Minifier

JavaScript minification plays a crucial role in optimizing website performance as it reduces the amount of data sent to users, resulting in faster page loads. This holds tremendous economic value, particularly for e-commerce websites, where every second can equate to millions of dollars.

However, existing minifiers typically require a trade-off between compression quality and speed. You have to choose between the slowest for the best compression or the fastest for less compression. But what if we could develop a faster minifier without compromising on compression?

Project Goals

We are actively working on a prototype that aims to achieve this goal, by porting all test cases from well-known minifiers such as google-closure-compiler, terser, esbuild, and tdewolff-minify.

Preliminary results indicate that we are on track to achieve our objectives. With the Oxc minifier, you can expect faster minification times without sacrificing compression quality.

Target Performance

• Speed: faster than Terser, competitive with esbuild
• Compression: Match or exceed Terser's compression ratio
• Correctness: Pass all major minifier test suites

Architecture Overview

Design Principles

The Oxc minifier is built around several key principles:

1. Semantic-Aware: Uses semantic analysis to enable safe optimizations
2. Incremental: Designed for incremental compilation workflows
3. Configurable: Supports various optimization levels and targets
4. Correct: Prioritizes correctness over aggressive optimization

Current Status

Implemented Features

• ✅ Dead Code Elimination: Remove unreachable code
• ✅ Constant Folding: Evaluate constant expressions
• ✅ Tree Shaking: Remove unused exports (basic)
• ✅ Variable Merging: Merge variable declarations
• ✅ Statement Merging: Combine compatible statements
• ✅ Name Mangling: Shorten variable and function names
• ✅ Control Flow Optimization: Simplify control structures
• ✅ Function Inlining: Inline small functions
• ✅ Advanced Tree Shaking: Cross-module optimization

Performance Optimization

Key strategies for maintaining performance:

1. Minimal AST Traversals: Combine multiple optimizations in single passes
2. Efficient Data Structures: Use arena allocation and compact representations
3. Early Termination: Skip optimizations when no benefit is possible

Resources

Documentation

• Minifier API Documentation

External References

• Google Closure Compiler Optimizations
• Terser Options
• esbuild Minification