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Security is one of the most burning issues in embedded system design nowadays. The majority of strategies to secure embedded systems are being implemented in software. However, a potential hardware backdoor that allows unprivileged software access to confidential data will render even the perfectly secure software useless. As the underlying SoC cannot be patched after deployment, it is very critical...
Data flow testing (DFT) has been shown to be an effective testing strategy. DFT features a high fault detection rate while avoiding the intense scalability problems to achieve full path coverage. In this paper we propose to apply data flow testing for SystemC virtual prototypes (VPs). Our contribution is twofold: First, we develop a set of SystemC specific coverage criteria for data flow testing....
Fault-free function and defect tolerance are key requirements for modern embedded systems. To meet time-to-market constraints, complex IP-components are used to assemble even more complex semiconductor products. Often, trust is required since these IPs are developed, verified and tested by external third-party IP-providers. In this work, we focus specifically on processor-IPs. A method for run-time...
Error metrics are used to evaluate the quality of an approximated circuit or to trade-off several approximated candidates in design exploration. Precisely determining the error of an approximated circuit is a hard problem since the errors accumulate over time depending on the composition and nature of individual components. In this paper, we present methods based on model checking to precisely determine...
To overcome the verification gap arising from significantly increased external IP integration and reuse during electronic platform design and composition, we present a model-based approach to specify platform variants. The variants specification is processed automatically by formalizing and solving the integrated constraint sets to derive valid platforms. These constraint sets enable a precise specification...
Geographically Weighted Regression (GWR) is a method of spatial statistical analysis used to explore geographical differences in the effect of one or more predictor variables upon a response variable. However, as a form of local analysis, it does not scale well to (especially) large data sets because of the repeated processes of fitting and then comparing multiple regression surfaces. A solution is...
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