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What and Who
Title:Automated Test Generation: A Journey from Symbolic Execution to Smart Fuzzing and Beyond
Speaker:Koushik Sen
coming from:UC Berkeley
Speakers Bio:Koushik Sen is a professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research interest lies in Software Engineering, Programming Languages, and Formal methods. He is interested in developing software tools and methodologies that improve programmer productivity and software quality. He is best known for his work on “DART: Directed Automated Random Testing” and concolic testing. He has received a NSF CAREER Award in 2008, a Haifa Verification Conference (HVC) Award in 2009, a IFIP TC2 Manfred Paul Award for Excellence in Software: Theory and Practice in 2010, a Sloan Foundation Fellowship in 2011, a Professor R. Narasimhan Lecture Award in 2014, an Okawa Foundation Research Grant in 2015, and an ACM SIGSOFT Impact Paper Award in 2019. He has won several ACM SIGSOFT Distinguished Paper Awards. He received the C.L. and Jane W-S. Liu Award in 2004, the C. W. Gear Outstanding Graduate Award in 2005, and the David J. Kuck Outstanding Ph.D. Thesis Award in 2007, and a Distinguished Alumni Educator Award in 2014 from the UIUC Department of Computer Science. He holds a B.Tech from Indian Institute of Technology, Kanpur, and M.S. and Ph.D. in CS from University of Illinois at Urbana-Champaign.
Event Type:SWS Distinguished Lecture Series
Visibility:D1, D2, D3, INET, D4, D5, SWS, RG1, MMCI
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Level:AG Audience
Language:English
Date, Time and Location
Date:Tuesday, 4 June 2019
Time:10:30
Duration:75 Minutes
Location:Kaiserslautern
Building:G26
Room:111
Abstract
In the last two decades, automation has had a significant impact on software testing and analysis. Automated testing techniques, such as symbolic execution, concolic testing, and feedback-directed fuzzing, have found numerous critical faults, security vulnerabilities, and performance bottlenecks in mature and well-tested software systems. The key strength of automated techniques is their ability to quickly search state spaces by performing repetitive and expensive computational tasks at a rate far beyond the human attention span and computation speed. In this talk, I will give a brief overview of our past and recent research contributions in automated test generation using symbolic execution, program analysis, constraint solving, and fuzzing. I will also describe a new technique, called constraint-directed fuzzing, where given a pre-condition on a program as a logical formula, we can efficiently generate millions of test inputs satisfying the pre-condition.
Contact
Name(s):Mouna Litz
Video Broadcast
Video Broadcast:YesTo Location:Saarbrücken
To Building:E1 5To Room:029
Meeting ID:SWS Space 2 (6312)
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Created:
Mouna Litz/MPI-SWS, 05/17/2019 11:49 AM
Last modified:
Mouna Litz/MPI-SWS, 06/08/2019 01:31 PM
  • Mouna Litz, 06/08/2019 01:31 PM
  • Mouna Litz, 05/17/2019 11:54 AM -- Created document.