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Counting nodes in binary trees

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Sami KhuriAuthors Info & Claims

ACM SIGCSE Bulletin, Volume 18, Issue 1

Pages 182 - 185

https://doi.org/10.1145/953055.5646

Published: 01 February 1986 Publication History

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Abstract

This paper describes an original method for introducing linear recurrence relations. Boolean expressions are represented by binary trees and the counting of the internal nodes of these trees yield linear recurrence relations. The method allows the students to create their own family of Boolean expressions, to draw the corresponding binary trees, to deduce the recurrence relation representing the number of nodes in the trees, and finally, to solve and check the solutions of these relations.

References

[1]

C. L. Liu, Elements of Discrete Mathematics. New York: McGraw-Hill Computer Science Series, 1977.

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[2]

P. W. Purdon, and C. A. Brown, The Analysis of Algorithms. Holt, Rinehart and Winston, 1985.

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[3]

A. S. Tanenbaum, Computer Networks. New Jersey: Prentice-Hall, Inc., 1981.

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Khuri SWilliams J(1994)Understanding the bottom-up SLR parserACM SIGCSE Bulletin10.1145/191033.19116326:1(339-343)Online publication date: 12-Mar-1994
https://dl.acm.org/doi/10.1145/191033.191163
Khuri SWilliams JBeck RGoelman D(1994)Understanding the bottom-up SLR parserProceedings of the twenty-fifth SIGCSE symposium on Computer science education10.1145/191029.191163(339-343)Online publication date: 12-Mar-1994
https://dl.acm.org/doi/10.1145/191029.191163

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Counting nodes in binary trees

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Counting nodes in binary trees
SIGCSE '86: Proceedings of the seventeenth SIGCSE technical symposium on Computer science education

This paper describes an original method for introducing linear recurrence relations. Boolean expressions are represented by binary trees and the counting of the internal nodes of these trees yield linear recurrence relations. The method allows the ...
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Reviewer: Douglas M. Campbell

Khuri uses binary trees to introduce elementary linear first order recurrence relations to students in a beginning data structure course. The equations are solved by tricks, rather than by the formal theory. Students are encouraged to discover and solve similar recurrence relations for other structures.

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Published In

ACM SIGCSE Bulletin Volume 18, Issue 1

Proceedings of the 17th SIGCSE symposium on Computer science education

February 1986

304 pages

ISSN:0097-8418

DOI:10.1145/953055

Issue’s Table of Contents

SIGCSE '86: Proceedings of the seventeenth SIGCSE technical symposium on Computer science education
February 1986
336 pages
ISBN:0897911784
DOI:10.1145/5600
Editors:
Joyce Currie Little
Towson State Univ., Baltimore, MD
,
Lillian N. Cassel
Univ. of Delaware, Newark

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 February 1986

Published in SIGCSE Volume 18, Issue 1

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Khuri SWilliams J(1994)Understanding the bottom-up SLR parserACM SIGCSE Bulletin10.1145/191033.19116326:1(339-343)Online publication date: 12-Mar-1994
https://dl.acm.org/doi/10.1145/191033.191163
Khuri SWilliams JBeck RGoelman D(1994)Understanding the bottom-up SLR parserProceedings of the twenty-fifth SIGCSE symposium on Computer science education10.1145/191029.191163(339-343)Online publication date: 12-Mar-1994
https://dl.acm.org/doi/10.1145/191029.191163

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