Every term in the wiki in one line. Hover a term for a preview, click it for the full note.
This page is generated from the notes themselves, so it is always complete.
JavaScript
Term In one line async / await Syntax that lets promise-based code read top to bottom. An async function always returns a promise; await pauses only that function. Event loop The rule that decides when queued callbacks run in JavaScript - only when the call stack is empty, microtasks first. Microtask queue A high-priority queue for promise callbacks and await continuations. It is emptied completely after every task. Promise An object that stands for a result that isn’t ready yet. It is pending, then fulfilled with a value or rejected with an error, exactly once. Task queue Where callbacks for timers, events and I/O wait. The event loop runs one task per turn, then all microtasks. Web Worker A real background thread for JavaScript in the browser. It has no DOM access and talks to the page by passing messages.
Python & Data
Term In one line GIL (Global Interpreter Lock) A lock in CPython that lets only one thread run Python bytecode at a time. Python 3.13 added an optional build without it. Mutability Whether an object can be changed after it is created. It decides what other names pointing at the same object will see. Shallow vs deep copy A shallow copy makes a new outer container that holds the same inner objects; a deep copy copies everything all the way down.
Backend & System Design
Term In one line Java A statically typed, object-oriented language that compiles to bytecode for the JVM. Heavily used in banks and large companies. Microservices Building one product as several small services that each own one job and their own data, and talk over the network.
CS Fundamentals
Term In one line Big-O notation A way to say how an algorithm’s time or memory grows as the input grows, ignoring constants. Call stack The list of functions currently running, newest on top. A function’s frame is pushed when it is called and popped when it returns. Concurrency vs parallelism Concurrency is dealing with many things in progress at once; parallelism is doing many things at the same instant. Hash map A key-value store that finds any key in O(1) time on average by turning the key into an array position with a hash function. Hash map lookup (pattern) Walk the input once and remember what you’ve seen in a hash map or set, so each “have I seen X?” question costs O(1). Thread A sequence of instructions the operating system can schedule. Threads in one process share memory; each has its own call stack.