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  1. Letters on Programming Languages and Systems (LOPLAS)
  2. ACM Letters on Programming Languages and Systems (LOPLAS) : Volume 1
  3. Issue 1, March 1992
  4. What are race conditions?: Some issues and formalizations
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ACM Letters on Programming Languages and Systems (LOPLAS) : Volume 2
ACM Letters on Programming Languages and Systems (LOPLAS) : Volume 1
Issue 4, Dec 1992
Issue 3, Sept 1992
Issue 2, June 1992
Issue 1, March 1992
Coloring register pairs
Precise and efficient integration of interprocedural alias information into data-flow analysis
Unexpected side effects of inline substitution: a case study
Polymorphic time systems for estimating program complexity
Reducing the latency of a real-time garbage collector
Generating parallel code for SIMD machines
What are race conditions?: Some issues and formalizations
On reasoning with the global time assumption

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Technical Report

What are race conditions?: Some issues and formalizations

Content Provider ACM Digital Library
Author Netzer, Robert H. B. Miller, Barton P.
Copyright Year 1992
Abstract In shared-memory parallel programs that use explicit synchronization, race conditions result when accesses to shared memory are not properly synchronized. Race conditions are often considered to be manifestations of bugs, since their presence can cause the program to behave unexpectedly. Unfortunately, there has been little agreement in the literature as to precisely what constitutes a race condition. Two different notions have been implicitly considered: one pertaining to programs intended to be deterministic (which we call general races) and the other to nondeterministic programs containing critical sections (which we call data races). However, the differences between general races and data races have not yet been recognized. This paper examines these differences by characterizing races using a formal model and exploring their properties. We show that two variations of each type of race exist: $\textit{feasible}$ general races and data races capture the intuitive notions desired for debugging and $\textit{apparent}$ races capture less accurate notions implicitly assumed by most dynamic race detection methods. We also show that locating feasible races is an NP-hard problem, implying that only the apparent races, which are approximations to feasible races, can be detected in practice. The complexity of dynamically locating apparent races depends on the type of synchronization used by the program. Apparent races can be exhaustively located efficiently only for weak types of synchronization that are incapable of implementing mutual exclusion. This result has important implications since we argue that debugging general races requires exhaustive race detection and is inherently harder than debugging data races (which requires only partial race detection). Programs containing data races can therefore be efficiently debugged by locating certain easily identifiable races. In contrast, programs containing general races require more complex debugging techniques.
Starting Page 74
Ending Page 88
Page Count 15
File Format PDF
ISSN 10574514
e-ISSN 15577384
DOI 10.1145/130616.130623
Volume Number 1
Issue Number 1
Journal ACM Letters on Programming Languages and Systems (LOPLAS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 1992-03-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Critical sections Data races Debugging Nondeterminacy Parallel programs Race conditions
Content Type Text
Resource Type Article
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