| --- |
| license: other |
| license_name: mii-open-license-v1.1 |
| license_link: https://github.com/cripto-bot/graphlang/blob/main/LICENSE |
| language: |
| - en |
| tags: |
| - intermediate-representation |
| - semantic-ir |
| - code-analysis |
| - compiler |
| - cross-language |
| - ast |
| - code-compression |
| - dataset |
| - demo |
| pipeline_tag: other |
| --- |
| |
| # 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 →](https://huggingface.co/spaces/Jose-dev/graphlang)** |
| > — paste code and see it collapse into a GraphLang IR graph, live. |
|
|
| ```text |
| 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."* |
|
|
