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This is a unit of which targeted on the emerging data structures. Red- Black trees, Splay trees, AA-trees & Treaps are introduced. The learner must explore the possibilities of applying these concepts in real life.
Splay trees are binary search trees that are self adjusting. Basically, self adjusts means that whenever a splay tree is accessed for insertion or deletion of a node, then that node pushes all the remaining nodes to become root. Thus, we can conclude that any node that is accessed frequently will be at the top levels of the Splay tree.
A Red-Black tree is a type of binary search tree in which each node is either red or black. In spite of that, the root is always black. If a node is red, then its children must be black. For every node, all the paths from a node to its leaves contain the identical number of black nodes.
AA-trees are described in terms of level of each node rather than storing a color bit with each node. AA-trees have also been designed in such a way that it must satisfy certain conditions regarding its new property that means level.
The priorities of nodes of a Treap must satisfy the heap order. Therefore, the priority of any node should be as large as it's parent's. Treap is the simplest of all the trees.
In this unit, the following four advanced data structures have been practically emphasized. These may be considered as alternative to a height balanced tree, i.e., AVL tree.
In-order Traversal This process when executed iteratively also needs a stack and a Boolean to prevent the implementation from traversing any portion of a tree twice. The gener
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