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List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.
This diagram represents five contiguous memory regions which each hold a pointer and a data block. The List Head points to the 2nd element, which points to the 5th, which points to the 3rd, thereby forming a linked list of available memory regions. A free list (or freelist) is a data structure used in a scheme for dynamic memory allocation.
Sometimes the list labeling problem is presented where S is not a set of values but rather a set of objects subject to a total order. In this setting, when an item is inserted into S, it is specified to be the successor of some other item already in S. For example, this is the way that list labeling is used in the order-maintenance problem. The ...
A problem related to the order-maintenance problem is the list-labeling problem in which instead of the order(X, Y) operation the solution must maintain an assignment of labels from a universe of integers {,, …,} to the elements of the set such that X precedes Y in the total order if and only if X is assigned a lesser label than Y.
The List Update or the List Access problem is a simple model used in the study of competitive analysis of online algorithms.Given a set of items in a list where the cost of accessing an item is proportional to its distance from the head of the list, e.g. a linked List, and a request sequence of accesses, the problem is to come up with a strategy of reordering the list so that the total cost of ...
Enumeration problems have been studied in the context of computational complexity theory, and several complexity classes have been introduced for such problems.. A very general such class is EnumP, [1] the class of problems for which the correctness of a possible output can be checked in polynomial time in the input and output.
From a dynamic programming point of view, Dijkstra's algorithm for the shortest path problem is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [8] [9] [10] In fact, Dijkstra's explanation of the logic behind the algorithm, [11] namely Problem 2.
Some problems which do not have a PTAS may admit a randomized algorithm with similar properties, a polynomial-time randomized approximation scheme or PRAS.A PRAS is an algorithm which takes an instance of an optimization or counting problem and a parameter ε > 0 and, in polynomial time, produces a solution that has a high probability of being within a factor ε of optimal.