Traversal
Traversal is the systematic process of visiting elements or nodes in a data structure according to its links, ordering, or a specified rule.
Grokking Data Structures
Array traversal is the process of visiting the elements of an array, typically to inspect or process their values.
- How it is used
- Applies an operation to every array element and supports scans that find values such as a maximum.
- How deep it goes
- Works through a Python callback loop and a maximum-index scan, including empty-array handling and initial-value choice.
- Examples
- Uses printing array elements and scanning die-face counters for the most frequent roll.
- What you can do after
- Build it from scratch with a Python loop and callback, or adapt the scan to track a largest value and its index.
AI-Powered Search
Graph traversal is the process of visiting nodes and relationships in a graph according to a specified path or sequence of steps.
- How it is used
- Uses search indexes to connect terms, queries, categories, and documents for semantic search and query disambiguation.
- How deep it goes
- Explains bidirectional index lookups, chained levels, scored edges, and configurable traversal inputs without detailing the scoring implementation.
- Examples
- Demonstrates skill-to-job paths, disconnected nodes, and server, driver, and chef queries separated by category.
- What you can do after
- Apply it via SKG traversal to discover related terms, chain graph levels, or disambiguate queries by category.
Optimization Algorithms: AI techniques for design, planning, and control problems
A graph-search technique that explores a tree or graph by visiting nodes according to a specified rule.
- How it is used
- Uses rule-based exploration to discover paths through trees and graphs in routing, puzzles, mazes, and relationship networks.
- How deep it goes
- Defines traversal and distinguishes BFS, DFS, DLS, IDS, and bidirectional search, but stops short of route-length optimization.
- Examples
- Demonstrates traversal through mazes, n-puzzles, family trees, social graphs, and origin-to-destination routing.
- What you can do after
- Apply BFS, DFS, DLS, IDS, or bidirectional search to find paths through simple, well-defined graph problems.
Related concepts
- breadth-first searchincludes · Breadth-first search is a graph or tree traversal algorithm that explores nodes in nondecreasing order of their distance from a starting node.
- depth-first searchincludes · Depth-first search is a graph or tree traversal algorithm that explores one branch as far as possible before backtracking to explore alternatives.
- postorder traversalincludes · A postorder traversal visits each node after visiting its children or subtrees.
- preorder traversalincludes · Preorder traversal is a tree traversal strategy that processes each node before recursively processing its child subtrees.
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