DAGs: Difference between revisions
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=Notes= | =Notes= | ||
A directed acyclic graph is a directed graph that does not contain cycles. | |||
For notes on detecting cycles, see [[Graphs/Cycles]]. (Use depth first search - see [[Graphs/DFS]]). | |||
Examples of DAGs: | |||
* All trees are DAGs (see [[Trees]]) | |||
* All git repositories are DAGs | |||
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Latest revision as of 20:19, 11 October 2017
Notes
A directed acyclic graph is a directed graph that does not contain cycles.
For notes on detecting cycles, see Graphs/Cycles. (Use depth first search - see Graphs/DFS).
Examples of DAGs:
- All trees are DAGs (see Trees)
- All git repositories are DAGs
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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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