Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

Digital Library

Javascript is currently disabled for your browser. For an optimal search experience, please enable javascript.

Advanced Search

Basic Search

Content Type

Topics

Publication Date

Showing 1 - 9 of 9 results for the Author - arie gurfinkel

Technical Report | August 2010 - Technical Report COVERT: A Framework for Finding Buffer Overflows in C ... By Sagar Chaki, Arie Gurfinkel

In this report, the authors present COVERT, an automated framework for finding buffer overflows in C programs using software verification tools and techniques.

Technical Report | August 2012 - Technical Report Results of SEI Line-Funded Exploratory New Starts Projects By Len Bass, Rick Kazman, Edwin J. Morris, Brad Myers, William Nichols, Robert Nord, Ipek Ozkaya, Raghvinder Sangwan, Soumya Simanta, Ofer Strichman, Peppo Valetto, Nanette Brown, Gene Cahill, William Casey, Sagar Chaki, Cory Cohen, Dionisio de Niz, David French, Arie Gurfinkel

This report describes the line-funded exploratory new starts (LENS) projects that were undertaken during fiscal year 2011. For each project, the report presents a brief description and a recounting of the research that was done, as well as a synopsis of the results of the project.

Technical Report | July 2013 - Technical Report Results of SEI Line-Funded Exploratory New Starts Projects ... By Bjorn Andersson, Lori Flynn, David P. Gluch, Dennis Goldenson, Arie Gurfinkel, Jeff Havrilla, Chuck Hines, John J. Hudak, Carly L. Huth, Wesley Jin, Rick Kazman, Stephany Bellomo, Mary Ann Lapham, James McCurley, John McGregor, David McIntire, Robert Nord, Ipek Ozkaya, Brittany Phillips, Robert W. Stoddard, David Zubrow, Lisa Brownsword, Yuanfang Cai (Drexel University), Sagar Chaki, William R. Claycomb, Julie B. Cohen, Peter H. Feiler, Robert Ferguson

This report describes line-funded exploratory new starts (LENS) projects that were conducted during fiscal year 2012 (October 2011 through September 2012).

Article | October 2014 - Article Supervised Learning for Provenance-Similarity of Binaries By Sagar Chaki, Cory Cohen, Arie Gurfinkel

In this article, the authors present a notion of similarity based on provenance; two binaries are similar if they are compiled from the same source code with the same compilers.

White Paper | April 2013 - White Paper Four Pillars for Improving the Quality of Safety-Critical ... By Peter H. Feiler, John B. Goodenough, Arie Gurfinkel, Charles B. Weinstock, Lutz Wrage

This white paper presents an improvement strategy comprising four pillars of an integrate-then-build practice that lead to improved quality through early defect discovery and incremental end-to-end validation and verification.

Special Report | November 2012 - Special Report Reliability Improvement and Validation Framework By Peter H. Feiler, John B. Goodenough, Arie Gurfinkel, Charles B. Weinstock, Lutz Wrage

This report discusses the reliability validation and improvement framework developed by the SEI. The purpose of this framework is to provide a foundation for addressing the challenges of qualifying increasingly software-reliant, safety-critical systems.

Article | October 2014 - Article Recovering C++ Objects From Binaries Using Inter-Procedural ... By Wesley Jin, Cory Cohen, Jeff Gennari, Chuck Hines, Sagar Chaki, Arie Gurfinkel, Jeff Havrilla, Priya Narasimhan (Carnegie Mellon University)

In this article, the authors present a static approach that uses symbolic execution and inter-procedural data flow analysis to discover object instances, data members, and methods of a common class.

Presentation | October 2011 - Presentation Time-Bounded Analysis of Real-Time Systems By Sagar Chaki, Arie Gurfinkel, Soonho Kong, Ofer Strichman

This presentation considers the problem of verifying functional correctness of periodic Real-Time Embedded Software (RTES), a popular variant of RTES that execute periodic tasks in an order determined by Rate Monotonic Scheduling (RMS).

Article | October 2014 - Article Binary Function Clustering using Semantic Hashes By Wesley Jin, Sagar Chaki, Cory Cohen, Arie Gurfinkel, Jeff Havrilla, Chuck Hines, Priya Narasimhan (Carnegie Mellon University)

In this article, the authors present an alternative to pair wise comparisons based on hashing” that captures the semantics of functions as semantic hashes.