Resource Analysis by Sup-interpretation
Identifieur interne : 002718 ( Istex/Corpus ); précédent : 002717; suivant : 002719Resource Analysis by Sup-interpretation
Auteurs : Jean-Yves Marion ; Romain PéchouxSource :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: We propose a new method to control memory resources by static analysis. For this, we introduce the notion of sup-interpretation which bounds from above the size of function outputs. We establish a criteria for which the stack frame size is polynomially bounded. The criteria analyses terminating as well as non-terminating programs. This method applies to first order functional programming with pattern matching. This work is related to quasi-interpretations but we are now able to determine resources of different algorithms and it is easier to perform an analysis with this new tools.
Url:
DOI: 10.1007/11737414_12
Links to Exploration step
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<Para>We propose a new method to control memory resources by static analysis. For this, we introduce the notion of sup-interpretation which bounds from above the size of function outputs. We establish a criteria for which the stack frame size is polynomially bounded. The criteria analyses terminating as well as non-terminating programs. This method applies to first order functional programming with pattern matching. This work is related to quasi-interpretations but we are now able to determine resources of different algorithms and it is easier to perform an analysis with this new tools.</Para>
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<abstract lang="en">Abstract: We propose a new method to control memory resources by static analysis. For this, we introduce the notion of sup-interpretation which bounds from above the size of function outputs. We establish a criteria for which the stack frame size is polynomially bounded. The criteria analyses terminating as well as non-terminating programs. This method applies to first order functional programming with pattern matching. This work is related to quasi-interpretations but we are now able to determine resources of different algorithms and it is easier to perform an analysis with this new tools.</abstract>
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