alea-institute/alea-synth-code

ALEA synthetic code files

Raw files from synthetic code artifacts in C, Rust, TypeScript and Python: focused samples and textbook-style walkthroughs on topics from mathematics and data structures to file formats and application foundations. One document per file, with a path header in the file's own comment syntax; files include source, tests, text fixtures and data, READMEs, walkthroughs and package manifests.

10,930 documents, 28,621,267 tokens (alea-v2b-sw32k, the ALEA R4 tokenizer, counting each document's start and end tokens).

Part of the ALEA R4 training mix

This dataset contains all trained rows of this family except 2 files omitted for internal-path hygiene: R4 trained on 10,932 documents (28,629,787 tokens) in its stable pretraining mixture (second data stage, one pass each), and 10,930 are released here. Every released row is byte-identical to the trained text; text_sha256 is the SHA-256 of text.

Held-out evaluation items generated by the same code are not part of this release.

Composition

task	documents	tokens
source	2,994	9,434,434
readme	2,264	2,187,885
test	2,124	9,879,574
manifest	1,261	118,269
walkthrough	1,011	3,934,079
data	868	2,401,194
prose	408	665,832

generator	documents	tokens
codex	8,000	19,760,910
unknown	1,363	4,192,708
claude-sonnet	1,183	3,507,277
codex-gpt-6.1-sol	376	1,146,568
claude-sonnet+codex-draft	8	13,804

How it was made

The artifacts were written by coding agents in an ALEA code-synthesis campaign. The generator column gives the generator recorded in each artifact's provenance file: codex (OpenAI Codex), codex-gpt-6.1-sol (OpenAI Codex with GPT-6.1-sol), claude-sonnet (Anthropic Claude Sonnet), claude-sonnet+codex-draft (a Claude Sonnet artifact from a Codex draft), and unknown where the provenance file does not record one.

Sources

• Synthetic code artifacts (no third-party repositories)

Verification

• File-level drops (detection only): infrastructure strings and absolute host paths, secrets, binaries, captured logs and stdout, provenance and review records, exact duplicates, walkthrough code near-duplicating the same topic's sample, and Markdown dominated by process text.
• A blind review judged sampled files against the bar for a curated natural-code corpus and hand-checked worked examples.
• Decontamination: training rows that shared a word 13-gram with a held-out evaluation item of this or any sibling family were removed, and rows overlapping ALEA's evaluation sets were removed or logged according to ALEA's decontamination policy.
• Every file in this release was scanned for API keys, access tokens and private keys; none were found.

Columns

column	content
id	row id from the generator (not always unique: a few families reuse an id across variants, and a handful of exact duplicate documents were trained twice and appear twice)
text	the document exactly as trained; chat documents use ALEA's chat template, whose control tokens appear as text (`<
task	task kind
phase	stable (trained in R4's stable pretraining mixture)
generator	what wrote the row (deterministic = code only)
group_id	source passage / record group; all variants of one group share it
prompt_chars	length in characters of the request part of text (0 for plain documents; null where not recorded)
n_tokens	tokens under alea-v2b-sw32k, including the document start and end tokens
text_sha256	SHA-256 of text
meta	JSON: the generator's structured fields (source, presentation, answer form, gold values, checks)

Known limitations

• Files keep natural-repository quirks: some docstrings and READMEs mention tiers, contracts, fixtures or review steps, and some identifiers are seed words.
• Tests may reference fixtures that are not included.
• Code was written by models; review it before reuse.

License

CC-BY-4.0 for this compilation and the generated text. Public-domain and public-record source text keeps its status; Wikidata is CC0; OpenGloss and SHELF are CC-BY-4.0.

Published by the ALEA Institute.