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- Time_complexity abstract "In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the string representing the input. The time complexity of an algorithm is commonly expressed using big O notation, which excludes coefficients and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity. For example, if the time required by an algorithm on all inputs of size n is at most 5n3 + 3n, the asymptotic time complexity is O(n3).Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform. Thus the amount of time taken and the number of elementary operations performed by the algorithm differ by at most a constant factor.Since an algorithm's performance time may vary with different inputs of the same size, one commonly uses the worst-case time complexity of an algorithm, denoted as T(n), which is defined as the maximum amount of time taken on any input of size n. Time complexities are classified by the nature of the function T(n). For instance, an algorithm with T(n) = O(n) is called a linear time algorithm, and an algorithm with T(n) = O(2n) is said to be an exponential time algorithm.".
- Time_complexity wikiPageID "405944".
- Time_complexity wikiPageRevisionID "606298927".
- Time_complexity hasPhotoCollection Time_complexity.
- Time_complexity subject Category:Analysis_of_algorithms.
- Time_complexity subject Category:Computational_complexity_theory.
- Time_complexity subject Category:Computational_resources.
- Time_complexity type Abstraction100002137.
- Time_complexity type Assets113329641.
- Time_complexity type ComputationalResources.
- Time_complexity type Possession100032613.
- Time_complexity type Relation100031921.
- Time_complexity type Resource113331778.
- Time_complexity comment "In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the string representing the input. The time complexity of an algorithm is commonly expressed using big O notation, which excludes coefficients and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity.".
- Time_complexity label "Complessità temporale".
- Time_complexity label "Time complexity".
- Time_complexity label "Zeitkomplexität".
- Time_complexity label "时间复杂度".
- Time_complexity sameAs Zeitkomplexität.
- Time_complexity sameAs Complessità_temporale.
- Time_complexity sameAs 시간_복잡도.
- Time_complexity sameAs m.0c4gy.
- Time_complexity sameAs Q2393193.
- Time_complexity sameAs Q2393193.
- Time_complexity sameAs Time_complexity.
- Time_complexity wasDerivedFrom Time_complexity?oldid=606298927.
- Time_complexity isPrimaryTopicOf Time_complexity.