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Automated Identification of High Impact Bug Reports Leveraging Imbalanced Learning Strategies
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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/j.infsof.2014.12.006openalex-snapshot
ELBlocker: Predicting blocking bugs with ensemble imbalance learning
inferredcites →https://doi.org/10.1109/ase.2011.6100086openalex-snapshot
AutoODC: Automated generation of Orthogonal Defect Classifications
inferredcites →https://doi.org/10.1109/csmr-wcre.2014.6747163openalex-snapshot
Towards more accurate multi-label software behavior learning
inferredcites →https://doi.org/10.1109/csmr-wcre.2014.6747167openalex-snapshot
An empirical study of bug report field reassignment
inferredcites →https://doi.org/10.1109/esem.2007.28openalex-snapshot
The Effects of Over and Under Sampling on Fault-prone Module Detection
inferredcites →https://doi.org/10.1109/msr.2010.5463284openalex-snapshot
Predicting the severity of a reported bug
inferredcites →https://doi.org/10.1109/msr.2013.6624040openalex-snapshot
Tag recommendation in software information sites
inferredcites →https://doi.org/10.1109/msr.2015.78openalex-snapshot
A Dataset of High Impact Bugs: Manually-Classified Issue Reports
inferredcites →https://doi.org/10.1109/tr.2013.2259203openalex-snapshot
Using Class Imbalance Learning for Software Defect Prediction
inferredcites →https://doi.org/10.1109/tr.2015.2484074openalex-snapshot
Automated Bug Report Field Reassignment and Refinement Prediction
inferredcites →https://doi.org/10.1145/1117696.1117704openalex-snapshot
Coping with an open bug repository
inferredcites →https://doi.org/10.1145/1985441.1985457openalex-snapshot
Security versus performance bugs
inferredcites →https://doi.org/10.1145/2597073.2597099openalex-snapshot
Characterizing and predicting blocking bugs in open source projects
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.5555/2820518.2820602openalex-snapshot
A dataset of high impact bugs: manually-classified issue reports
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/smr.2290openalex-snapshot
IMNRFixer: A hybrid approach to alleviate class‐imbalance problem for predicting the fixability of Non‐Reproducible bugs
inferred← citeshttps://doi.org/10.1007/978-3-319-93638-3_35openalex-snapshot
Automatically Identifying Security Bug Reports via Multitype Features Analysis
inferred← citeshttps://doi.org/10.1007/s10664-020-09906-8openalex-snapshot
How to Better Distinguish Security Bug Reports (Using Dual Hyperparameter Optimization)
inferred← citeshttps://doi.org/10.1007/s11390-017-1713-3openalex-snapshot
High-Impact Bug Report Identification with Imbalanced Learning Strategies
inferred← citeshttps://doi.org/10.1016/j.eswa.2016.12.035openalex-snapshot
Learning from class-imbalanced data: Review of methods and applications
inferred← citeshttps://doi.org/10.1016/j.infsof.2020.106314openalex-snapshot
LTRWES: A new framework for security bug report detection
inferred← citeshttps://doi.org/10.1109/apsec57359.2022.00041openalex-snapshot
Multifaceted Hierarchical Report Identification for Non-Functional Bugs in Deep Learning Frameworks
inferred← citeshttps://doi.org/10.1109/fskd.2018.8687174openalex-snapshot
Ensemble based on Constraint Projection and Under-Sampling for Imbalanced Learning
inferred← citeshttps://doi.org/10.1109/iciev.2018.8641045openalex-snapshot
Security and Performance Bug Reports Identification with Class-Imbalance Sampling and Feature Selection
inferred← citeshttps://doi.org/10.1109/qrs54544.2021.00056openalex-snapshot
Automatic Identification of High Impact Bug Report by Test Smells of Textual Similar Bug Reports
inferred← citeshttps://doi.org/10.1109/smartcomp.2019.00026openalex-snapshot
Identifying Security Bug Reports Based Solely on Report Titles and Noisy Data
inferred← citeshttps://doi.org/10.1109/tse.2018.2876537openalex-snapshot
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models
inferred← citeshttps://doi.org/10.1142/s021819402250036xopenalex-snapshot
Automatic Identification of High-Impact Bug Report by Product and Test Code Quality
inferred← citeshttps://doi.org/10.1145/3811925openalex-snapshot
Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1905.06872openalex-snapshot
Better Security Bug Report Classification via Hyperparameter Optimization
inferred← citeshttps://doi.org/10.7717/peerj-cs.604openalex-snapshot
Selective oversampling approach for strongly imbalanced data
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