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← Algorithms library/Data Structures/Binary Search Tree
ALGORITHM READING NOTE

Binary Search Tree

A binary search tree keeps smaller keys in the left subtree and larger keys in the right subtree, so search follows one branch at a time when the tree is balanced.

TYPEData structureCATEGORYData StructuresDEPTHAdvancedTYPICAL COMPLEXITYavg O(log n), worst O(n)
SHORT INTERVIEW ANSWER

Start with this mental model

A binary search tree keeps smaller keys in the left subtree and larger keys in the right subtree, so search follows one branch at a time when the tree is balanced.

01
SIMPLE EXPLANATION

How it works, without unnecessary jargon

01

BST order gives efficient search only when tree height stays small.

02

A plain BST may become a chain and degrade to O(n). Balanced trees fix that risk.

02
EXECUTION

Read the algorithm as a sequence of decisions

01

Identify the invariant that must always remain true.

02

Follow the read/update path through the structure.

03

After a mutation, restore the invariant before returning.

A small example to keep in mind

Read a tiny input by hand and write down the state after every important operation. For Binary Search Tree, the goal is to make the invariant visible rather than to memorize code.

COMPLEXITY

avg O(log n), worst O(n)

Do not quote this complexity mechanically. Ask which operation or input dimension it describes, then derive the cost from the loops, recursion depth, data-structure operations and any preprocessing assumptions.

03
WHEN TO USE IT

Good fit

  • Choose it when its dominant operations match your workload.
  • Compare memory overhead as well as Big-O.
04
COMMON MISTAKES

What usually goes wrong

  • Memorizing complexity without understanding representation.
  • Ignoring worst-case shape or resizing/rebalancing costs.
HOW TO EXPLAIN IT IN AN INTERVIEW

A professional answer shape

Always qualify O(log n) with 'when balanced'. A plain BST has O(n) worst-case search/insert/delete.

Problem→Core idea→Invariant / state→Big-O→Trade-off
QUICK INTERVIEW CHECK

What problem does Binary Search Tree solve?

A binary search tree keeps smaller keys in the left subtree and larger keys in the right subtree, so search follows one branch at a time when the tree is balanced.

What should I mention about complexity?

Its typical cost here is avg O(log n), worst O(n), but a complete answer should connect that cost to the representation, input constraints and the dominant operations.

What is the most common mistake?

Memorizing complexity without understanding representation.

Continue readingAVL TreeRed-Black TreeTree Traversal
SOURCE & FURTHER READING

This lesson is independently written for calm study and interview preparation, based on the topic catalog from trekhleb/javascript-algorithms. The upstream repository contains the original implementations, tests and per-topic README references.

Open upstream repository ↗
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