GraphLang — Universal Semantic Kernel for Code
The same computational intent, in 13 languages, collapses to the same 12-node graph.
GraphLang is a semantic Intermediate Representation (IR) that maps source code from 13 languages (Python, Java, JavaScript, TypeScript, C#, Rust, Go, Kotlin, Ruby, PHP, Zig, C, C++) into a single canonical graph of 12 universal IR kinds. It is not a new language — it is a discovery: different syntaxes converge to the same structure when their intent is equivalent.
Try it now on Spaces → — paste code and see it collapse into a GraphLang IR graph, live.
Python: def add(a, b): return a + b ─┐
Java: int add(int a, int b){ return a+b; } ─┤ → SAME GraphLang IR
JavaScript: function add(a,b){ return a+b; } ─┘ (identical graph)
The 12 IR Kinds (FROZEN)
| # | Kind | Meaning |
|---|---|---|
| 1 | function |
Executable unit with parameters |
| 2 | if |
Conditional branch |
| 3 | for |
Bounded iteration |
| 4 | while |
Unbounded iteration |
| 5 | return |
Value return |
| 6 | assign |
Variable binding |
| 7 | call |
Invocation |
| 8 | binop |
Binary / comparison operation |
| 9 | unary |
Unary operation |
| 10 | var |
Variable reference |
| 11 | const |
Literal constant |
| 12 | block |
Statement sequence |
The 12 kinds were derived from the analysis of ~2,215 Concrete Syntax Tree (CST) node types across the 13 languages.
Cross-language equivalence (measured, not claimed)
12 canonical intents were compiled in Python, Java, and JavaScript through the
real engine (complete_normalizer.py) and fingerprinted with a recursive
structural hash (content-addressed, not node-id based).
| Group | Identical IR? | Notes |
|---|---|---|
add, max2, abs, square, compare, negate, twice |
Yes (7/7) | arithmetic / expression intents |
is_even, sum_loop, fact, fib, grade |
Partial | comparison/loop sugar (elif vs else if, for-of vs for-in, Python Compare vs binary op) |
Arithmetic and expression-level intents collapse to bit-identical IR across
the three languages. The remaining divergence is a known normalization gap in
comparison and loop sugar — documented, not hidden. See data/equivalence.csv.
IR visualization
grade(score) in Python, normalized to GraphLang IR:
Reproducible Benchmarks
The compression ratio converges to a constant — 22.5x monolingual and
29.8x multilingual — from 100K functions onward. Results below are
reproducible with the engine (benchmark_100k.py / benchmark_1m.py).
| Functions | Total Nodes | Unique Patterns | Ratio | Errors |
|---|---|---|---|---|
| 1,500 | 32,481 | 1,567 | 20.7x | 0 |
| 10,000 | 217,233 | 9,770 | 22.2x | 0 |
| 100,000 | 2,170,018 | 96,616 | 22.5x | 0 |
| 1,000,000 | 21,721,197 | 965,045 | 22.5x | 0 |
Datasets (downloadable)
| File | Content |
|---|---|
data/examples.jsonl |
36 code→IR samples (12 intents × Python/Java/JavaScript), full IR node dump + fingerprint |
data/equivalence.csv |
Cross-language equivalence matrix with recursive structural hashes |
benchmark_100k_results.json |
100K-function compression measurement |
benchmark_1m_results.json |
1M-function compression measurement |
Included in this repository
app.py— didactic interactive demo (Gradio): paste code, see the IR graph, merge two functions, measure structural deduplication. This is a self-contained educational reimplementation, not the production engine.parallel_ir.py— GPU/HPC extension (CUDA / OpenCL / Metal detection and thread-index normalization) sitting on top of the 12 core kinds.benchmark_100k_results.json,benchmark_1m_results.json— reproducible benchmark measurements.data/— the code→IR dataset and equivalence matrix (generated by the real engine).assets/— IR graph visualizations (SVG + PNG).paper/— the academic paper (GraphLang: a universal semantic kernel for code).
Engine and license
The full multi-language normalizer engine is available under the
MII Open License v1.1 (see LICENSE): free for non-commercial and
research use, restricted for AI/ML training (drafted as a copyright condition,
enforceable under Jacobsen v. Katzer), and commercial use requires a
license.
The benchmarks and data/ files in this repository were produced by the real
engine. The app.py demo is a simplified didactic reimplementation that
illustrates the concept only.
For the engine, the 20M aligned function-pair dataset, or commercial licensing: josu31.jas@gmail.com
- Source repository: https://github.com/cripto-bot/graphlang
- Author: Josué Argaña Silguero — 2026
"No inventamos un nuevo lenguaje. Descubrimos que todos los lenguajes ya hablaban el mismo."