Safety-critical medical device development using the UPP2SF model translation tool
Abstract
Software-based control of life-critical embedded systems has become increasingly complex,
and to a large extent has come to determine the safety of the human being. For example,
implantable cardiac pacemakers have over 80,000 lines of code which are responsible
for maintaining the heart within safe operating limits. As firmware-related recalls
accounted for over 41% of the 600,000 devices recalled in the last decade, there is
a need for rigorous model-driven design tools to generate verified code from verified
software models. To this effect, we have developed the UPP2SF model-translation tool,
which facilitates automatic conversion of verified models (in UPPAAL) to models that
may be simulated and tested (in Simulink/Stateflow). We describe the translation rules
that ensure correct model conversion, applicable to a large class of models. We demonstrate
how UPP2SF is used in themodel-driven design of a pacemaker whosemodel is (a) designed
and verified in UPPAAL (using timed automata), (b) automatically translated to Stateflow
for simulation-based testing, and then (c) automatically generated into modular code
for hardware-level integration testing of timing-related errors. In addition, we show
how UPP2SF may be used for worst-case execution time estimation early in the design
stage. Using UPP2SF, we demonstrate the value of integrated end-to-end modeling, verification,
code-generation and testing process for complex software-controlled embedded systems.
© 2014 ACM.
Type
Journal articlePermalink
https://hdl.handle.net/10161/11281Published Version (Please cite this version)
10.1145/2584651Publication Info
Pajic, M; Jiang, Z; Lee, I; Sokolsky, O; & Mangharam, R (2014). Safety-critical medical device development using the UPP2SF model translation tool.
Transactions on Embedded Computing Systems, 13(4 SPEC. ISSUE). 10.1145/2584651. Retrieved from https://hdl.handle.net/10161/11281.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Miroslav Pajic
Dickinson Family Associate Professor
Miroslav Pajic's research focuses on design and analysis of cyber-physical systems
with varying levels of autonomy and human interaction, at the intersection of (more
traditional) areas of embedded systems, AI, learning and controls, formal methods
and robotics.

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