A sorted array is an array data structure in which each element is sorted in numerical, alphabetical, or some other order, and placed at equally spaced addresses in computer memory. It is typically used in computer science to implement static lookup tables to hold multiple values which have the same data type. Sorting an array is useful in organising data in ordered form and recovering them rapidly. Sorted arrays are the most space-efficient data structure with the best locality of reference for sequentially stored data. Elements within a sorted array are found using a binary search, in O(log n); thus sorted arrays are suited for cases when one needs to be able to look up elements quickly, e.g. as a set or multiset data structure. This complexity for lookups is the same as for self-balancing binary search trees. In some data structures, an array of structures is used. In such cases, the same sorting methods can be used to sort the structures according to some key as a structure element; for example, sorting records of students according to roll numbers or names or grades. If one is using a sorted dynamic array, then it is possible to insert and delete elements. The insertion and deletion of elements in a sorted array executes at O(n), due to the need to shift all the elements following the element to be inserted or deleted; in comparison a self-balancing binary search tree inserts and deletes at O(log n). In the case where elements are deleted or inserted at the end, a sorted dynamic array can do this in amortized O(1) time while a self-balancing binary search tree always operates at O(log n). Elements in a sorted array can be looked up by their index (random access) at O(1) time, an operation taking O(log n) or O(n) time for more complex data structures. John von Neumann wrote the first array sorting program (merge sort) in 1945, when the first stored-program computer was still being built.

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Merge sort
In computer science, merge sort (also commonly spelled as mergesort) is an efficient, general-purpose, and comparison-based sorting algorithm. Most implementations produce a stable sort, which means that the relative order of equal elements is the same in the input and output. Merge sort is a divide-and-conquer algorithm that was invented by John von Neumann in 1945. A detailed description and analysis of bottom-up merge sort appeared in a report by Goldstine and von Neumann as early as 1948.
Heap (data structure)
In computer science, a heap is a specialized tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is a parent node of C, then the key (the value) of P is greater than or equal to the key of C. In a min heap, the key of P is less than or equal to the key of C. The node at the "top" of the heap (with no parents) is called the root node. The heap is one maximally efficient implementation of an abstract data type called a priority queue, and in fact, priority queues are often referred to as "heaps", regardless of how they may be implemented.

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