Journal Article10.1145/358234.381162
Programming pearls: algorithm design techniques
279
TL;DR: This column is built around one small problem, with an emphasis on the algorithms that solve it and the techniques used to design them: sophisticated algorithmic methods sometimes lead to dramatic performance improvements.
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Abstract: The September 1983 column described the \"everyday\" impact that algorithm design can have on programmers: an algorithmic view of a problem gives insights that may make a program simpler to unders tand and to write. In this column we' l l s tudy a contribution of the field that is less frequent but more impressive: sophisticated algorithmic methods sometimes lead to dramatic performance improvements. This column is built around one small problem, with an emphasis on the algorithms that solve it and the techniques used to design them. Some of the algorithms are a little complicated, but the complication is justified; while the first algorithm we' l l s tudy takes 39 days to solve a problem of size 10,000, the final algorithm solves the same problem in just a third of a second.
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References
A universal algorithm for sequential data compression
Jacob Ziv,A. Lempel +1 more
TL;DR: The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable- to-block codes designed to match a completely specified source.
A Method for the Construction of Minimum-Redundancy Codes
David A. Huffman
- 01 Sep 1952
TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
6.1K
Algorithm 97: Shortest path
TL;DR: The procedure was originally programmed in FORTRAN for the Control Data 160 desk-size computer and was limited to te t ra t ion because subroutine recursiveness in CONTROL Data 160 FORTRan has been held down to four levels in the interests of economy.
4.3K
Compression of individual sequences via variable-rate coding
Jacob Ziv,A. Lempel +1 more
TL;DR: The proposed concept of compressibility is shown to play a role analogous to that of entropy in classical information theory where one deals with probabilistic ensembles of sequences rather than with individual sequences.
4K
The String-to-String Correction Problem
TL;DR: An algorithm is presented which solves the string-to-string correction problem in time proportional to the product of the lengths of the two strings.
3.5K