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C. C (programming language) C dynamic memory allocation; C file input/output; C syntax; C data types; C23 (C standard revision) Callback (computer programming) CIE 1931 color space; Coalesced hashing; Code injection; Comment (computer programming) Composite data type; Conditional (computer programming) Const (computer programming) Constant ...
The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric. [3]: ND22, ND23
A problem is hard for a class of problems C if every problem in C can be polynomial-time reduced to . Thus no problem in C is harder than X {\displaystyle X} , since an algorithm for X {\displaystyle X} allows us to solve any problem in C with at most polynomial slowdown.
NP is a class of decision problems; the analogous class of function problems is FNP. The only known strict inclusions come from the time hierarchy theorem and the space hierarchy theorem , and respectively they are N P ⊊ N E X P T I M E {\displaystyle {\mathsf {NP\subsetneq NEXPTIME}}} and N P ⊊ E X P S P A C E {\displaystyle {\mathsf {NP ...
A problem that is complete for a class C is said to be C-complete, and the class of all problems complete for C is denoted C-complete. The first complete class to be defined and the most well known is NP-complete, a class that contains many difficult-to-solve problems that arise in practice. Similarly, a problem hard for a class C is called C ...
a:(b,c,d), b:(c,a,d), c:(a,b,d), d:(a,b,c) In this ranking, each of A, B, and C is the most preferable person for someone. In any solution, one of A, B, or C must be paired with D and the other two with each other (for example AD and BC), yet for anyone who is partnered with D, another member will have rated them highest, and D's partner will ...
In computational complexity theory, a problem refers to the abstract question to be solved. In contrast, an instance of this problem is a rather concrete utterance, which can serve as the input for a decision problem. For example, consider the problem of primality testing. The instance is a number (e.g., 15) and the solution is "yes" if the ...
The class i.o.-SUBEXP, which stands for infinitely often SUBEXP, contains problems which have sub-exponential time algorithms for infinitely many input sizes. They also showed that P = BPP if the exponential-time hierarchy, which is defined in terms of the polynomial hierarchy and E as E PH , collapses to E ; however, note that the exponential ...