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Prediction of software development faults in PL/SQL files using neural network models

https://doi.org/10.1016/j.infsof.2003.08.006

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What this work says

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

inferredcites →https://doi.org/10.1016/b978-0-12-799957-9.00002-xopenalex-snapshot

Database Management Systems

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The prediction of faulty classes using object-oriented design metrics

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Exploring the relationships between design measures and software quality in object-oriented systems

inferredcites →https://doi.org/10.1109/32.748920openalex-snapshot

A unified framework for coupling measurement in object-oriented systems

inferredcites →https://doi.org/10.1109/32.859533openalex-snapshot

Predicting fault incidence using software change history

inferredcites →https://doi.org/10.1109/32.879814openalex-snapshot

An empirical investigation of an object-oriented software system

inferredcites →https://doi.org/10.1109/32.879815openalex-snapshot

Quantitative analysis of faults and failures in a complex software system

inferredcites →https://doi.org/10.1109/32.935855openalex-snapshot

The confounding effect of class size on the validity of object-oriented metrics

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A general regression neural network

inferredcites →https://doi.org/10.1109/asset.2000.888032openalex-snapshot

Predicting testability of program modules using a neural network

inferredcites →https://doi.org/10.1109/csmr.2001.914976openalex-snapshot

A study on fault-proneness detection of object-oriented systems

inferredcites →https://doi.org/10.1109/iconip.2002.1201906openalex-snapshot

Application of neural network for predicting software development faults using object-oriented design metrics

inferredcites →https://doi.org/10.1109/icsm.2001.972771openalex-snapshot

A metric framework for the assessment of object-oriented systems

inferredcites →https://doi.org/10.1109/metric.2001.915509openalex-snapshot

Proceedings Seventh International Software Metrics Symposium

inferredcites →https://doi.org/10.1109/metric.2001.915527openalex-snapshot

A primer on object-oriented measurement

inferredcites →https://doi.org/10.1109/tools.2000.868960openalex-snapshot

Towards a semantic metrics suite for object-oriented design

inferredcites →https://doi.org/10.1109/tse.2002.1019484openalex-snapshot

Assessing the applicability of fault-proneness models across object-oriented software projects

inferredcites →https://doi.org/10.2307/2282666openalex-snapshot

Elementary Business Statistics: The Modern Approach.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A systematic review of machine learning techniques for software fault prediction

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Prediction approach of software fault-proneness based on hybrid artificial neural network and quantum particle swarm optimization

inferred← citeshttps://doi.org/10.1016/j.eswa.2007.02.012openalex-snapshot

Regression via Classification applied on software defect estimation

inferred← citeshttps://doi.org/10.1016/j.eswa.2009.12.056openalex-snapshot

Cost-sensitive boosting neural networks for software defect prediction

inferred← citeshttps://doi.org/10.1016/j.eswa.2010.08.022openalex-snapshot

Practical development of an Eclipse-based software fault prediction tool using Naive Bayes algorithm

inferred← citeshttps://doi.org/10.1016/j.eswa.2021.114595openalex-snapshot

Machine learning based methods for software fault prediction: A survey

inferred← citeshttps://doi.org/10.1016/j.infsof.2008.04.008openalex-snapshot

Integrating in-process software defect prediction with association mining to discover defect pattern

inferred← citeshttps://doi.org/10.1016/j.infsof.2021.106747openalex-snapshot

SHSE: A subspace hybrid sampling ensemble method for software defect number prediction

inferred← citeshttps://doi.org/10.1016/j.ins.2008.10.005openalex-snapshot

Estimating software readiness using predictive models

inferred← citeshttps://doi.org/10.1016/j.ins.2011.01.026openalex-snapshot

The design of polynomial function-based neural network predictors for detection of software defects

inferred← citeshttps://doi.org/10.1088/1742-6596/1823/1/012052openalex-snapshot

Pl/sql design to determine the training data pattern on the Adaline neural network

inferred← citeshttps://doi.org/10.1109/icste.2010.5608831openalex-snapshot

Software fault detection for reliability using recurrent neural network modeling

inferred← citeshttps://doi.org/10.1109/ijcnn.2006.1716506openalex-snapshot

Utilizing Computational Intelligence in Estimating Software Readiness

inferred← citeshttps://doi.org/10.1109/itng.2009.12openalex-snapshot

Clustering and Metrics Thresholds Based Software Fault Prediction of Unlabeled Program Modules

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Gauzing software readiness using metrics

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AN IMPLEMENTATION OF METRICS EXTRACTION AND ANALYZER TOOL

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Mind the gaps: increasing the impact of IS research on ISD performance improvement

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Credibility Based Imbalance Boosting Method for Software Defect Proneness Prediction

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Empirical Study of Software Defect Prediction: A Systematic Mapping

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A Frame Work for Business Defect Predictions in Mobiles

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