A developer optimized a simple AST-walking interpreter for their dynamic language Zef, achieving an impressive 16x speed-up through 21 incremental optimizations. The tiny interpreter, starting from scratch without JIT compilers or complex garbage collectors, now performs competitively with established languages like Lua, QuickJS, and CPython.

The optimization journey focused on fundamental techniques rather than advanced compiler technology. The author implemented changes like value representation, inline caching, object model improvements, and eliminating unnecessary heap allocations. Each optimization was documented with detailed benchmark comparisons using ScriptBench1, a custom benchmark suite with ports of classic language benchmarks.

The final benchmark results showed Zef reaching near-parity with mainstream interpreters. When ported to Yolo-C++, the interpreter achieved a 67x speed-up compared to the original baseline and outperformed CPython and Lua in some tests. This work demonstrates that significant performance gains are possible through careful optimization of basic interpreter architecture, without requiring complex compiler infrastructure.