Search results
Results from the WOW.Com Content Network
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.
In computer science, iterative deepening search or more specifically iterative deepening depth-first search [1] (IDS or IDDFS) is a state space/graph search strategy in which a depth-limited version of depth-first search is run repeatedly with increasing depth limits until the goal is found.
*/ /* This implementation does not implement composite functions, functions with a variable number of arguments, or unary operators. */ while there are tokens to be read: read a token if the token is: - a number: put it into the output queue - a function: push it onto the operator stack - an operator o 1: while ( there is an operator o 2 at the ...
A stack (LIFO queue) will yield a depth-first algorithm. A best-first branch and bound algorithm can be obtained by using a priority queue that sorts nodes on their lower bound. [3] Examples of best-first search algorithms with this premise are Dijkstra's algorithm and its descendant A* search. The depth-first variant is recommended when no ...
Example applications of the stack search algorithm can be found in the literature: Frederick Jelinek. Fast sequential decoding algorithm using a stack. IBM Journal of Research and Development, pp. 675-685, 1969. Ye-Yi Wang and Alex Waibel. Decoding algorithm in statistical machine translation. Proceedings of the 8th conference on European ...
An alternative algorithm for topological sorting is based on depth-first search.The algorithm loops through each node of the graph, in an arbitrary order, initiating a depth-first search that terminates when it hits any node that has already been visited since the beginning of the topological sort or the node has no outgoing edges (i.e., a leaf node):
Knuth showed that Algorithm X can be implemented efficiently on a computer using dancing links in a process Knuth calls "DLX". DLX uses the matrix representation of the exact cover problem, implemented as doubly linked lists of the 1s of the matrix: each 1 element has a link to the next 1 above, below, to the left, and to the right of itself.
The stack is often used to store variables of fixed length local to the currently active functions. Programmers may further choose to explicitly use the stack to store local data of variable length. If a region of memory lies on the thread's stack, that memory is said to have been allocated on the stack, i.e. stack-based memory allocation (SBMA).