Name
Abstract | ||
|---|---|---|
We propose an approach for timing analysis of software-based embedded computer systems that builds on the established probabilistic framework of Bayesian networks. We envision an approach where we take (1) an abstract description of the control flow within a piece of software, and (2) a set of run-time traces, which are combined into a Bayesian network that can be seen as an interactive timing profile. The obtained profile can be used by the embedded systems engineer not only to obtain a probabilistic estimate of the WCET, but also to run interactive timing simulations, or to automat- ically identify software configurations that are likely to evoke noteworthy timing behavior, like, e.g., high variances of execution times, and which are therefore candidates for further inspection. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.4230/OASIcs.WCET.2008.1669 | WCET |
Keywords | Field | DocType |
probabilistic modeling,embedded systems,profiling,measurement-based execu- tion time analysis,bayesian networks,real-time systems,software modeling,hardware modeling,bayesian network,probabilistic model,embedded system,real time systems,embedded computing,control flow,timing analysis | Data mining,Computer science,Control flow,Software,Static timing analysis,Bayesian network,Probabilistic logic,Probabilistic framework | Conference |
Citations | PageRank | References |
2 | 0.41 | 8 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Zolda | 1 | 42 | 3.57 |