Trees/Preorder
From charlesreid1
Contents
Preorder traversal in trees
Preorder traversal is a depth-first recursive tree traversal algorithm that can be defined and applied recursively to Trees. The children do not necessarily need to be ordered - the order refers to the order of depth (bottom-up or top-down) and not order of children. In Binary Trees an Inorder traversal can be defined that relies on the convention that in a sorted binary tree the left side comes before the right side.
Recursive definition
(See also: Recursion)
As with any recursive method, this must be split into a base case and a recursive case. The base case is, we've reached an external node - no children. The recursive case is, we call preorder on each child. In this case we don't need an explicit base case and recursive case.
The preorder traversal is the heuristic utilized in a "greedy" Traveling Salesperson Problem TSP algorithm. See also: https://charlesreid1.github.io/ (several blog posts documenting implementations and profiling TSP code in Java).
Here is an example of a preorder traversal pseudocode:
define public function preorder( tree ) preorder_subtree( tree, root, 0 ) define private function preorder_subtree( tree, position, depth) perform visit action on position for child in position.children(): preorder_subtree(tree, child, depth+1)
Because this is an intransitive recursive function - nothing is returned - the base case can remain implicit (if position is an external node, position.children is empty, and the for loop is not run, and an instance of the void recursive method returns).
Implementation
The implementation of preorder traversal is implemented in the linked binary tree class Binary Trees/LinkedBinTree using the following methods:
- A public method that takes no parameters,
preorder()
, returning an iterator over each node in pretraversal order: https://git.charlesreid1.com/cs/java/src/master/trees/LinkedBinTree.java#L362 - A public method that takes one parameter, a position,
preorder(p)
, returning an iterator over each node in the subtree rooted at p in pretraversal order: https://git.charlesreid1.com/cs/java/src/master/trees/LinkedBinTree.java#L369 - A private method that takes two parameters, one position and one Collections object (a list) to store a list of items for the iterator to return back: https://git.charlesreid1.com/cs/java/src/master/trees/LinkedBinTree.java#L376
All the work is done by the last method, and that method doesn't actually do much work - it just adds the current node to the list, and then iterates over the children and calls itself recursively on each child.
/** Utility method for pre-order tree traversal. */ private void preorderSubtree(Position<E> p, List<Position<E>> snapshot) { // Base case is, no children, no loop. // Recursive case is, this will be called on child nodes. // 1. Perform visit action for Position p snapshot.add(p); // 2. Recurse through children for(Position<E> c : children(p)) { preorderSubtree(c,snapshot); } }
Related Pages
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
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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