CMU SEI Research Review 2019
• Collection
Publisher
Software Engineering Institute
Collection Items
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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Causal Models for Software Cost Prediction and Control (video)
• Video
By Michael D. Konrad, Bill Nichols, Robert W. Stoddard, David Zubrow
Researchers at CMU SEI collaborated with other researchers to apply causal learning to learn how to control costs in software development and sustainment.
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Causal Models for Software Cost Prediction and Control
• Presentation
By Michael D. Konrad, Robert W. Stoddard, Bill Nichols, David Zubrow
This presentation describes work toward establishing causation with observational data, which remains a vital need and a key technical challenge.
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Causal Models for Software Cost Prediction & Control
• Poster
By Michael D. Konrad, Robert W. Stoddard, Bill Nichols, David Zubrow
This poster provides an update on ongoing research to use causal learning in software cost prediction.
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Integrating Safety and Security Engineering for Mission-Critical Systems (2019)
• Poster
By Sam Procter
This poster provides an update on research to make systems safer and more secure.
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Integrated Safety and Security Engineering for Mission-Critical Systems
• Presentation
By Sam Procter
This presentation describes progress in research to develop software and processes that use a system's architecture to support developer intuition and improve safety and security.
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Graph Convolutional Neural Networks
• Presentation
By Oren Wright
This project used graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs).
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Graph Convolutional Neural Networks
• Poster
By Oren Wright
This poster describes research to use graph convolutional neural networks to extend deep learning.
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Graph Convolutional Neural Networks
• Video
By Oren Wright
Watch SEI researcher Mr. Oren Wright discuss using graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs) to answer the question "how does …
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Video Summarization and Search
• Presentation
By Rachel Brower-Sinning, Jeffrey Hansen
This project's goal is to assist video analysts by increasing the volume of data that can be analyzed and providing insights into patterns of life
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Summarizing and Searching Video: Domain Adaptation
• Poster
By Edwin J. Morris
This poster describes research to enable the use of existing data sets to training detectors in low data environments.
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Summarizing and Searching Video: Patterns-of-Life Analysis
• Poster
By Edwin J. Morris
This poster describes experiments to use simulations to explore patterns-of-life analysis.
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Summarizing and Searching Video: Geometry-Aware Visual Surveillance
• Poster
By Edwin J. Morris
This poster describes research to develop a moving-object tracker for video search.
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Projecting Quantum Computational Advantage Versus Classical State of the Art
• Presentation
By Jason Larkin
This presentation reports on research to predict when (or whether) quantum computing will be mission-capable for hard combinatorial optimization problems in software V&V.
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Projecting Quantum Computational Advantage Versus Classical State of the Art
• Poster
By Jason Larkin
This poster describes research to project when quantum computational advantage will outperform classical state of the art.
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Projecting Quantum Computational Advantage Versus Classical State of the Art (video)
• Video
By Jason Larkin
Watch SEI researcher Dr. Jason Larkin discuss research to predict when (or whether) quantum computing will be mission-capable for hard combinatorial optimization problems in software verification and validation (V&V).
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Field Stripping a Weapons System: Building a Trustworthy Computer
• Presentation
By Gabriel Somlo
This presentation describes research to demonstrate the practicality of a comprehensive approach to guaranteeing the trustworthiness of computer systems.
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Field Stripping a Weapons System: Building a Trustworthy Computer
• Poster
By Gabriel Somlo
This poster describes research to determine the feasibility of rebuilding a weapons system from source code.
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Field Stripping a Weapons System: Building a Trustworthy Computer (video)
• Video
By Gabriel Somlo
Watch SEI principal investigator Dr. Gabriel Somlo discuss research to demonstrate the practicality of guaranteeing the trustworthiness of DoD fielded computer systems.
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KalKi: High Assurance Software-Defined IoT Security
• Poster
By Sebastián Echeverría
This poster provides an update on research to help accelerate the safe use of Internet of Things devices in tactical settings.
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KalKi: High-Assurance Software-Defined IoT Security
• Presentation
By Sebastián Echeverría
We are developing a solution for DoD's use of commodity IoT technologies that remains resilient and trustworthy, even in the presence of a powerful attacker.
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Kalki: High Assurance Software-Defined IoT Security (video)
• Video
By Sebastián Echeverría
Watch SEI principal investigator Mr. Sebastian Echeverria discuss research to enable the secure integration of IoT devices into DoD systems, even if the devices are not fully trusted or configurable.
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Using All Processor Cores While Being Confident about Timing
• Presentation
By Bjorn Andersson
This presentation describes research to address the use of all processor cores while retaining confidence about timing.
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Using All Processor Cores While Being Confident about Timing
• Poster
By Bjorn Andersson
This posters provides information on research to develop a method to verify timing of software executing on a multicore processor assuming that we do not know the resources in the …
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Using All Processor Cores While Being Confident about Timing
• Video
By Bjorn Andersson
Watch SEI principal investigator Dr. Bjorn Andersson discuss research on solutions to avoid the common practice of disabling all processor cores except one in order to be confident about timing.
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Emotion Recognition from Voice in the Wild
• Presentation
By Oren Wright
This presentation describes progress in research to use advances in micro-articulometry to identify emotion from voice.
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Emotion Recognition from Voice in the Wild
• Poster
By Oren Wright
This poster represents research to determine the feasibility of using micro-articulometry technique to accurately recognize emotion from voice.
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Untangling the Knot: Recommending Component Refactorings
• Poster
By James Ivers
This poster describes early research intended to outperform refactoring recommendations based only on quality metrics.
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Untangling the Knot: Recommending Component Refactorings
• Presentation
By James Ivers
This presentation describes work to improve the ability to evolve software efficiently.
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Untangling the Knot: Recommending Component Refactorings
• Video
By James Ivers
Watch SEI principal investigator Mr. James Ivers discuss research on applying AI techniques to rapidly increase the pace of making structural changes to software code bases.
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A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior
• Poster
By Eric Heim
This poster represents research to apply Inverse Reinforcement Learning techniques to model sequential behavior.
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A Series of Unlikely Events: Learning from Sequential Behavior for Activity-Based Intelligence and Modeling Human Expertise
• Presentation
By Eric Heim
This presentation describes work to use inverse reinforcement learning techniques to perform activity-based intelligence.
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A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior (video)
• Video
By Eric Heim
Watch SEI principal investigator Eric Heim discuss research to develop novel Inverse Reinforcement Learning (IRL) techniques.
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Spiral/AIML: Frontiers of Graph Processing in Linear Algebra
• Poster
By Scott McMillan, Franz Franchetti (Carnegie Mellon University)
This poster represents research to extend the use of linear algebra beyond simple graph traversal.
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Spiral/AIML: Co-optimization for High-Performance, Data-Intensive Computing in Resource Constrained Environments
• Presentation
By Scott McMillan, Franz Franchetti (Carnegie Mellon University)
Data-intensive computing is pervasive. This presentation provides an update on research to allow platform developers to realize high-performance AI/ML applications on leading-edge hardware architectures faster and cheaper.
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Spiral/AIML: Resource-Constrained Co-Optimization for High-Performance, Data-Intensive Computing
• Video
By Scott McMillan, Franz Franchetti (Carnegie Mellon University)
Watch SEI Principal Investigator, Dr. Scott McMillan, and research collaborator, CMU ECE Professor Franz Franchetti, discuss a community research effort to develop tools to reduce the prohibitive cost of implementing …
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Rapid Certifiable Trust (video)
• Video
By Dionisio de Niz
Watch SEI principal investigator Dr. Dionisio de Niz discuss research on verification techniques to reduce the deployment time of cyber-physical systems such as unmanned vehicles and aircraft, by reducing the …
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Rapid Certifiable Trust
• Presentation
By Dionisio de Niz
Rapid Certifiable Trust preserves cyber-physical system safety by verifying and protecting part of a system and enforcing constraints on unverified components.
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Rapid Certifiable Trust
• Poster
By Dionisio de Niz
This poster describes investigation into formal methods to automatically validate new technologies for safety.
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Panel: Supercharging the Software Factory: Deploying Capability at the Speed of Relevance
• Video
By Anita Carleton
Watch as Ms. Anita Carleton, Director of the SEI Software Solutions Division, moderates discussion on deploying mission capability at the speed of relevance to maintain DoD competitive advantage by a …
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Integrating Safety and Security Engineering for Mission-Critical Systems
• Video
By Sam Procter, Alex Boydston (U.S. Army ADD/JMR)
Watch SEI principal investigator Dr. Sam Procter discuss ongoing research to make it easier to specify, design, and assure critical systems that are safer and more secure using model based …
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Future Reach Conversation: Countering Adversarial Operations Made Possible by AI
• Video
By Allen D. Householder, Lujo Bauer (Carnegie Mellon University, Department of Electrical and Computer Engineering), Kathleen Carley (Carnegie Mellon School of Computer Science)
Watch as Dr. Matt Gaston, Director of SEI Emerging Technology Center, moderates discussion on countering adversarial operations made possible by AI
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Summarizing and Searching Video (2019)
• Video
By Edwin J. Morris, Rachel Brower-Sinning, Jeffrey Hansen
Watch SEI and CMU researchers discuss a way to improve the training of machine learning algorithms necessary for detecting, tracking, and recognizing patterns of objects in video.
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Defining AI Engineering
• Video
By Matt Gaston
Watch Dr. Matt Gaston, Director of the SEI Emerging Technology Center, and Professor Martial Hebert, Dean of CMU School of Computer Science and recognized world expert in computer vision, discuss …
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Emotion Recognition from Voice in the Wild (Video)
• Video
By Oren Wright
Watch SEI Principal Investigator, Oren Wright, and CMU Language Technologies Institute collaborator, Shahan Ali Memon, discuss machine emotional intelligence and introduce an innovative speech emotion recognition database, CMU-SER.
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Projecting How AI/ML Will Revolutionize Software Vulnerability Discovery
• Video
By Greg Shannon
Watch as Dr. Greg Shannon, SEI CERT Division Chief Scientist, moderates discussion on projecting how AI/ML will revolutionize software vulnerability discovery, mitigation, and/or coordination
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