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The paper describes a model-integrated approach for embedded software development that is based on domain-specific, multiple-view models used in all phases of the development process. Models explicitly represent the embedded software and the environment it operates in, and capture the requirements and the design of the application, simultaneously. Models are descriptive, in the sense that they allow the formal analysis, verification, and validation of the embedded system at design time. Models are also generative, in the sense that they carry enough information for automatically generating embedded systems using the techniques of program generators. Because of the widely varying nature of embedded systems, a single modeling language may not be suitable for all domains; thus, modeling languages are often domain-specific. To decrease the cost of defining and integrating domain-specific modeling languages and corresponding analysis and synthesis tools, the model-integrated approach is applied in a metamodeling architecture, where formal models of domain-specific modeling languages-called metamodels-play a key role in customizing and connecting components of tool chains. This paper discusses the principles and techniques of model-integrated embedded software development in detail, as well as the capabilities of the tools supporting the process. Examples in terms of real systems will be given that illustrate how the model-integrated approach addresses the physical nature, the assurance issues, and the dynamic structure of embedded software.

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Objective To determine whether automated identification with physician notification of the systemic inflammatory response syndrome in medical intensive care unit (MICU) patients expedites early administration of new antibiotics or improvement of other patient outcomes in patients with sepsis. Design A prospective, randomized, controlled, single-center study. Setting MICU of an academic, tertiary-care medical center. Patients 442 consecutive patients admitted over a 4 month period who met modified SIRS criteria in a MICU. Intervention Patients were randomized to monitoring by an electronic “Listening Application” to detect modified (SIRS) criteria vs. usual care. The Listening Application notified physicians in real-time when modified SIRS criteria were detected, but did not provide management recommendations. Measurements and Main Results The median time to new antibiotics was similar between the intervention and usual care groups whether comparing among all patients (6.0h vs 6.1h, p=0.95), patients with sepsis (5.3h vs. 5.1h; p=0.90), patients on antibiotics at enrollment (5.2h vs. 7.0h, p= 0.27), or patients not on antibiotics at enrollment (5.2h vs. 5.1h, p= 0.85). The amount of fluid administered following detection of modified SIRS criteria was similar between groups whether comparing all patients or only patients hypotensive at enrollment. Other clinical outcomes including ICU length of stay, hospital length of stay, and mortality were not shown to be different between patients in the intervention and control groups. Conclusions Real-time alerts of modified SIRS criteria to physicians in one tertiary care MICU were feasible and safe but did not influence measured therapeutic interventions for sepsis or significantly alter clinical outcomes.

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