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  2. Range minimum query - Wikipedia

    en.wikipedia.org/wiki/Range_minimum_query

    Range minimum query reduced to the lowest common ancestor problem.. Given an array A[1 … n] of n objects taken from a totally ordered set, such as integers, the range minimum query RMQ A (l,r) =arg min A[k] (with 1 ≤ l ≤ k ≤ r ≤ n) returns the position of the minimal element in the specified sub-array A[l …

  3. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    The k-way merge problem consists of merging k sorted arrays to produce a single sorted array with the same elements. Denote by n the total number of elements. n is equal to the size of the output array and the sum of the sizes of the k input arrays. For simplicity, we assume that none of the input arrays is empty.

  4. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    For example, for the array of values [−2, 1, −3, 4, −1, 2, 1, −5, 4], the contiguous subarray with the largest sum is [4, −1, 2, 1], with sum 6. Some properties of this problem are: If the array contains all non-negative numbers, then the problem is trivial; a maximum subarray is the entire array.

  5. Range query (computer science) - Wikipedia

    en.wikipedia.org/wiki/Range_query_(computer_science)

    Given a function that accepts an array, a range query (,) on an array = [,..,] takes two indices and and returns the result of when applied to the subarray [, …,].For example, for a function that returns the sum of all values in an array, the range query ⁡ (,) returns the sum of all values in the range [,].

  6. Cycle sort - Wikipedia

    en.wikipedia.org/wiki/Cycle_sort

    When the array contains only duplicates of a relatively small number of items, a constant-time perfect hash function can greatly speed up finding where to put an item 1, turning the sort from Θ(n 2) time to Θ(n + k) time, where k is the total number of hashes. The array ends up sorted in the order of the hashes, so choosing a hash function ...

  7. Fenwick tree - Wikipedia

    en.wikipedia.org/wiki/Fenwick_tree

    A Fenwick tree or binary indexed tree (BIT) is a data structure that stores an array of values and can efficiently compute prefix sums of the values and update the values. It also supports an efficient rank-search operation for finding the longest prefix whose sum is no more than a specified value.

  8. “I Still Need An ID”: 50 Examples Of Unhinged Customer ...

    www.aol.com/lifestyle/still-id-55-examples...

    Image credits: Cubbby It does not take a genius to realize that the customer is most definitely not always right. Broadly speaking, this concept was more often used as advice for the folks ...

  9. Heap (data structure) - Wikipedia

    en.wikipedia.org/wiki/Heap_(data_structure)

    Example of a binary max-heap with node keys being integers between 1 and 100. In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key (the value) of P is greater than or equal to the key of C.