A tree is a hierarchical structure of nodes with one root and no cycles. A binary search tree keeps left children smaller and right children larger, giving O(log n) search, insert, and delete when balanced.
Trees and binary search trees - Interview Concepts - ExtraBrain is part of ExtraBrain's local-first Mac workflow for live interviews, meetings, transcription, provider control, and responsible AI use.
A tree is a hierarchical structure of nodes with one root and no cycles. A binary search tree keeps left children smaller and right children larger, giving O(log n) search, insert, and delete when balanced.
ExtraBrain has 1 current public platform family, macOS, with support for 2 Mac CPU families: Apple Silicon and Intel.
ExtraBrain has 3 configurable data paths to review before sensitive work: local Parakeet transcription, local Gemma 4 where installed and compatible, and external providers you choose.
In-order, pre-order, post-order, and level-order traversals each suit different problems.
An unbalanced BST degrades to O(n); balanced variants like AVL and red-black trees keep O(log n).
Range queries, ordered data, and hierarchical relationships map to trees.
Use any live AI assistant only where interview, workplace, school, and platform rules allow it. Do not use generated answers to misrepresent your skills, experience, or authorship.
Short answers for people and crawlers comparing ExtraBrain with other live AI assistants.
Search, insert, and delete are O(log n) in a balanced BST and O(n) in the worst case when unbalanced.
Use in-order for sorted output of a BST, level-order for breadth, and pre or post-order for structure-based tasks.
