Embedded program timing analysis based on path clustering and architecture classification
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Combining multiple models of computation for scheduling and allocation
Proceedings of the 6th international workshop on Hardware/software codesign
Efficient and Precise Cache Behavior Prediction for Real-TimeSystems
Real-Time Systems
Execution cost interval refinement in static software analysis
Journal of Systems Architecture: the EUROMICRO Journal - Modern methods and tools in digital system design
Performance Analysis of Real-Time Embeded Software
Performance Analysis of Real-Time Embeded Software
Behavioral Intervals in Embedded Software: Timing and Power Analysis of Embedded Real-Time Software Processes
WCET Analysis of Probabilistic Hard Real-Time Systems
RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
Context-Aware Performance Analysis for Efficient Embedded System Design
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Formal Methods for Integration of Automotive Software
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe: Designers' Forum - Volume 2
A full lifecycle performance verification methodology for multicore systems-on-chip
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special section on verification challenges in the concurrent world
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Accurate timing analysis is key to efficient embedded system synthesis and integration. While industrial control software systems are developed using graphical models, such as Matlab/Simulink or ASCET/SD, exhaustive simulation is not suitable for verifying functional and timing behavior. Formal performance analysis is an alternative but can lead to wide timing intervals because of input data dependency and complex target architectures. Hence a designer might want to restrict the formal performance analysis to parts of the software system, called context or process modes. In this paper, we describe how to define and characterize such context information from graphical models. Further, we extend the formal performance analysis to consider contexts. Results from an automotive application demonstrate the applicability of our approach.