Automatic Data Race Error Detection in SystemC Models
Abstract
Hardware/software systems simulated by using the SystemC language are usually parallel and, therefore, may contain synchronization errors. One widespread type of synchronization errors is data races. In this paper we propose an approach to data race detection in SystemC programs which is based on the source code static analysis. We have developed some static analysis algorithms that can extract information for data race detection in a SystemC program without quantitative time. These algorithms can detect all the errors that exist in the program. The efficiency of our approach is shown by the evaluation results of the developed tool on a set of test SystemC programs.
About the Authors
A. V. Zakharov
Санкт-Петербургский государственный политехнический университет
Russian Federation
Russian Federation
M. J. Moiseev
Санкт-Петербургский государственный политехнический университет
Russian Federation
Russian Federation
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Review
For citations:
Zakharov A.V., Moiseev M.J. Automatic Data Race Error Detection in SystemC Models. Modeling and Analysis of Information Systems. 2011;18(4):94-105. (In Russ.)
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