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Ascertaining Uncertainty for Efficient Exact Cache Analysis: Tech report. Extended version of CAV 2017 "Ascertaining Uncertainty for Efficient Exact Cache Analysis" paper

Abstract : Static cache analysis characterizes a program’s cache behavior by determining in a sound but approximate manner which memory accesses result in cache hits and which result in cache misses. Such information is valuable in optimizing compilers, worst-case execution time analysis, and side-channel attack quantification and mitigation. Cache analysis is usually performed as a combination of “must” and “may” abstract interpretations, classifying instructions as either “always hit”, “always miss”, or “unknown”. Instructions classified as “unknown” might result in a hit or a miss depending on program inputs or the initial cache state. It is equally possible that they do in fact always hit or always miss, but the cache analysis is too coarse to see it. Our approach to eliminate this uncertainty consists in (i) a novel abstract interpretation able to ascertain that a particular instruction may definitely cause a hit and a miss on different paths, and (ii) an exact analysis, removing all remaining uncertainty, based on model checking, using abstract-interpretation results to prune down the model for scalability. We evaluated our approach on a variety of examples; it notably improves precision upon classical abstract interpretation at reasonable cost.
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https://hal.archives-ouvertes.fr/hal-01592048
Contributor : Valentin Touzeau Connect in order to contact the contributor
Submitted on : Tuesday, December 18, 2018 - 5:19:59 PM
Last modification on : Tuesday, January 25, 2022 - 10:16:49 PM
Long-term archiving on: : Wednesday, March 20, 2019 - 9:01:15 AM

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Claire Maïza, Valentin Touzeau, David Monniaux, Jan Reineke. Ascertaining Uncertainty for Efficient Exact Cache Analysis: Tech report. Extended version of CAV 2017 "Ascertaining Uncertainty for Efficient Exact Cache Analysis" paper. Computer Aided Verification - 29th International Conference, Rupak Majumdar; Viktor Kuncak, Jul 2017, Heidelberg, France. pp.20 - 40, ⟨10.1007/978-3-319-63390-9_2⟩. ⟨hal-01592048v2⟩

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