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Because each binomial tree in a binomial heap corresponds to a bit in the binary representation of its size, there is an analogy between the merging of two heaps and the binary addition of the sizes of the two heaps, from right-to-left. Whenever a carry occurs during addition, this corresponds to a merging of two binomial trees during the merge.
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.
A mergeable heap supports the usual heap operations: [1] Make-Heap(), create an empty heap. Insert(H,x), insert an element x into the heap H. Min(H), return the minimum element, or Nil if no such element exists. Extract-Min(H), extract and return the minimum element, or Nil if no such element exists. And one more that distinguishes it: [1]
Accordingly, the set bit is used to index the first item, or child node, in the 32- or 64-entry based bitwise tree. Search then proceeds by testing each subsequent bit in the key. [19] This procedure is also cache-local and highly parallelizable due to register independency, and thus performant on out-of-order execution CPUs. [19]
Vuillemin invented the binomial heap [2] and Cartesian tree data structures. [3] With Ron Rivest, he proved the Aanderaa–Rosenberg conjecture, according to which any deterministic algorithm that tests a nontrivial monotone property of graphs, using queries that test whether pairs of vertices are adjacent, must perform a quadratic number of adjacency queries. [4]
Therefore I suggest sticking with the textbook version. In principle even the textbook version can be made user-friendly by using some additional memory - for example you have one structure for describing node of the tree and its connection with other nodes, and a separate structure holding the key and other user information.
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.
Skew binomial heap containing numbers 1 to 19, showing trees of ranks 0, 1, 2, and 3 constructed from various types of links Simple, type a skew, and type b skew links. A skew binomial heap is a forest of skew binomial trees, which are defined inductively: A skew binomial tree of rank 0 is a singleton node.