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Java Apache License 2.0 Java and C client, HTTP, FUSE [8] transparent master failover No Reed-Solomon [9] File [10] 2005 IPFS: Go Apache 2.0 or MIT HTTP gateway, FUSE, Go client, Javascript client, command line tool: Yes with IPFS Cluster: Replication [11] Block [12] 2015 [13] JuiceFS: Go Apache License 2.0 POSIX, FUSE, HDFS, S3: Yes Yes Reed ...
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, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [7]
If G is a tree, replacing the queue of this breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [10]
A depth-first search (DFS) is an algorithm for traversing a finite graph. DFS visits the child vertices before visiting the sibling vertices; that is, it traverses the depth of any particular path before exploring its breadth. A stack (often the program's call stack via recursion) is generally used when implementing the algorithm.
Beam search uses breadth-first search to build its search tree. At each level of the tree, it generates all successors of the states at the current level, sorting them in increasing order of heuristic cost. [2] However, it only stores a predetermined number, , of best states at each level (called the beam width). Only those states are expanded ...
Distributed fault-tolerant replication of data between nodes (between servers or servers/clients) for high availability and offline (disconnected) operation. Coda from Carnegie Mellon University focuses on bandwidth-adaptive operation (including disconnected operation) using a client-side cache for mobile computing. It is a descendant of AFS-2.
IDDFS achieves breadth-first search's completeness (when the branching factor is finite) using depth-first search's space-efficiency. If a solution exists, it will find a solution path with the fewest arcs. [2] Iterative deepening visits states multiple times, and it may seem wasteful.
The line just below the Breadth-first search explanation. It uses the opposite strategy as depth-first search, which instead explores the highest-depth nodes first before being forced to backtrack and expand shallower nodes. This is incorrect. The algorithm does not know about highest-depth or shallow-depth nodes.