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Contract-Based Integration of Cyber-Physical Analyses

Ivan Ruchkin, Dio De Niz, Sagar Chaki and David Garlan.


In Embedded Systems Week, 12-17 October 2014.

Online links: PDF

Abstract
Developing cyber-physical systems involves creating systems with properties from multiple domains, e.g., timing, logical correctness, thermal resilience, aerodynamics, and mechanical stress. In today�s industrial practice, multiple analyses are used to obtain and verify such properties. Unfortunately, given that these analyses originate from different scientific domains, they abstract away interactions among themselves, risking the invalidation of their results. Specifically, one challenge is to ensure that an analysis is never applied to a model that violates its assumptions. Since such violation can originate from the updating of the model by another analysis, analyses must be executed in the correct order. Another challenge is to do this soundly and scalably over models of realistic complexity and diverse set of analyses. To address these challenges, we develop an analysis integration approach that uses contracts to specify dependencies between analyses, determine their correct orders of application, and specify and verify applicability conditions across multiple domains. We present an implementation of our approach, and demonstrate its effectiveness, extensibility, and scalability.

Keywords: Cyberphysical Systems, Landmark.  
@InProceedings{2014/Ruchkin/CBI,
      AUTHOR = {Ruchkin, Ivan and De Niz, Dio and Chaki, Sagar and Garlan, David},
      TITLE = {Contract-Based Integration of Cyber-Physical Analyses},
      YEAR = {2014},
      MONTH = {12-17 October},
      BOOKTITLE = {Embedded Systems Week},
      PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/paper-camera-ready-ieee-verified-178-EM82.pdf},
      ABSTRACT = {Developing cyber-physical systems involves creating systems with properties from multiple domains, e.g., timing, logical correctness, thermal resilience, aerodynamics, and mechanical stress. In today�s industrial practice, multiple analyses are used to obtain and verify such properties. Unfortunately, given that these analyses originate from different scientific domains, they abstract away interactions among themselves, risking the invalidation of their results. Specifically, one challenge is to ensure that an analysis is never applied to a model that violates its assumptions. Since such violation can originate from the updating of the model by another analysis, analyses must be executed in the correct order. Another challenge is to do this soundly and scalably over models of realistic complexity and diverse set of analyses. To address these challenges, we develop an analysis integration approach that uses contracts to specify dependencies between analyses, determine their correct orders of application, and specify and verify applicability conditions across multiple domains. We present an implementation of our approach, and demonstrate its effectiveness, extensibility, and scalability.},
      KEYWORDS = {Cyberphysical Systems, Landmark}
}
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