique Based on Correlation for Data Reduction in Sensor Networks
inferredcites →https://doi.org/10.1007/s00500-019-04047-7openalex-extracted
RETRACTED ARTICLE: A novel machine learning approach for software reliability growth modelling with pareto distribution function
inferredcites →https://doi.org/10.1007/s12652-020-01912-4openalex-extracted
Software reliability prediction model with realistic assumption using time series (S)ARIMA model
inferredcites →https://doi.org/10.1007/s42452-020-04015-zopenalex-extracted
A time-variant fault detection software reliability model
inferredcites →https://doi.org/10.1016/j.jss.2007.05.005openalex-extracted
Software reliability prediction by soft computing techniques
inferredcites →https://doi.org/10.1016/j.jss.2013.03.045openalex-extracted
An approach to software reliability prediction based on time series modeling
inferredcites →https://doi.org/10.1016/j.jss.2014.12.029openalex-extracted
Improving software reliability prediction through multi-criteria based dynamic model selection and combination
inferredcites →https://doi.org/10.1016/j.matpr.2020.11.518openalex-extracted
Reliability prediction analysis of aspect-oriented application using soft computing techniques
inferredcites →https://doi.org/10.1049/iet-sen.2010.0007openalex-extracted
When to stop testing: a study from the perspective of software reliability models
inferredcites →https://doi.org/10.1049/iet-sen.2014.0108openalex-extracted
Approach for parameter estimation in Markov model of software reliability for early prediction: a case study
inferredcites →https://doi.org/10.1109/3468.823478openalex-extracted
Software reliability models with time-dependent hazard function based on Bayesian approach
inferredcites →https://doi.org/10.1109/3468.925663openalex-extracted
A Bayesian predictive software reliability model with pseudo-failures
inferredcites →https://doi.org/10.1109/37.55119openalex-extracted
Neural networks for self-learning control systems
inferredcites →https://doi.org/10.1109/aiccsa.2009.5069339openalex-extracted
Software reliability prediction using multi-objective genetic algorithm
inferredcites →https://doi.org/10.1109/confluence.2016.7508198openalex-extracted
Software reliability prediction modeling: A comparison of parametric and non-parametric modeling
inferredcites →https://doi.org/10.1109/grc.2012.6468581openalex-extracted
A data-driven model for software reliability prediction
inferredcites →https://doi.org/10.1109/icime.2010.5478245openalex-extracted
A software reliability prediction model based on benchmark measurement
inferredcites →https://doi.org/10.1109/mysec.2015.7475221openalex-extracted
A survey of software reliability growth model selection methods for improving reliability prediction accuracy
inferredcites →https://doi.org/10.1109/prdc.2006.30openalex-extracted
Early Software Reliability Prediction with ANN Models
inferredcites →https://doi.org/10.1109/rams.2010.5447986openalex-extracted
Soft computing approaches in reliability modeling and analysis of repairable systems
inferredcites →https://doi.org/10.1109/skg.2010.49openalex-extracted
Software Reliability Prediction Model Based on Relevance Vector Machine
inferredcites →https://doi.org/10.12720/joams.3.3.203-210openalex-extracted
Reliability Analysis and Failure Prediction of Construction Equipment with Time Series Models
inferredcites →https://doi.org/10.1613/jair.1.11420openalex-extracted
Pitfalls and Best Practices in Algorithm Configuration
inferredcites →https://doi.org/10.22214/ijraset.2017.4180openalex-extracted
A Brief Review of Software Reliability Prediction Models
inferredcites →https://doi.org/10.3390/math8050791openalex-extracted
Software Reliability for Agile Testing
inferredcites →https://doi.org/10.5555/800054.801975openalex-extracted
A logarithmic poisson execution time model for software reliability measurement

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inferred← citeshttps://doi.org/10.32604/csse.2024.057067openalex-snapshot
Software Reliability Prediction Using Ensemble Learning on Selected Features in Imbalanced and Balanced Datasets: A Review
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