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Insertion sort is a simple sorting algorithm that builds the final sorted array (or list) one item at a time by comparisons.It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort.
Insertion sort is widely used for small data sets, while for large data sets an asymptotically efficient sort is used, primarily heapsort, merge sort, or quicksort. Efficient implementations generally use a hybrid algorithm , combining an asymptotically efficient algorithm for the overall sort with insertion sort for small lists at the bottom ...
Bucket sort can be seen as a generalization of counting sort; in fact, if each bucket has size 1 then bucket sort degenerates to counting sort. The variable bucket size of bucket sort allows it to use O( n ) memory instead of O( M ) memory, where M is the number of distinct values; in exchange, it gives up counting sort's O( n + M ) worst-case ...
Cubesort's algorithm uses a specialized binary search on each axis to find the location to insert an element. When an axis grows too large it is split. Locality of reference is optimal as only four binary searches are performed on small arrays for each insertion.
Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...
The B-tree generalizes the binary search tree, allowing for nodes with more than two children. [2] Unlike other self-balancing binary search trees, the B-tree is well suited for storage systems that read and write relatively large blocks of data, such as databases and file systems.
As described above, a skip list is capable of fast () insertion and removal of values from a sorted sequence, but it has only slow () lookups of values at a given position in the sequence (i.e. return the 500th value); however, with a minor modification the speed of random access indexed lookups can be improved to ().
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 ...