The Manchester prototype dataflow computer
Communications of the ACM - Special section on computer architecture
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Monitors: an operating system structuring concept
Communications of the ACM
VAL- ORIENTED ALGORITHMIC LANGUAGE, PRELIMINARY REFERENCE MANUAL
VAL- ORIENTED ALGORITHMIC LANGUAGE, PRELIMINARY REFERENCE MANUAL
An object-oriented approach to graphical interfaces
ACM Transactions on Graphics (TOG)
Impulse-86: a substrate for object-oriented interface design
OOPLSA '86 Conference proceedings on Object-oriented programming systems, languages and applications
Automatic programming for streams II: transformational implementation
ICSE '88 Proceedings of the 10th international conference on Software engineering
Using weaves for software construction and analysis
ICSE '91 Proceedings of the 13th international conference on Software engineering
An Overview of a Graphical Multilanguage Applications Environment
IEEE Transactions on Software Engineering
Automatic programming for streams
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
OptionStream: An automated system for tracking derivative effects on equity prices
Expert Systems with Applications: An International Journal
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The Stream Machine is a software architecture designed to support the development and evolution, as well as the efficient execution, of software that performs both data acquisition and process control under real-time constraints. A stream machine program consists of a set of concurrently executing modules communicating through streams of data. Streams provide essentially a data flow style of communication, thereby supporting deterministic data acquisition and calculation. The basic constructs have been augmented by several time-based operations to support process control software. In addition, explicit declarations of timing constraints layered on Stream Machine programs are currently being explored for resource allocation and scheduling. Our experience to date with two implementations of the Stream Machine suggests that it facilitates the mixture of software that performs both data acquisition and process control.