Big-O
/bɪɡ oʊ/ · Noun · Development
Definitions
Big-O notation is a mathematical notation that describes the upper bound of an algorithm's time or space complexity as the input size grows, abstracting away constants and lower-order terms to characterize scalability.
In plain English: A shorthand for describing how much slower a program gets as you give it more data — O(n) means twice the data takes roughly twice as long.
Example: "Binary search is O(log n), which is why it finds an item in a billion-element array in about 30 steps."
Related Terms
- Space Complexity
- Allocator
- Backtracking
- Binary Tree
- Comptime
- Concurrency
- Frame Rate
- Graph
- Hash Table
- Mex
- Native
- Reduction
- Protocol Buffers
- Rate Limiter
- Tail Latency
- Cold Start
- Big-O Notation
- MessagePack
- Edge Function
- Bloom Filter
- io_uring
- First Contentful Paint
- Largest Contentful Paint
- Build Cache
- USE Method
- K-Means
- Optimization
- Pathfinding
- Pure Component
- Radix Sort
- Scan
- Time Complexity
- Turbolinks
- Wasm
- Zap
- Constraint Programming