Annotate once – analyze anywhere: context-aware WCET analysis by user-defined abstractions
Annotate once – analyze anywhere: context-aware WCET analysis by user-defined abstractions
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一次注释,随处分析:通过用户定义的抽象进行上下文感知的 WCET 分析
DOI:
10.1145/3461648.3463847
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
W. Schröder-Preikschat
中科院分区:
文献类型:
--
作者:
S. Schuster;P. Wägemann;P. Ulbrich;W. Schröder-Preikschat
The widespread adoption of cyber-physical systems in the safety-critical (hard real-time) domain is accompanied by a rising degree of code-reuse up to actual software product lines spanning different hardware platforms. Nevertheless, the dominant tools for static worst-case execution-time (WCET) analysis operate on individual, specific system instances at the binary level, further depending on machine-code–level annotations for precise analysis. Thus, this timing verification is neither portable nor reusable.PragMetis addresses this schism by providing an expressive source-level annotation language that enables to express context dependence at the library level using user-defined abstractions. These abstractions allow users to generically annotate context-dependent flow facts down to the granularity of individual loop contexts. We then use control-flow–relation graphs to transfer these facts to machine-code level for specific instances, even in the presence of certain compiler optimizations, thus achieving portability. Our evaluation results based on TACLeBench confirm that PragMetis's powerful expressions yield more accurate WCET bounds.
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DOI:
--
发表时间:
2009
期刊:
International Conference on Embedded Software and Systems
影响因子:
--
作者:
Mingsong Lv;Nan Guan;Yi Zhang;Qingxu Deng;Ge Yu;Jianming Zhang
通讯作者:
Jianming Zhang
DOI:
--
发表时间:
2002
期刊:
影响因子:
--
作者:
N. Holsti;S. Saarinen
通讯作者:
S. Saarinen
DOI:
--
发表时间:
2000
期刊:
European Signal Processing Conference
影响因子:
--
作者:
N. Holsti;T. Långbacka;S. Saarinen
通讯作者:
S. Saarinen
DOI:
--
发表时间:
2012
期刊:
Worst-Case Execution Time Analysis
影响因子:
--
作者:
Benedikt Huber;Daniel Prokesch;P. Puschner
通讯作者:
P. Puschner
影响因子:
1.4
作者:
J. Knoop;L. Kovács;Jakob Zwirchmayr
通讯作者:
Jakob Zwirchmayr