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Large-Scale Empirical Studies on Effort-Aware Security Vulnerability Prediction Methods

https://doi.org/10.1109/tr.2019.2924932
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What this work says

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

inferredcites →https://doi.org/10.1007/s10515-010-0069-5openalex-snapshot
Defect prediction from static code features: current results, limitations, new approaches
inferredcites →https://doi.org/10.1007/s10664-008-9080-xopenalex-snapshot
Theory of relative defect proneness
inferredcites →https://doi.org/10.1007/s10664-011-9190-8openalex-snapshot
Can traditional fault prediction models be used for vulnerability prediction?
inferredcites →https://doi.org/10.1007/s10664-015-9400-xopenalex-snapshot
Studying just-in-time defect prediction using cross-project models
inferredcites →https://doi.org/10.1007/s11390-017-1785-0openalex-snapshot
A Cluster Based Feature Selection Method for Cross-Project Software Defect Prediction
inferredcites →https://doi.org/10.1016/j.infsof.2017.08.004openalex-snapshot
MULTI: Multi-objective effort-aware just-in-time software defect prediction
inferredcites →https://doi.org/10.1016/j.infsof.2018.10.003openalex-snapshot
Software defect number prediction: Unsupervised vs supervised methods
inferredcites →https://doi.org/10.1016/j.jss.2009.06.055openalex-snapshot
A systematic and comprehensive investigation of methods to build and evaluate fault prediction models
inferredcites →https://doi.org/10.1016/j.jss.2019.03.012openalex-snapshot
An empirical study on pareto based multi-objective feature selection for software defect prediction
inferredcites →https://doi.org/10.1108/eb046814openalex-snapshot
An algorithm for suffix stripping
inferredcites →https://doi.org/10.1109/4235.996017openalex-snapshot
A fast and elitist multiobjective genetic algorithm: NSGA-II
inferredcites →https://doi.org/10.1109/ase.2015.56openalex-snapshot
CLAMI: Defect Prediction on Unlabeled Datasets (T)
inferredcites →https://doi.org/10.1109/compsac.2014.66openalex-snapshot
FECAR: A Feature Selection Framework for Software Defect Prediction
inferredcites →https://doi.org/10.1109/compsac.2015.66openalex-snapshot
FECS: A Cluster Based Feature Selection Method for Software Fault Prediction with Noises
inferredcites →https://doi.org/10.1109/csmr.2010.18openalex-snapshot
Effort-Aware Defect Prediction Models
inferredcites →https://doi.org/10.1109/esem.2017.48openalex-snapshot
File-Level Defect Prediction: Unsupervised vs. Supervised Models
inferredcites →https://doi.org/10.1109/esem.2017.8openalex-snapshot
Code Churn: A Neglected Metric in Effort-Aware Just-in-Time Defect Prediction
inferredcites →https://doi.org/10.1109/iceccs.2015.15openalex-snapshot
Combining Software Metrics and Text Features for Vulnerable File Prediction
inferredcites →https://doi.org/10.1109/icmla.2018.00120openalex-snapshot
Automated Vulnerability Detection in Source Code Using Deep Representation Learning
inferredcites →https://doi.org/10.1109/icse.2013.6606583openalex-snapshot
Does bug prediction support human developers? Findings from a Google case study
inferredcites →https://doi.org/10.1109/icse.2015.91openalex-snapshot
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
inferredcites →https://doi.org/10.1109/icse.2017.48openalex-snapshot
Unsupervised Software-Specific Morphological Forms Inference from Informal Discussions
inferredcites →https://doi.org/10.1109/icsm.2010.5609530openalex-snapshot
Revisiting common bug prediction findings using effort-aware models
inferredcites →https://doi.org/10.1109/icsme.2017.51openalex-snapshot
Supervised vs Unsupervised Models: A Holistic Look at Effort-Aware Just-in-Time Defect Prediction
inferredcites →https://doi.org/10.1109/icst.2010.32openalex-snapshot
Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista
inferredcites →https://doi.org/10.1109/issre.2014.32openalex-snapshot
Predicting Vulnerable Components: Software Metrics vs Text Mining
inferredcites →https://doi.org/10.1109/issre.2016.13openalex-snapshot
The Impact of Feature Selection on Defect Prediction Performance: An Empirical Comparison
inferredcites →https://doi.org/10.1109/msp.2011.70openalex-snapshot
Vulnerability Detection Systems: Think Cyborg, Not Robot
inferredcites →https://doi.org/10.1109/msr.2017.18openalex-snapshot
A Large-Scale Study of the Impact of Feature Selection Techniques on Defect Classification Models
inferredcites →https://doi.org/10.1109/qrs.2015.15openalex-snapshot
Predicting Vulnerable Components via Text Mining or Software Metrics? An Effort-Aware Perspective
inferredcites →https://doi.org/10.1109/saner.2016.34openalex-snapshot
MICHAC: Defect Prediction via Feature Selection Based on Maximal Information Coefficient with Hierarchical Agglomerative Clustering
inferredcites →https://doi.org/10.1109/saner.2016.56openalex-snapshot
Defect Prediction: Accomplishments and Future Challenges
inferredcites →https://doi.org/10.1109/saner.2018.8330210openalex-snapshot
Cross-version defect prediction via hybrid active learning with kernel principal component analysis
inferredcites →https://doi.org/10.1109/tkde.2008.239openalex-snapshot
Learning from Imbalanced Data
inferredcites →https://doi.org/10.1109/tr.2015.2461676openalex-snapshot
Empirical Studies of a Two-Stage Data Preprocessing Approach for Software Fault Prediction
inferredcites →https://doi.org/10.1109/tr.2016.2630503openalex-snapshot
The Effect of Dimensionality Reduction on Software Vulnerability Prediction Models
inferredcites →https://doi.org/10.1109/tse.2008.90openalex-snapshot
An Investigation into the Functional Form of the Size-Defect Relationship for Software Modules
inferredcites →https://doi.org/10.1109/tse.2010.81openalex-snapshot
Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities
inferredcites →https://doi.org/10.1109/tse.2011.103openalex-snapshot
A Systematic Literature Review on Fault Prediction Performance in Software Engineering
inferredcites →https://doi.org/10.1109/tse.2012.43openalex-snapshot
Reducing Features to Improve Code Change-Based Bug Prediction
inferredcites →https://doi.org/10.1109/tse.2012.70openalex-snapshot
A large-scale empirical study of just-in-time quality assurance
inferredcites →https://doi.org/10.1109/tse.2013.21openalex-snapshot
Assessing the Cost Effectiveness of Fault Prediction in Acceptance Testing
inferredcites →https://doi.org/10.1109/tse.2014.2340398openalex-snapshot
Predicting Vulnerable Software Components via Text Mining
inferredcites →https://doi.org/10.1109/tse.2016.2521368openalex-snapshot
A Survey on Software Fault Localization
inferredcites →https://doi.org/10.1109/tse.2016.2584050openalex-snapshot
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
inferredcites →https://doi.org/10.1109/tse.2017.2693980openalex-snapshot
Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2017.2724538openalex-snapshot
A Comparative Study to Benchmark Cross-Project Defect Prediction Approaches
inferredcites →https://doi.org/10.1109/tse.2017.2770124openalex-snapshot
A Systematic Literature Review and Meta-Analysis on Cross Project Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2836442openalex-snapshot
A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2876537openalex-snapshot
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models
inferredcites →https://doi.org/10.1111/j.2517-6161.1995.tb02031.xopenalex-snapshot
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
inferredcites →https://doi.org/10.1145/1852786.1852792openalex-snapshot
Understanding the impact of code and process metrics on post-release defects
inferredcites →https://doi.org/10.1145/1852786.1852798openalex-snapshot
Strengthening the empirical analysis of the relationship between Linus' Law and software security
inferredcites →https://doi.org/10.1145/1985793.1985859openalex-snapshot
Dealing with noise in defect prediction
inferredcites →https://doi.org/10.1145/2001420.2001445openalex-snapshot
Are automated debugging techniques actually helping programmers?
inferredcites →https://doi.org/10.1145/2187671.2187673openalex-snapshot
Mitigating program security vulnerabilities
inferredcites →https://doi.org/10.1145/2372225.2372230openalex-snapshot
Software vulnerability prediction using text analysis techniques
inferredcites →https://doi.org/10.1145/2635868.2635892openalex-snapshot
Software developers' perceptions of productivity
inferredcites →https://doi.org/10.1145/2746194.2746198openalex-snapshot
Challenges with applying vulnerability prediction models
inferredcites →https://doi.org/10.1145/2785733openalex-snapshot
Collaborative Security
inferredcites →https://doi.org/10.1145/2884781.2884839openalex-snapshot
Cross-project defect prediction using a connectivity-based unsupervised classifier
inferredcites →https://doi.org/10.1145/2931037.2931043openalex-snapshot
Semantic modelling of Android malware for effective malware comprehension, detection, and classification
inferredcites →https://doi.org/10.1145/2931037.2931051openalex-snapshot
Practitioners' expectations on automated fault localization
inferredcites →https://doi.org/10.1145/2950290.2950353openalex-snapshot
Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models
inferredcites →https://doi.org/10.1145/3092566openalex-snapshot
Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques
inferredcites →https://doi.org/10.1145/3106237.3106257openalex-snapshot
Revisiting unsupervised learning for defect prediction
inferredcites →https://doi.org/10.1145/3106237.3106258openalex-snapshot
QTEP: quality-aware test case prioritization
inferredcites →https://doi.org/10.1145/3134667openalex-snapshot
By the Community & For the Community
inferredcites →https://doi.org/10.1145/3183339openalex-snapshot
How Far We Have Progressed in the Journey? An Examination of Cross-Project Defect Prediction
inferredcites →https://doi.org/10.5540/tema.2014.015.01.0003openalex-snapshot
ScottKnott: A Package for Performing the Scott-Knott Clustering Algorithm in R
inferredcites →https://doi.org/10.5555/2486788.2486838openalex-snapshot
Does bug prediction support human developers? findings from a google case study

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

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