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  2. 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 ...

  3. 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.

  4. Comparison of Java and C++ - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_Java_and_C++

    Direct access from Java to native operating system and hardware functions requires the use of the Java Native Interface, or since Java 21, the Foreign Function and Memory API, which allow for allocating and managing memory outside of the Java Virtual Machine, as well as calling native (i.e. C/C++) functions.

  5. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    Its complexity can be expressed in an alternative way for very large graphs: when C * is the length of the shortest path from the start node to any node satisfying the "goal" predicate, each edge has cost at least ε, and the number of neighbors per node is bounded by b, then the algorithm's worst-case time and space complexity are both in O(b ...

  6. Shellsort - Wikipedia

    en.wikipedia.org/wiki/Shellsort

    Swapping pairs of items in successive steps of Shellsort with gaps 5, 3, 1. Shellsort, also known as Shell sort or Shell's method, is an in-place comparison sort.It can be understood as either a generalization of sorting by exchange (bubble sort) or sorting by insertion (insertion sort). [3]

  7. Computational complexity of mathematical operations - Wikipedia

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

    Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.

  8. Ackermann function - Wikipedia

    en.wikipedia.org/wiki/Ackermann_function

    The inverse of the Ackermann function appears in some time complexity results. For instance, the disjoint-set data structure takes amortized time per operation proportional to the inverse Ackermann function, [ 24 ] and cannot be made faster within the cell-probe model of computational complexity.

  9. ABC Software Metric - Wikipedia

    en.wikipedia.org/wiki/ABC_Software_Metric

    Since basic languages such as C, C++, Java, etc. have operations like assignments of variables, function calls and test conditions only, the ABC score has these three components. [ 1 ] If the ABC vector is denoted as 5,11,9 for a subroutine , it means that the subroutine has 5 assignments, 11 branches and 9 conditionals.