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Fractal structure of random programs

Authors:

Peter Kokol,

Janez BrestAuthors Info & Claims

ACM SIGPLAN Notices, Volume 33, Issue 6

Pages 33 - 38

https://doi.org/10.1145/284563.284572

Published: 01 June 1998 Publication History

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Abstract

We constructed a generator of random programs and with the comparison of random and ordinary programs we showed that the long range correlation characteristic coefficient can be used as a measure of the semantic structure of software.

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Coleman RRahtelli M(2017)A Fractal Geometry Approach to Quantifying Aesthetic Values in Scientific Codes2017 International Conference on Computational Science and Computational Intelligence (CSCI)10.1109/CSCI.2017.160(922-927)Online publication date: Dec-2017
https://doi.org/10.1109/CSCI.2017.160
Coleman RJohnson M(2014)Power-Laws and Structure in Functional ProgramsProceedings of the 2014 International Conference on Computational Science and Computational Intelligence - Volume 0210.1109/CSCI.2014.112(168-172)Online publication date: 10-Mar-2014
https://dl.acm.org/doi/10.1109/CSCI.2014.112
Podgorelec V(2010)Assessing the current state of software evolution and intellectual energy spentProceedings of the Workshop on Advances in Functional Size Measurement and Effort Estimation10.1145/1921705.1921709(1-8)Online publication date: 21-Jun-2010
https://dl.acm.org/doi/10.1145/1921705.1921709
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Index Terms

Fractal structure of random programs
1. Theory of computation
  1. Semantics and reasoning
    1. Program semantics

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Information

Published In

ACM SIGPLAN Notices Volume 33, Issue 6

June 1998

47 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/284563

Editor:
A. Michael Berman
Rowan Univ., Glassboro, NJ

Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1998

Published in SIGPLAN Volume 33, Issue 6

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Coleman RRahtelli M(2017)A Fractal Geometry Approach to Quantifying Aesthetic Values in Scientific Codes2017 International Conference on Computational Science and Computational Intelligence (CSCI)10.1109/CSCI.2017.160(922-927)Online publication date: Dec-2017
https://doi.org/10.1109/CSCI.2017.160
Coleman RJohnson M(2014)Power-Laws and Structure in Functional ProgramsProceedings of the 2014 International Conference on Computational Science and Computational Intelligence - Volume 0210.1109/CSCI.2014.112(168-172)Online publication date: 10-Mar-2014
https://dl.acm.org/doi/10.1109/CSCI.2014.112
Podgorelec V(2010)Assessing the current state of software evolution and intellectual energy spentProceedings of the Workshop on Advances in Functional Size Measurement and Effort Estimation10.1145/1921705.1921709(1-8)Online publication date: 21-Jun-2010
https://dl.acm.org/doi/10.1145/1921705.1921709
Kokol PLenič M(2006)Analyzing software with the complexity theoryProceedings of the 10th WSEAS international conference on Systems10.5555/1984211.1984271(321-325)Online publication date: 10-Jul-2006
https://dl.acm.org/doi/10.5555/1984211.1984271
Lenic MZorman MPovalej PKokol P(2004)Alternative measurement of software artifactsSecond IEEE International Conference on Computational Cybernetics, 2004. ICCC 2004.10.1109/ICCCYB.2004.1437715(231-235)Online publication date: 2004
https://doi.org/10.1109/ICCCYB.2004.1437715
Kokol PPodgorelec VCardoso ADion F(2000)Assessing the state of the software process development using the chaos theoryACM SIGSOFT Software Engineering Notes10.1145/505863.50587425:3(41-43)Online publication date: 1-May-2000
https://dl.acm.org/doi/10.1145/505863.505874
Podgorelec VKokol PZorman M(2000)A Fractal Software Complexity Metric AnalyserComputer Aided Systems Theory - EUROCAST’9910.1007/10720123_42(486-493)Online publication date: 2000
https://doi.org/10.1007/10720123_42
Kokol PPodgorelec VHabrias HRabia N(1999)The complexity of formal specifications - assessments by α - metricACM SIGPLAN Notices10.1145/606666.60668134:6(84-88)Online publication date: 1-Jun-1999
https://dl.acm.org/doi/10.1145/606666.606681
Kokol PBrest JZorman MPodgorelec V(1998)Integration of complexity metrics with the use of decision treesACM SIGSOFT Software Engineering Notes10.1145/272263.27227723:1(56-58)Online publication date: 1-Jan-1998
https://dl.acm.org/doi/10.1145/272263.272277

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Attacks on Pseudo Random Number Generators Hiding a Linear Structure

Bit-Wise Behavior of Random Number Generators

On the lattice structure of the add-with-carry and subtract-with-borrow random number generators

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