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 ABSTRACT
A PROGRAM with a number of subroutines can be represented by a flow diagram; Figure 1. The nodes represent the subroutines and the directed branches indicate the allowed transitions between them. Given a program consisting of n subroutines R1, R2 .....Rn, two matrices are also assumed to be known, viz., an n × 1 matrix of execution times of each subroutine and a n × n matrix P, such that its ij-th element Pij is the branching probability that the program will branch to subroutine j from subroutine i. We shall assume Pij's are statistically independent so that the model of the computer program is that of a discrete Markov process. The expected time to complete a program is then a summation of all possible statistically weighted paths that begin at an initial or starting subroutine and end at the terminal subroutine.
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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Mason, S. J., "Further Properties of Flow Graphs," Proc. IRE; July, 1956.
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Ramamoorthy, C. V., "Representation and Analysis of Discrete Systems by Generating Functions of Astract Graphs," IEEE International Convention Record; 1965.
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Howard, R. A., "Dynamic Programming and Markov Processes," Wiley; 1960.
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Feller, W., "An Introduction to Probability Theory and Its Applications," Wiley; 1957.
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Karp, R., Ph.D. Thesis, Harvard University; 1959.
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Ramamoorthy, C. V., Ph.D. Thesis, Harvard University; May, 1964.
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CITED BY 11
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Virginie Galtier , Kevin L. Mills , Yannick Carlinet , Stefan Leigh , Andrew Rukhin, Expressing meaningful processing requirements among heterogeneous nodes in an active network, Proceedings of the 2nd international workshop on Software and performance, p.20-28, September 2000, Ottawa, Ontario, Canada
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