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  2. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    A tournament tree can be represented as a balanced binary tree by adding sentinels to the input lists (i.e. adding a member to the end of each list with a value of infinity) and by adding null lists (comprising only a sentinel) until the number of lists is a power of two. The balanced tree can be stored in a single array.

  3. Join-based tree algorithms - Wikipedia

    en.wikipedia.org/wiki/Join-based_tree_algorithms

    Join follows the right spine of t 1 until a node c which is balanced with t 2. At this point a new node with left child c, root k and right child t 2 is created to replace c. The new node may invalidate the balancing invariant. This can be fixed with rotations. The following is the join algorithms on different balancing schemes.

  4. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    In computing, binary trees can be used in two very different ways: First, as a means of accessing nodes based on some value or label associated with each node. [9] Binary trees labelled this way are used to implement binary search trees and binary heaps, and are used for efficient searching and sorting.

  5. Leftist tree - Wikipedia

    en.wikipedia.org/wiki/Leftist_tree

    If we have a pointer to a node x in a Min HBLT, we can delete it as follows: Replace the node x with the result of merging its two subtrees and update the s-values of the nodes on the path from x to the root, swapping the right and left subtrees if necessary to maintain the leftist tree property.

  6. Cartesian tree - Wikipedia

    en.wikipedia.org/wiki/Cartesian_tree

    To merge the two trees, apply a merge algorithm to the right spine of the left tree and the left spine of the right tree, replacing these two paths in two trees by a single path that contains the same nodes. In the merged path, the successor in the sorted order of each node from the left tree is placed in its right child, and the successor of ...

  7. Binomial heap - Wikipedia

    en.wikipedia.org/wiki/Binomial_heap

    To merge two binomial trees of the same order, first compare the root key. Since 7>3, the black tree on the left (with root node 7) is attached to the grey tree on the right (with root node 3) as a subtree. The result is a tree of order 3. The operation of merging two heaps is used as a subroutine in most other operations. A basic subroutine ...

  8. Binary expression tree - Wikipedia

    en.wikipedia.org/wiki/Binary_expression_tree

    Next, c, d, and e are read. A one-node tree is created for each and a pointer to the corresponding tree is pushed onto the stack. Creating a one-node tree. Continuing, a '+' is read, and it merges the last two trees. Merging two trees. Now, a '*' is read. The last two tree pointers are popped and a new tree is formed with a '*' as the root.

  9. Disjoint-set data structure - Wikipedia

    en.wikipedia.org/wiki/Disjoint-set_data_structure

    Initially when each node is the root of its own tree, it's trivially true. Assume that a node u with rank r has at least 2 r nodes. Then when two trees with rank r are merged using the operation Union by Rank, a tree with rank r + 1 results, the root of which has at least + = + nodes.