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An anatree [1] is a data structure designed to solve anagrams. Solving an anagram is the problem of finding a word from a given list of letters. These problems are commonly encountered in word games like Scrabble or in newspaper crossword puzzles. The problem for the wordwheel also has the condition that the central letter appear in all the ...
[1] Can one find a simple closed quasigeodesic on a convex polyhedron in polynomial time? [2] Can a simultaneous embedding with fixed edges for two given graphs be found in polynomial time? [3] Can the square-root sum problem be solved in polynomial time in the Turing machine model?
An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, typically using all the original letters exactly once. [1] For example, the word anagram itself can be rearranged into the phrase "nag a ram"; which is an Easter egg suggestion in Google after searching for the word "anagram". [2]
For example, the character A is mapped to p, while a is mapped to 2. The use of a larger alphabet produces a more thorough obfuscation than that of ROT13; for example, a telephone number such as +1-415-839-6885 is not obvious at first sight from the scrambled result Z'\c`d\gbh\eggd. On the other hand, because ROT47 introduces numbers and ...
The Hardest Logic Puzzle Ever is a logic puzzle so called by American philosopher and logician George Boolos and published in The Harvard Review of Philosophy in 1996. [1] [2] Boolos' article includes multiple ways of solving the problem.
Unlike other puzzle books, each page is involved in solving the book's riddle. Specifically, each page represents a room or space in a hypothetical house, and each room leads to other "rooms" in this "house". Part of the puzzle involves reaching the center of the house, Room #45 (page 45 in the book), and back to Room #1 in only sixteen steps.
Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations.CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables, which is solved by constraint satisfaction methods.
If the substrings in question are long, this algorithm achieves great savings compared with many other hashing schemes. Theoretically, there exist other algorithms that could provide convenient recomputation, e.g. multiplying together ASCII values of all characters so that shifting substring would only entail dividing the previous hash by the ...