A tree is a connected graph with no cycles, and it has a unique path between any two vertices.

The maximum number of edges in a tree with n vertices is n-1, as adding one more edge would create a cycle.

A forest is a graph in which every connected component is a tree.

The minimum number of edges in a forest with n vertices is 0, as a forest can have isolated vertices.

Kruskal's algorithm and Prim's algorithm are both used to find a minimum spanning tree of a weighted graph.

The time complexity of Kruskal's algorithm is O(E log E), where E is the number of edges and V is the number of vertices in the graph.

A binary tree is a tree in which each node has at most two children, and it has a unique path from the root to each node. A complete binary tree is a binary tree in which all levels are completely filled, except possibly the last level.

The maximum number of nodes in a complete binary tree of height h is 2^(h+1) - 1.

Inorder traversal, preorder traversal, and postorder traversal are all traversal methods for a binary tree.

The time complexity of inorder traversal of a binary tree is O(V), where V is the number of vertices in the tree.

Binary search tree, red-black tree, and AVL tree are all types of tree data structures.

In a binary search tree, the left child of a node is always smaller than the node, and the right child of a node is always larger than the node.

Trie, suffix tree, and Patricia tree are all types of forest data structures.

A trie is a tree-like data structure that is used for storing strings. It allows for efficient searching and retrieval of strings.

Nice tree decomposition, path decomposition, and treewidth decomposition are all types of tree decompositions.