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Cited by 1,871

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The worst-case execution-time problem—overview of methods and survey of tools

Wilhelm, Reinhard, Engblom, Jakob, Ermedahl, Andreas, Holsti, Niklas, Thesing, Stephan, Whalley, David, Bernat, Guillem, Ferdinand, Christian, Heckmann, Reinhold, Mitra, Tulika, Mueller, Frank, Puaut, Isabelle, Puschner, Peter, Staschulat, Jan, Stenström, Per·2008·ACM Transactions on Embedded Computing Systems

Abstract

The determination of upper bounds on execution times, commonly called worst-case execution times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components, such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools 1 and research prototypes.

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Metadata

Authors
Wilhelm, R., Engblom, J., Ermedahl, A., Holsti, N., Thesing, S., Whalley, D., Bernat, G., Ferdinand, C., Heckmann, R., Mitra, T., Mueller, F., Puaut, I., Puschner, P., Staschulat, J., & Stenström, P.
Venue
ACM Transactions on Embedded Computing Systems
Published
2008-04
Volume
7
Issue
3
Pages
1-53
ISSN
  • 1539-9087 (ISSN-L)
  • 1558-3465
OpenAlex
W2076285066
Cited by
1,871
References
1
FWCI
248.41
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The worst-case execution-time problem—overview of methods and survey of tools. https://app.cochat.ai/papers/10.1145/1347375.1347389
The paper
Wilhelm, R., Engblom, J., Ermedahl, A., Holsti, N., Thesing, S., Whalley, D., Bernat, G., Ferdinand, C., Heckmann, R., Mitra, T., Mueller, F., Puaut, I., Puschner, P., Staschulat, J., & Stenström, P. (2008). The worst-case execution-time problem—overview of methods and survey of tools. ACM Transactions on Embedded Computing Systems. https://doi.org/10.1145/1347375.1347389

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.