The C programming language
A calculus of mobile processes, I
Information and Computation
Backpropagation: theory, architectures, and applications
Backpropagation: theory, architectures, and applications
The B-book: assigning programs to meanings
The B-book: assigning programs to meanings
Communicating sequential processes
Communications of the ACM
The Theory and Practice of Concurrency
The Theory and Practice of Concurrency
Artificial Neural Networks
A grammar of integrity constraints in medical documentation systems
Computer Methods and Programs in Biomedicine
ProB: an automated analysis toolset for the B method
International Journal on Software Tools for Technology Transfer (STTT)
Formal interaction specification in public health surveillance systems using π-calculus
Computer Methods and Programs in Biomedicine
Model checking of healthcare domain models
Computer Methods and Programs in Biomedicine
Combining CSP and b for specification and property verification
FM'05 Proceedings of the 2005 international conference on Formal Methods
A systematic approach to embedded biomedical decision making
Computer Methods and Programs in Biomedicine
Designing offshore fish cages using systems engineering principles
Systems Engineering
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Systems engineering aims to produce reliable systems which function according to specification. In this paper we follow a systems engineering approach to design a biomedical signal processing system. We discuss requirements capturing, specification definition, implementation and testing of a classification system. These steps are executed as formal as possible. The requirements, which motivate the system design, are based on diabetes research. The main requirement for the classification system is to be a reliable component of a machine which controls diabetes. Reliability is very important, because uncontrolled diabetes may lead to hyperglycaemia (raised blood sugar) and over a period of time may cause serious damage to many of the body systems, especially the nerves and blood vessels. In a second step, these requirements are refined into a formal CSP@? B model. The formal model expresses the system functionality in a clear and semantically strong way. Subsequently, the proven system model was translated into an implementation. This implementation was tested with use cases and failure cases. Formal modeling and automated model checking gave us deep insight in the system functionality. This insight enabled us to create a reliable and trustworthy implementation. With extensive tests we established trust in the reliability of the implementation.