Inspecting JavaScript Vulnerability Mitigation Patches with Automated Fix Generation in Mind

[1]  Laurie A. Williams,et al.  Can traditional fault prediction models be used for vulnerability prediction? , 2011, Empirical Software Engineering.

[2]  Dimitrios Tzovaras,et al.  A Preliminary Study on the Relationship Among Software Metrics and Specific Vulnerability Types , 2017, 2017 International Conference on Computational Science and Computational Intelligence (CSCI).

[3]  Claire Le Goues,et al.  Current challenges in automatic software repair , 2013, Software Quality Journal.

[4]  Yves Le Traon,et al.  Enabling the Continous Analysis of Security Vulnerabilities with VulData7 , 2018 .

[5]  Laurie A. Williams,et al.  An empirical model to predict security vulnerabilities using code complexity metrics , 2008, ESEM '08.

[6]  Tzi-cker Chiueh,et al.  DIRA: Automatic Detection, Identification and Repair of Control-Hijacking Attacks , 2005, NDSS.

[7]  Andreas Zeller,et al.  Predicting vulnerable software components , 2007, CCS '07.

[8]  Xuandong Li,et al.  BovInspector: Automatic inspection and repair of buffer overflow vulnerabilities , 2016, 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE).

[9]  Tibor Gyimóthy,et al.  Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions , 2019, 2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE).

[10]  Laurie A. Williams,et al.  Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities , 2011, IEEE Transactions on Software Engineering.

[11]  Yves Le Traon,et al.  [Engineering Paper] Enabling the Continuous Analysis of Security Vulnerabilities with VulData7 , 2018, 2018 IEEE 18th International Working Conference on Source Code Analysis and Manipulation (SCAM).

[12]  Tyler Moore,et al.  Measuring the Cost of Cybercrime , 2012, WEIS.

[13]  Chris F. Kemerer,et al.  A Metrics Suite for Object Oriented Design , 2015, IEEE Trans. Software Eng..

[14]  Robert H. Deng,et al.  VuRLE: Automatic Vulnerability Detection and Repair by Learning from Examples , 2017, ESORICS.

[15]  Mohammad Zulkernine,et al.  Using complexity, coupling, and cohesion metrics as early indicators of vulnerabilities , 2011, J. Syst. Archit..

[16]  Laurie A. Williams,et al.  Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista , 2010, 2010 Third International Conference on Software Testing, Verification and Validation.

[17]  Laurie A. Williams,et al.  Cost-aware Vulnerability Prediction: the HARMLESS Approach , 2018, ArXiv.

[18]  Laurie A. Williams,et al.  Challenges with applying vulnerability prediction models , 2015, HotSoS.