I turned notebook pseudocode into a real programming language — C++17 VM and all

Description and use

X++ lets you run pseudocode natively with a C++17 VM, offering simple syntax and competitive performance.

Problem

Beginners can write algorithms in plain language but cannot run them because notebooks lack compilers.

Outcome

X++ allows running pseudocode natively with performance comparable to CPython and faster for many workloads, while keeping syntax simple and free of manual memory management.

Workflow

• Write pseudocode in .xp file
• Choose engine via RNM header (ZITR, ZCOM, ZJIT)
• Run with x run app.xp
• VM interprets or JIT compiles to native binary
• Output is produced

Evidence

X++ is an intent-driven language: you write strict pseudocode (or loose English steps for the AI mode), type one command, and it booms.

Source

Version 0.4.1 adds a zero-dependency native VM (C++17) so your programs run without Python — the Python stack is still available for the legacy and AI paths.

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The numbers, asterisks included: sum 1..5,000,000 CPython 381 ms, ZITR 202 ms, ZJIT 50 ms; fib(28) CPython 55 ms, ZITR 91 ms, ZJIT 10 ms.

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My VM loses the recursive fib to CPython. Call overhead is real and it's my next battle — a register JIT with profiling feedback is on the roadmap.

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I built a test harness that runs 40+ programs on both engines and requires byte-identical stdout, stderr, and exit codes.

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