Safety-critical medical device development using the UPP2SF model translation tool
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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.
Published Version (Please cite this version)10.1145/2584651
Publication InfoJiang, Z; Lee, Insup; Mangharam, R; Pajic, M; & Sokolsky, O (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 http://hdl.handle.net/10161/11281.
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Nortel Networks Assistant Professor in the Pratt School of Engineering
Miroslav Pajic's research focuses on design and analysis of cyber-physical systems and in particular, embedded and distributed/networked control, real-time and embedded systems, and high-confidence medical device systems.