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Complexity class and DSPACE

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Complexity class and DSPACE

Complexity class vs. DSPACE

In computational complexity theory, a complexity class is a set of problems of related resource-based complexity. In computational complexity theory, DSPACE or SPACE is the computational resource describing the resource of memory space for a deterministic Turing machine.

Similarities between Complexity class and DSPACE

Complexity class and DSPACE have 16 things in common (in Unionpedia): Algorithm, Big O notation, Computational complexity theory, Computational problem, Computational resource, Decision problem, EXPSPACE, L (complexity), Non-deterministic Turing machine, NSPACE, NTIME, PSPACE, Savitch's theorem, Space hierarchy theorem, Time complexity, Turing machine.

Algorithm

In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.

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Big O notation

Big O notation is a mathematical notation that describes the limiting behaviour of a function when the argument tends towards a particular value or infinity.

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Computational complexity theory

Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.

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Computational problem

In theoretical computer science, a computational problem is a mathematical object representing a collection of questions that computers might be able to solve.

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Computational resource

In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems.

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Decision problem

In computability theory and computational complexity theory, a decision problem is a problem that can be posed as a yes-no question of the input values.

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EXPSPACE

In complexity theory, '' is the set of all decision problems solvable by a deterministic Turing machine in O(2p(n)) space, where p(n) is a polynomial function of n. (Some authors restrict p(n) to be a linear function, but most authors instead call the resulting class.) If we use a nondeterministic machine instead, we get the class, which is equal to by Savitch's theorem.

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L (complexity)

In computational complexity theory, L (also known as LSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space.

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Non-deterministic Turing machine

In theoretical computer science, a Turing machine is a theoretical machine that is used in thought experiments to examine the abilities and limitations of computers.

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NSPACE

In computational complexity theory, non-deterministic space or NSPACE is the computational resource describing the memory space for a non-deterministic Turing machine.

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NTIME

In computational complexity theory, the complexity class NTIME(f(n)) is the set of decision problems that can be solved by a non-deterministic Turing machine which runs in time O(f(n)).

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PSPACE

In computational complexity theory, PSPACE is the set of all decision problems that can be solved by a Turing machine using a polynomial amount of space.

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Savitch's theorem

In computational complexity theory, Savitch's theorem, proved by Walter Savitch in 1970, gives a relationship between deterministic and non-deterministic space complexity.

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Space hierarchy theorem

In computational complexity theory, the space hierarchy theorems are separation results that show that both deterministic and nondeterministic machines can solve more problems in (asymptotically) more space, subject to certain conditions.

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Time complexity

In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.

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Turing machine

A Turing machine is a mathematical model of computation that defines an abstract machine, which manipulates symbols on a strip of tape according to a table of rules.

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The list above answers the following questions

Complexity class and DSPACE Comparison

Complexity class has 77 relations, while DSPACE has 26. As they have in common 16, the Jaccard index is 15.53% = 16 / (77 + 26).

References

This article shows the relationship between Complexity class and DSPACE. To access each article from which the information was extracted, please visit:

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