On-the-fly detection of access anomalies
PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
An empirical comparison of monitoring algorithms for access anomaly detection
PPOPP '90 Proceedings of the second ACM SIGPLAN symposium on Principles & practice of parallel programming
Improving the accuracy of data race detection
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Race Frontier: reproducing data races in parallel-program debugging
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Detecting access anomalies in programs with critical sections
PADD '91 Proceedings of the 1991 ACM/ONR workshop on Parallel and distributed debugging
On-the-fly detection of data races for programs with nested fork-join parallelism
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
On-the-fly detection of access anomalies in nested parallel loops
PADD '93 Proceedings of the 1993 ACM/ONR workshop on Parallel and distributed debugging
Clock Trees: Logical Clocks for Programs with Nested Parallelism
IEEE Transactions on Software Engineering
Scalable on-the-fly detection of the first races in parallel programs
ICS '98 Proceedings of the 12th international conference on Supercomputing
Protocol-based data-race detection
SPDT '98 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Parallel Loop Transformation Technique for Efficient Race Detection
ICPADS '01 Proceedings of the Eighth International Conference on Parallel and Distributed Systems
| Hi-index | 0.00 |
Detecting data race is an important debugging problem that should be solved in the shared-memory parallel programs. To attack this problem, considerable works have been developed in the literature. In particular, detecting data races on-the-fly is regarded as more efficient strategy. However, the time and space overhead required to perform the technique on-the-fly is still considered as a serious problem. This paper presents a practical method to improve the problem. The target model of our method for detecting data race on-the-fly is the shared-memory programs with nested fork-join parallelism. The method presented here shows that it is more efficient in the complexity of space and time over previous techniques. Thus, it makes the technique for detecting data race on-the-fly more practical. The worst-case of space and time required to apply our method to the parallel programs are O(VT) and O(T) respectively.