Dynamic Data Race Prediction: Fundamentals and Advances

Speaker: Dr. Umang MATHUR
         National University of Singapore

Title: "Dynamic Data Race Prediction: Fundamentals and Advances"

Date: Monday, 4 April 2022

Time: 4:00pm - 5:00pm (Hong Kong Local time)

Zoom link:
https://hkust.zoom.us/j/928308079?pwd=MW9wTCtlSDd2MnViZGdNd2oreUpXZz09

Meeting ID:     928 308 079
Passcode:       20212022

Abstract:

Concurrent programs are notoriously hard to write correctly, as scheduling
nondeterminism introduces subtle errors that are both hard to detect and
to reproduce. Data races are arguably the most insidious amongst
concurrency bugs and extensive research efforts have been dedicated to
effectively detect them. A data race occurs when memory-conflicting
actions are executed concurrently. Consequently, considerable effort has
been made towards developing efficient techniques for race detection. The
preferred
approach to detect data races is through dynamic analysis, where one
observes an execution of a concurrent programs and checks for the presence
of data races in the execution observed. Traditional dynamic race
detectors rely on Lamport's happens-before (HB) partial order, which can
be
conservative and are often unable to discover simple data races, even
after executing the program several times.
Dynamic data race prediction aims to expose data races, that can be
otherwise missed by traditional dynamic race detectors (such as those
based on HB), by inferring data races in alternate executions of the
underlying program, without re-executing it. In this talk, I will talk
about the fundamentals of and recent algorithmic advances in data race
prediction.


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Biograpgy:

Umang Mathur is an Assistant Professor at the National University of
Singapore. He received his PhD from the University of Illinois at Urbana
Champaign in 2021 and was an NTT Research Fellow at the Simons Institute
for the Theory of Computing at Berkeley. His research interests lie in the
use of formal methods and logic for answering design, analysis and
implementation questions in programming languages, software engineering
and systems. He was a recipient of a Google PhD Fellowship, an ACM SIGSOFT
Distinguished Paper Award at ESEC/FSE'18, and a Best Paper Award at
ASPLOS'22. He was also one of the young scientists invited to the 8th
Heidelberg Laureate Forum.