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“Carbon Credits” for Resource-Bounded Computations Using Amortised Analysis

  • Steffen Jost
  • Hans-Wolfgang Loidl
  • Kevin Hammond
  • Norman Scaife
  • Martin Hofmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5850)

Abstract

Bounding resource usage is important for a number of areas, notably real-time embedded systems and safety-critical systems. In this paper, we present a fully automatic static type-based analysis for inferring upper bounds on resource usage for programs involving general algebraic datatypes and full recursion. Our method can easily be used to bound any countable resource, without needing to revisit proofs. We apply the analysis to the important metrics of worst-case execution time, stack- and heap-space usage. Our results from several realistic embedded control applications demonstrate good matches between our inferred bounds and measured worst-case costs for heap and stack usage. For time usage we infer good bounds for one application. Where we obtain less tight bounds, this is due to the use of software floating-point libraries.

Keywords

Operational Semantic Inverted Pendulum Carbon Credit Share Rule Resource Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Steffen Jost
    • 1
  • Hans-Wolfgang Loidl
    • 2
  • Kevin Hammond
    • 1
  • Norman Scaife
    • 3
  • Martin Hofmann
    • 2
  1. 1.St Andrews UniversitySt AndrewsScotland, UK
  2. 2.Ludwig-Maximilians UniversityMunichGermany
  3. 3.Université Blaise-PascalClermont-FerrandFrance

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