Position paper for the Workshop on Dependability Benchmarking, affiliated with the International Conference on Dependable Systems and Networks (DSN-2002).
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Many of the software systems we use for everyday purposes incorporate
elements developed and maintained by third parties. These elements include not
only code components and data bases but also dynamic data feeds from online data
sources. Even though everyday software is not mission critical it must be
dependable enough for its intended use. This is limited by the dependability of
its constituting elements.
It is especially difficult to assess the dependability of dynamic data feeds
because they exhibit not only "fail-silent" behavior but also semantic
failures -- delivery of unreasonable yet well structured results by a responsive
data feed. Further, it is normal for the behavior of such data feeds to
change. Unfortunately, the specifications of these data feeds are often
too incomplete and sketchy to support failure detection.
We propose an approach for benchmarking the semantic availability of redundant
data feeds. The fault model is defined as violations of inferred invariants
about the usual behavior of a data feed.
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