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The (decision version of the) smallest grammar problem is NP-complete. [1] It can be approximated in polynomial time to within a logarithmic approximation ratio ; more precisely, the ratio is O ( log n g ) {\displaystyle O(\log {\tfrac {n}{g}})} where n {\displaystyle n} is the length of the given string and g {\displaystyle g} is the size ...
Müller designed Brainfuck with the goal of implementing the smallest possible compiler, [6] inspired by the 1024-byte compiler for the FALSE programming language. [7] [8] Müller's original compiler was implemented in assembly and compiled to a binary with a size of 296 bytes. He uploaded the first Brainfuck compiler to Aminet in 1993.
Furthermore, there can be no approximation algorithm with absolute approximation ratio smaller than unless =. This can be proven by a reduction from the partition problem : [ 10 ] given an instance of Partition where the sum of all input numbers is 2 T {\displaystyle 2T} , construct an instance of bin-packing in which the bin size is T .
Order the items from largest to smallest. Initialize an empty bin and call it the "open bin". For each item in order, check if it can fit into the open bin: If it fits, then place the new item into it. Otherwise, close the current bin, open a new bin, and put the current item inside it.
No logographic script is composed solely of logograms. All contain graphemes that represent phonetic (sound-based) elements as well. These phonetic elements may be used on their own (to represent, for example, grammatical inflections or foreign words), or may serve as phonetic complements to a logogram (used to specify the sound of a logogram ...
SYDNEY (Reuters) -The remaining five members of the "Bali Nine" Australian drug ring have returned from Indonesia after diplomatic efforts between the countries this month to strike a repatriation ...
There's a certain charm to small-town America. From scenic places in Maine, Alaska, California, and beyond, we've got the scoop on some of the nation's smallest towns.
Edit distance finds applications in computational biology and natural language processing, e.g. the correction of spelling mistakes or OCR errors, and approximate string matching, where the objective is to find matches for short strings in many longer texts, in situations where a small number of differences is to be expected.