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  2. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    Also, when implemented with the "shortest first" policy, the worst-case space complexity is instead bounded by O(log(n)). Heapsort has O(n) time when all elements are the same. Heapify takes O(n) time and then removing elements from the heap is O(1) time for each of the n elements. The run time grows to O(nlog(n)) if all elements must be distinct.

  3. Selection sort - Wikipedia

    en.wikipedia.org/wiki/Selection_sort

    It has a O(n 2) time complexity, which makes it inefficient on large lists, and generally performs worse than the similar insertion sort. Selection sort is noted for its simplicity and has performance advantages over more complicated algorithms in certain situations, particularly where auxiliary memory is limited.

  4. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    [1]: 226 Since this function is generally difficult to compute exactly, and the running time for small inputs is usually not consequential, one commonly focuses on the behavior of the complexity when the input size increases—that is, the asymptotic behavior of the complexity. Therefore, the time complexity is commonly expressed using big O ...

  5. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    This yields average time complexity of O(n log n), with low overhead, and thus this is a popular algorithm. Efficient implementations of quicksort (with in-place partitioning) are typically unstable sorts and somewhat complex, but are among the fastest sorting algorithms in practice.

  6. List of terms relating to algorithms and data structures

    en.wikipedia.org/wiki/List_of_terms_relating_to...

    The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology.It defines a large number of terms relating to algorithms and data structures.

  7. Complexity class - Wikipedia

    en.wikipedia.org/wiki/Complexity_class

    A representation of the relationships between several important complexity classes. In computational complexity theory, a complexity class is a set of computational problems "of related resource-based complexity". [1] The two most commonly analyzed resources are time and memory.

  8. Computational complexity theory - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Since the time taken on different inputs of the same size can be different, the worst-case time complexity () is defined to be the maximum time taken over all inputs of size . If T ( n ) {\displaystyle T(n)} is a polynomial in n {\displaystyle n} , then the algorithm is said to be a polynomial time algorithm.

  9. DTIME - Wikipedia

    en.wikipedia.org/wiki/DTIME

    In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine. It represents the amount of time (or number of computation steps) that a "normal" physical computer would take to solve a certain computational problem using a certain algorithm .