Abstract

Real-time systems engineers face a daunting duty: they must ensure that each task in their system can always meet its deadline. To analyse schedulability they must know the worst-case execution time (WCET) of each task. However, determining exact WCETs is practically infeasible in cost-constrained industrial settings involving real-life code and COTS hardware. Static analysis tools that could yield sufficiently tight WCET bounds are often unavailable. As a result, interest in portable analysis approaches like measurement-based timing analysis is growing. We present an approach based on integer linear programming (ILP) for calculating a WCET estimate from a given database of timed execution traces. Unlike previous work, our method specifically aims at reducing overestimation, by means of an automatic classification of code executions into scenarios with differing worst-case behaviour. To ease the integration into existing analysis tool chains, our method is based on the implicit path enumeration technique. It can thus reuse flow facts from other analysis tools and produces ILP problems that can be solved by off-the-shelf solvers.

Highlights

  • Modern software usually adopts a modular design with multiple interacting computational processes executing concurrently inside the system

  • Comparing the worst-case execution time (WCET) estimates produced by context-sensitive Implicit Path Enumeration Technique (IPET) to those produced by standard IPET, we see that the former results are closer to the maximal observed execution time (MOET) than the latter

  • We have presented context-sensitive IPET, an integer linear programming (ILP)-based approach for calculating a WCET estimate from a given database of timed execution traces

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Summary

Introduction

Modern software usually adopts a modular design with multiple interacting computational processes executing concurrently inside the system. These processes compete for shared system resources like memory space, processing time, etc. In real-time processor scheduling the demands of each process for processing time are specified by a set of task parameters. Measurement-based timing analysis (MBTA) (Bernat et al 2002, 2003; Kirner et al 2005;Wenzel et al 2009; Stattelmann and Martin 2010) proposes the calculation of WCET estimates from a database of timed execution traces of code runs on the target hardware. We present an IPET-based approach for calculating a WCET estimate from a given database of timed execution traces In Appendix 1 we present proofs for all theorems in the main part of the paper

Related work
The implicit path-enumeration technique
Pessimism and monotonicity
Context-sensitive IPET
Contexts
Timed traces and clips
Finding contexts for MBTA
The next step of the algorithm is a vertical context split
The algorithm sets
Instantiating context-sensitive IPET
The FORTAS high-precision MBTA framework
Benchmarks
Experiments and results
Conclusion
Full Text
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