Functional paradigm for designing dependable large-scale parallel computing systems

Bondavalli, Andrea; Simoncini, L.

doi:10.1109/isads.1993.262715

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…Quite apart the modelling of the physical environment as a part of the overall system which can be used as test case for the control system, the use of the data flow computational model for the description of the system specification allows the designer to use notations which are very natural and which can be made even more user friendly by the use of development tools like a graphical editor [4]. The transformation into process algebras specification allows the use of the analysis tools available in LOTOS, making the entire process from specification to verification and validation fully automated.…”

Section: Discussionmentioning

confidence: 99%

“…This makes data flow generally recognised as a convenient programming paradigm for the development of control systems. The referential transparency property admitted when nodes compute functions, by which two executions of the same node with the same input data produce equal output results, makes data flow "inherently fault tolerant": it is possible to tolerate simple failures by re-evaluating the same function on the same input data [4], [5]. If a non deterministic behaviour of nodes is allowed, still the strong isolation and information hiding enforces a good confinement useful for setting error confinement areas around modules by means of appropriate consistency checks.…”

Section: Introductionmentioning

confidence: 99%

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Data Flow Control Systems: an Example of Safety Validation

Bernardeschi

Simoncini

Bondavalli³

1993

Safecomp ’93

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In this paper a methodology to develop safety-critical control systems is proposed. These systems continuously interact with the physical environment, and those admitting at least one failure causing a catastrophe are classified as safety-critical. Our methodology takes into account both the control system (controller) and the physical environment (plant). After the requirements analysis, the system is developed following data flow model, i.e., described as a static data flow network of nodes executing concurrently and communicating asynchronously. The plant is used as the test case for the validation of the controller and their composition is analysed to show whether hazards are reached. To this purpose we apply a transformation from data flow networks to LOTOS specifications. The transformation preserves the semantics of the original network and data flow network properties can be derived and proved on the LOTOS specification using available support tools. A train set example for the contact-free moving of trains on a circular track divided into sections is shown as an application of the methodology.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data Flow Control Systems: an Example of Safety Validation

Bernardeschi

Simoncini

Bondavalli³

1993

Safecomp ’93

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“…In Bondavalli and Simoncini, 1993;Bernardeschi et al, 1993 a data ow computational model is proposed for allowing early analyses of control systems. In this model, the control system corresponds to a data ow network whose input and output events describe the interaction between the control system and its environment.…”

Section: Data Flow Network For Control Systemsmentioning

confidence: 99%