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The reverse-delete algorithm is an algorithm in graph theory used to obtain a minimum spanning tree from a given connected, edge-weighted graph. It first appeared in Kruskal (1956), but it should not be confused with Kruskal's algorithm which appears in the same paper. If the graph is disconnected, this algorithm will find a minimum spanning ...
Queue overflow results from trying to add an element onto a full queue and queue underflow happens when trying to remove an element from an empty queue. A bounded queue is a queue limited to a fixed number of items. [1] There are several efficient implementations of FIFO queues.
The reversal algorithm is the simplest to explain, using rotations. A rotation is an in-place reversal of array elements. This method swaps two elements of an array from outside in within a range. The rotation works for an even or odd number of array elements. The reversal algorithm uses three in-place rotations to accomplish an in-place block ...
The dynamic array approach uses a variant of a dynamic array that can grow from both ends, sometimes called array deques. These array deques have all the properties of a dynamic array, such as constant-time random access , good locality of reference , and inefficient insertion/removal in the middle, with the addition of amortized constant-time ...
In computer science, a double-ended priority queue (DEPQ) [1] or double-ended heap [2] is a data structure similar to a priority queue or heap, but allows for efficient removal of both the maximum and minimum, according to some ordering on the keys (items) stored in the structure. Every element in a DEPQ has a priority or value.
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...
For this purpose, m - 1 keys from the current node, the new key inserted, one key from the parent node and j keys from the sibling node are seen as an ordered array of m + j + 1 keys. The array becomes split by half, so that ⌊ ( m + j + 1)/2 ⌋ lowest keys stay in the current node, the next (middle) key is inserted in the parent and the rest ...
it uses a stack instead of a queue, and; it delays checking whether a vertex has been discovered until the vertex is popped from the stack rather than making this check before adding the vertex. If G is a tree, replacing the queue of the breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs ...