dead code detection

**Dead code detection** is a **static analysis technique identifying unreachable or unused code** — finding functions, variables, and branches that never execute, reducing codebase size, improving maintainability, and catching potential bugs. **What Is Dead Code Detection?** - **Definition**: Identify code that is never executed or used. - **Types**: Unreachable code, unused functions, unused variables, dead stores. - **Tools**: Tree-shaking, linters (ESLint, Pylint), IDE analysis. - **Benefit**: Smaller bundles, cleaner codebases, fewer bugs. - **AI Application**: Code LLMs can detect and suggest removal. **Why Dead Code Detection Matters** - **Bundle Size**: Remove unused code from production builds. - **Maintainability**: Less code to read and understand. - **Bug Prevention**: Dead code may indicate logic errors. - **Security**: Unused code can contain vulnerabilities. - **Performance**: Smaller codebases load and compile faster. **Types of Dead Code** - **Unreachable**: After return/throw, inside false conditions. - **Unused Functions**: Defined but never called. - **Unused Variables**: Assigned but never read. - **Dead Stores**: Values overwritten before use. **Detection Tools** - Python: Vulture, Pylint, Pyflakes. - JavaScript: ESLint, Webpack tree-shaking. - Java: IntelliJ IDEA, SpotBugs. - Multi-language: SonarQube. Dead code detection **keeps codebases lean and maintainable** — essential for healthy software projects.