Time complexity
ESTIMATE OF TIME TAKEN FOR RUNNING AN ALGORITHM
Polynomial time; Exponential time; Linearithmic function; Subquadratic time; Running time; Linear time; Cubic time; Quadratic time; Algorithmic time complexity; Polynomial-time; Polynomial-time algorithm; Polynomial-time solutions; Polynomial-time solution; Computation time; Constant time; Exponential algorithm; Logarithmic time; Linear-time; Linearithmic; N log n; Weakly polynomial; Strongly polynomial; Run-time complexity; Sublinear time; Sublinear-time; Sublinear time algorithm; Linearithm; Computational time; Sub-exponential time; Super-polynomial time; Superpolynomial; Fast algorithms; Quasi-polynomial time; SUBEXP; Linearithmic time; Double exponential time; Polylogarithmic time; Sub-linear time; Polynomial time algorithm; Subexponential time; Nlogn; Quasilinear time; Strongly polynomial time; Polynomial complexity; Linear-time algorithm; Linear time agorithm; Sublinear algorithm; Polytime; Weakly polynomial time algorithm; Time complexities
In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform.