Computer Science Seminar
Date: Tuesday, 10 October 2023
Time: 03:45 PM
Venue: Seminar Hall, CMI
Exposing Concurrency Bugs from their Hiding Places
Umang Mathur
National University of Singapore.
10-10-23

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Abstract

Concurrent programs are notoriously hard to write correctly, as scheduling nondeterminism introduces subtle errors that are both hard to detect and to reproduce.
Despite rigorous testing, concurrency bugs such as races conditions often find their way into production software, and manifest as critical security issues. Consequently, considerable effort has been made towards developing efficient techniques for detecting them automatically.
The preferred approach to detect data races is through dynamic analysis, where one executes the software with some test inputs, and checks for the presence of bugs in the execution observed.
Traditional bug detectors however are often unable to discover simple bugs present in the underlying software, even after executing the program several times, because these bugs are sensitive to thread scheduling.
In this talk, I will discuss how runtime predictive analysis can help. Runtime predictive analyses aim to expose concurrency bugs, that can be otherwise missed by traditional dynamic analysis techniques (such as the race detector TSan), by inferring the presence of these bugs in alternate executions of the underlying software, without explicitly re-executing the software program.
I will talk about the fundamentals of and recent algorithmic advances for building highly scalable and sound predictive analysis techniques.

Speaker Bio:
Umang Mathur is a Presidential Young Professor at the National University of Singapore. He received his PhD from the University of Illinois at Urbana Champaign and was an NTT Research Fellow at the Simons Institute for the Theory of Computing at Berkeley. His research broadly centers on developing techniques inspired from formal methods and logic for answering design, analysis and implementation questions in programming languages, software engineering and systems. He has received a Google PhD Fellowship, an ACM SIGSOFT Distinguished Paper Award at ESEC/FSE'18. Best Paper Award at ASPLOS'22 and an ACM SIGPLAN Distinguished Paper Award at POPL'23 for his work on designing techniques and tools for analyzing concurrent software.