Signal and image processing applications require a lot of computing resources. For low-volume applications like in professional electronics applications, FPGA are used in combination with DSP and GPP in order to reach the performances required by the product roadmaps. Nevertheless, FPGA designs are static, which raises a flexibility issue with new complex or software defined applications like software-defined radio (SDR). In this scope, dynamic partial reconfiguration (DPR) is used to bring a virtualization layer upon the static hardware of FPGA. During the last decade, DPR has been widely studied in academia. Nevertheless, there are very few real applications using it, and therefore, there is a lack of feedback providing relevant issues to address in order to improve its applicability. This paper evaluates the interest and limitations when using DPR in professional electronics applications and provides guidelines to improve its applicability. It makes a fair evaluation based on experiments made on a set of signal and image processing applications. It identifies the missing elements of the design flow to use DPR in professional electronics applications. Finally, it introduces a fast reconfiguration manager providing an 84-time improvement compared to the vendor solution.

In systems engineering, the deployment of software components is error-prone since numerous safety and security rules have to be preserved. Furthermore, many deployments on different heterogeneous platforms are possible. In this paper we present a technological solution to assist industrial practitioners in producing a safe and secure solution out of numerous architectural variants. First, we introduce a pattern technology that provides correct-by-construction deployment models through the reuse of modeling artifacts organized in a catalog. Second, we develop a variability solution, connected to the pattern technology and based on an extension of the common variability language, for supporting the synthesis of model-based architectural variants. This paper describes a live demonstration of an industrial effort seeking to bridge the gap between variability modeling and model-based systems engineering practices. We illustrate the tooling support with an industrial case study (a secure radio platform).

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In systems engineering, practitioners shall explore numerous architectural alternatives until choosing the most adequate variant. The decision-making process is most of the time a manual, time-consuming, and error-prone activity. The exploration and justification of architectural solutions is ad-hoc and mainly consists in a series of tries and errors on the modeling assets. In this paper, we report on an industrial case study in which we apply variability modeling techniques to automate the assessment and comparison of several candidate architectures (variants). We first describe how we can use a model-based approach such as the Common Variability Language (CVL) to specify the architectural variability. We show that the selection of an architectural variant is a multi-criteria decision problem in which there are numerous interactions (veto, favor, complementary) between criteria. We present a tooled process for exploring architectural variants integrating both CVL and the MYRIAD method for assessing and comparing variants based on an explicit preference model coming from the elicitation of stakeholders' concerns. This solution allows understanding differences among variants and their satisfactions with respect to criteria. Beyond variant selection automation improvement, this experiment results highlight that the approach improves rationality in the assessment and provides decision arguments when selecting the preferred variants.