---
id:"kb-2026-00199"
title:"Type Systems"
schema_type:"TechArticle"
category:"computer-science"
language:"en"
confidence:"high"
last_verified:"2026-05-22"
generation_method: "human_only"
ai_models:["claude-opus"]
derived_from_human_seed:true


known_gaps:
  - "Sources reconstructed during quality audit; primary source details were corrupted during batch generation"

completeness: 0.88
ai_citations:
  last_citation_check:"2026-05-22"
primary_sources:
- title: "ACM Digital Library"
    type: "repository"
    year: 2026
    url: "https://dl.acm.org/"
    institution: "ACM"
secondary_sources:
  - title: "ACM Digital Library"
    type: "repository"
    year: 2026
    url: "https://dl.acm.org/"
    institution: "ACM"
---

## TL;DR

Type systems assign types to program constructs, catching errors at compile time. Static typing (C, Java, Rust): types checked before execution. Dynamic typing (Python, JavaScript): types checked at runtime. Type systems prevent entire classes of bugs: null dereferences, type mismatches, memory safety violations.

## Core Explanation

Type safety: well-typed programs don't go wrong (no runtime type errors). Strong vs. weak: strong (Python, Rust — no implicit coercion) vs. weak (C, JavaScript — implicit conversions). Nominal typing (Java: types defined by name) vs. structural typing (TypeScript: types defined by shape). Hindley-Milner (ML/Haskell) infers types without annotations.

## Further Reading

- [undefined](undefined)