BFT: Difference between revisions
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==Related== | |||
{{TraversalRelated}} | |||
==Flags== | ==Flags== | ||
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[[Category:Trees]] | |||
[[Category:Binary Trees]] | |||
[[Category:Graphs]] | |||
[[Category:Traversal]] | [[Category:Traversal]] | ||
[[Category:Queues]] | [[Category:Queues]] | ||
[[Category:DFS]] | [[Category:DFS]] | ||
Latest revision as of 15:51, 7 September 2017
Breadth-first traversal using queues
Breadth-first traversal: same idea as breadth-first search BFS, except for traversing the tree. So, instead of searching for something in the tree, you're performing a visit action.
When doing BFT, use a queue. The pseudocode looks like this:
add root to queue
while queue not empty:
remove next item from queue
perform visit action on item
add children queue
Related
Graphs:
- Graphs#Graph Traversals
- Graphs/Depth First Traversal
- Graphs/Breadth First Traversal
- Graphs/Euler Tour
- Graphs/Euler Circuit
Traversals on trees:
Breadth-first search and traversal on trees:
Depth-first search and traversal on trees:
OOP design patterns:
Flags
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Trees Part of Computer Science Notes
Series on Data Structures Abstract data type: Trees/ADT Concrete implementations: Trees/LinkedTree · Trees/ArrayTree · SimpleTree
Tree Traversal Preorder traversal: Trees/Preorder Postorder traversal: Trees/Postorder In-Order traversal: Binary Trees/Inorder Breadth-First Search: BFS Breadth-First Traversal: BFT Depth-First Search: DFS Depth-First Traversal: DFT OOP Principles for Traversal: Tree Traversal/OOP · Tree Traversal/Traversal Method Template Tree operations: Trees/Operations Performance · Trees/Removal
Tree Applications Finding Minimum in Log N Time: Tree/LogN Min Search
Abstract data type: Binary Trees/ADT Concrete implementations: Binary Trees/LinkedBinTree · Binary Trees/ArrayBinTree Binary Trees/Cheat Sheet · Binary Trees/OOP · Binary Trees/Implementation Notes
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