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A relationship between self-organizing lists and binary search trees

  • Algorithms And Complexity
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Advances in Computing and Information — ICCI '91 (ICCI 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 497))

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Abstract

We establish the following relationship between the move-to-front heuristic for lists and the move-to-root heuristic for trees. Suppose we have a list s and we access an element x using the move-to-front heuristic to obtain a list s′. If we insert s into an empty binary search tree to obtain T and insert s′ into an empty binary search tree to obtain T′, then we can obtain T′ from T by accessing x using the move-to-root heuristic. We thus have a commutative diagram that relates the move-to-front and move-to-root heuristics.

Also, we show that there is no such commutative diagram relating the transposition heuristic for lists and the simple exchange heuristic for trees. But a new heuristic for trees, the conditional simple exchange heuristic, is related to the transposition heuristic by a commutative diagram. Furthermore, unlike the simple exchange heuristic, we show that the conditional simple exchange heuristic has an O(log n) asymptotic expected search time if the elements are accessed with independent and equal probabilities.

We conjecture that: if we are given an “oblivious” list heuristic that converges and we transform it into a binary search tree heuristic that results in a commutative diagram, then the tree heuristic also converges. The two examples of move-to-front and transposition support this conjecture.

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References

  1. B. Allen and I. Munro. Self-organizing binary search trees. Journal of the ACM, 25:526–535, 1978.

    Article  Google Scholar 

  2. R. P. Cheetham, B. J. Oommen, and D. T. H. Ng. Adaptive structuring of binary search trees using conditional rotations. Technical Report SCS-TR-126, Carleton University, October 1987.

    Google Scholar 

  3. G. H. Gonnet, J. I. Munro, and H. Suwanda. Exegesis of self-organizing linear search. SIAM Journal on Computing, 10:613–637, 1981.

    Article  Google Scholar 

  4. T. W. Lai and D. Wood. Sequential search, binary search trees, and adaptivity. In preparation.

    Google Scholar 

  5. T. W. H. Lai. Efficient maintenance of binary search trees. PhD thesis, University of Waterloo, 1990. In preparation.

    Google Scholar 

  6. J. McCabe. On serial files with relocatable records. Operations Research, 13:609–618, 1965.

    Google Scholar 

  7. R. L. Rivest. On self-organizing sequential search heuristics. Communications of the ACM, 19:63–67, 1976.

    Article  Google Scholar 

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Frank Dehne Frantisek Fiala Waldemar W. Koczkodaj

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© 1991 Springer-Verlag Berlin Heidelberg

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Lai, T.W., Wood, D. (1991). A relationship between self-organizing lists and binary search trees. In: Dehne, F., Fiala, F., Koczkodaj, W.W. (eds) Advances in Computing and Information — ICCI '91. ICCI 1991. Lecture Notes in Computer Science, vol 497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54029-6_159

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  • DOI: https://doi.org/10.1007/3-540-54029-6_159

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54029-8

  • Online ISBN: 978-3-540-47359-6

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