Concurrency control and recovery in database systems
Concurrency control and recovery in database systems
Programming with POSIX threads
Programming with POSIX threads
Eraser: a dynamic data race detector for multithreaded programs
ACM Transactions on Computer Systems (TOCS)
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Control Flow Optimization Via Dynamic Reconvergence Prediction
Proceedings of the 37th annual IEEE/ACM International Symposium on Microarchitecture
A serializability violation detector for shared-memory server programs
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
RaceTrack: efficient detection of data race conditions via adaptive tracking
Proceedings of the twentieth ACM symposium on Operating systems principles
Associating synchronization constraints with data in an object-oriented language
Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Learning from mistakes: a comprehensive study on real world concurrency bug characteristics
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Dynamic detection of atomic-set-serializability violations
Proceedings of the 30th international conference on Software engineering
On-the-fly race detection in multi-threaded programs
PADTAD '08 Proceedings of the 6th workshop on Parallel and distributed systems: testing, analysis, and debugging
Helgrind+: An efficient dynamic race detector
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
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In parallel programs concurrency bugs are often caused by unsynchronized accesses to shared memory locations, which are called data races. In order to support programmers in writing correct parallel programs, it is therefore highly desired to have tools on hand that automatically detect such data races. Today, most of these tools only consider unsynchronized read and write operations on a single memory location. Concurrency bugs that involve multiple accesses on a set of correlated variables may be completely missed. Tools may overwhelm programmers with data races on various memory locations, without noticing that the locations are correlated. In this paper, we propose a novel approach to data race detection that automatically infers sets of correlated variables and logical operations by analyzing data and control dependencies. For data race detection itself, we combine a modified version of the lockset algorithm with happens-before analysis providing the first hybrid, dynamic race detector for correlated variables. We implemented our approach on top of the Valgrind, a framework for dynamic binary instrumentation. Our evaluation confirmed that we can catch data races missed by existing detectors and provide additional information for correct bug fixing.