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High-level real-time programming in Java
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Source International Conference On Embedded Software archive
Proceedings of the 5th ACM international conference on Embedded software table of contents
Jersey City, NJ, USA
SESSION: Languages table of contents
Pages: 68 - 78  
Year of Publication: 2005
ISBN:1-59593-091-4
Authors
David F. Bacon  IBM T.J. Watson Research Center
Perry Cheng  IBM T.J. Watson Research Center
David Grove  IBM T.J. Watson Research Center
Michael Hind  IBM T.J. Watson Research Center
V. T. Rajan  IBM T.J. Watson Research Center
Eran Yahav  IBM T.J. Watson Research Center
Matthias Hauswirth  Università della Svizzera Italiana
Christoph M. Kirsch  Universität Salzburg
Daniel Spoonhower  Carnegie-Mellon University, Pittsburgh, PA
Martin T. Vechev  University of Cambridge
Sponsors
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Real-time systems have reached a level of complexity beyond the scaling capability of the low-level or restricted languages traditionally used for real-time programming.While Metronome garbage collection has made it practical to use Java to implement real-time systems, many challenges remain for the construction of complex real-time systems, some specific to the use of Java and others simply due to the change in scale of such systems.The goal of our current research is the creation of a comprehensive Java-based programming environment and methodology for the creation of complex real-time systems. Our goals include construction of a provably correct real-time garbage collector capable of providing worst case latencies of 100 μs, capable of scaling from sensor nodes up to large multiprocessors; specialized programming constructs that retain the safety and simplicity of Java, and yet provide sub-microsecond latencies; the extension of Java's "write once, run anywhere" principle from functional correctness to timing behavior; on-line analysis and visualization that aids in the understanding of complex behaviors; and a principled probabilistic analysis methodology for bounding the behavior of the resulting systems.While much remains to be done, this paper describes the progress we have made towards these goals.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
David F. Bacon: colleagues
Perry Cheng: colleagues
David Grove: colleagues
Michael Hind: colleagues
V. T. Rajan: colleagues
Eran Yahav: colleagues
Matthias Hauswirth: colleagues
Christoph M. Kirsch: colleagues
Daniel Spoonhower: colleagues
Martin T. Vechev: colleagues