A New Empirical Test for the Quality of Random Integer Generators

Jacob Savir

doi:10.1109/TC.1983.1676142

A New Empirical Test for the Quality of Random Integer Generators

Jacob Savir

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

In a number of applications, it is necessary to generate stimuli: to generate random patterns when random testing of logic faults is employed, and to generate the random occurrence of events when simulation is used, to mention two. In this paper, we show a quick empirical test, which is based on a data compression method, to analyze the pseudorandom integers generated by certain types of random integer generators and to determine whether the approximation to a true random process is good.

Original language	English (US)
Pages (from-to)	960-961
Number of pages	2
Journal	IEEE Transactions on Computers
Volume	C-32
Issue number	10
DOIs	https://doi.org/10.1109/TC.1983.1676142
State	Published - Oct 1983
Externally published	Yes

All Science Journal Classification (ASJC) codes

Software
Theoretical Computer Science
Hardware and Architecture
Computational Theory and Mathematics

Keywords

Confidence interval
mean
random integer generator
variance

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10.1109/TC.1983.1676142

Cite this

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AB - In a number of applications, it is necessary to generate stimuli: to generate random patterns when random testing of logic faults is employed, and to generate the random occurrence of events when simulation is used, to mention two. In this paper, we show a quick empirical test, which is based on a data compression method, to analyze the pseudorandom integers generated by certain types of random integer generators and to determine whether the approximation to a true random process is good.

KW - Confidence interval

KW - mean

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KW - variance

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A New Empirical Test for the Quality of Random Integer Generators

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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