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Shared Data Analysis for Multi-Tasking Real-Time System Testing
Publication Type:
Conference/Workshop Paper
Venue:
In proceedings of IEEE Second International Symposium on Industrial Embedded Systems, Lisbon, Portugal
Abstract
Memory corruption due to program faults is one of the most common
failures in computer software. For software running in a
sequential manner and for multi-tasking software with synchronized
data accesses, it has been shown that program faults causing memory
corruption can be detected by analyzing the relations between defines
and uses of variables (DU coverage-based testing).
However, using such methods in testing for memory corruption where
globally shared data is accessed through asynchronous events will not
be sufficient since they lack the possibility to analyse the cases
where preemption of tasks may lead to interleaving failures.
In this paper, we propose the use of a system level shared variable DU
analysis of multi-tasking real-time software. By analyzing the
temporal attributes of each access to globally shared data, our method
handles asynchronous data accesses. When used in system-level testing,
the result from the analysis can discover failures such as
ordering, synchronization and interleaving
failures. The result can also serve a as measure for coverage and
complexity in data dependency at system level.
Bibtex
@inproceedings{Pettersson1150,
author = {Anders Pettersson and Daniel Sundmark and Henrik Thane and Dag Nystr{\"o}m},
title = {Shared Data Analysis for Multi-Tasking Real-Time System Testing},
month = {June},
year = {2007},
booktitle = {In proceedings of IEEE Second International Symposium on Industrial Embedded Systems, Lisbon, Portugal},
url = {http://www.es.mdu.se/publications/1150-}
}