CMU SEI Research Review 2019
• Collection
Publisher
Software Engineering Institute
Collection Items
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CMU SEI Research Review 2019 Project Descriptions and Posters
• Annual Report
By Software Engineering Institute
This brochure includes descriptive information about the SEI's fiscal year 2019 research portfolio
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Research Review 2019 Schedule
• Brochure
By Software Engineering Institute
This handout outlines the schedule for Research Review 2019, held on October 21 and 22, 2019.
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Automated Code Repair to Ensure Memory Safety (2019)
• Presentation
By William Klieber
This presentation describes an approach to automatically repair source doe to assure memory safety.
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Automated Code Repair to Ensure Memory Safety in C Source Code (2019)
• Poster
By William Klieber
This is a poster reflecting research to automatically repair C source code to eliminate memory-safety vulnerabilities.
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Automated Code Repair to Ensure Memory Safety (video)
• Video
By William Klieber
Watch SEI principal investigator Dr. Will Klieber discuss research to design and implement a technique to automatically repair all potential violations of memory safety in the source code so that …
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Recovering Meaningful Variable Names in Decompiled Code
• Poster
By Professor Vasilescu
In this project, we showed that the conventional wisdom that variable names cannot be recovered is wrong.
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Recovering Meaningful Variable Names in Decompiled Code (video)
• Video
By Professor Vasilescu
Watch CMU Institute for Software Research (ISR) assistant professor Dr. Bogdan Vasilescu discuss ongoing collaborative research with SEI in the reverse engineering of legacy systems using machine learning (ML) to …
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Rapid Construction of Accurate Automatic Alert Handling System (2019)
• Poster
By Lori Flynn, Ebonie McNeil
This poster includes information about research to develop a prototype source code analysis integrated framework environment.
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Rapid Construction of Accurate Automatic Alert Handling System (2019)
• Presentation
By Lori Flynn, Ebonie McNeil
This presentation describes progress toward developing a reference architecture and prototype that enables rapid deployment of a method intended to automatically, accurately, and adaptively classify and prioritize alerts.
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Rapid Construction of Accurate Automatic Alert Handling System (video)
• Video
By Lori Flynn, Ebonie McNeil
Watch SEI principal investigator, Dr. Lori Flynn and SEI researcher Ebonie McNeil discuss their prototype of a tool that enables the rapid adoption of accurate, automated static analysis alerts classifiers …
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