Compositional Performance Analysis in Python with pyCPA

نویسندگان

  • Jonas Diemer
  • Philip Axer
  • Rolf Ernst
چکیده

The timing behavior of current and future embedded and distributed systems becomes increasingly complex. At the same time, many application fields such as safety-critical systems require a verification of worst-case timing behavior. Deriving sound guarantees is a complex task, which can be solved by Compositional Performance Analysis. This approach formally computes worst-case timing scenarios on each component of the system and derives end-to-end system timing from these local analyses. In this paper, we present pyCPA, an open-source implementation of the Compositional Performance Analysis approach. Targeted towards academia, pyCPA offers features such as support for the most common real-time schedulers, path analysis for communicating tasks, import and export functionality, and different visualizations. Thus, pyCPA is a valuable contribution to the research domain.

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تاریخ انتشار 2012