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https://doi.org/10.1109/memcod...
Article . 2010 . Peer-reviewed
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Proving transaction and system-level properties of untimed SystemC TLM designs

Authors: Daniel Große; Hoang Minh Le 0001; Rolf Drechsler;

Proving transaction and system-level properties of untimed SystemC TLM designs

Abstract

Electronic System Level (ESL) design manages the enormous complexity of todays systems by using abstract models. In this context Transaction Level Modeling (TLM) is state-of-the-art for describing complex communication without all the details. As ESL language, SystemC has become the de facto standard. Since the SystemC TLM models are used for early software development and as reference for hardware implementation their correct functional behavior is crucial. Admittedly, the best possible verification quality can be achieved with formal approaches. However, formal verification of TLM models is a hard task. Existing methods basically consider local properties or have extremely high run-time. In contrast, the approach proposed in this paper can verify “true” TLM properties, i.e. major TLM behavior like for instance the effect of a transaction and that the transaction is only started after a certain event can be proven. Our approach works as follows: After a fully automatic SystemC-to-C transformation, the TLM property is mapped to monitoring logic using C assertions and finite state machines. To detect a violation of the property the approach uses a BMC-based formulation over the outermost loop of the SystemC scheduler. In addition, we improve this verification method significantly by employing induction on the C model forming a complete and efficient approach. As shown by experiments state-of-the-art proof techniques allow proving important non-trivial behavior of SystemC TLM designs.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Top 10%
Top 10%