Datasets:

cezar-sas
/

code-theseus

---
license: cc-by-4.0
pretty_name: code-theseus
task_categories:
- text-generation
language:
- en
size_categories:
- 10K<n<100K
tags:
- software-engineering
- requirements-engineering
- software-architecture
- reverse-engineering
- c4-model
- code-generation
- coding-agents
- llm
- synthetic
configs:
- config_name: documents
  data_files: documents/train.parquet
  default: true
- config_name: repos
  data_files: repos/train.parquet
---
<div align="center">

# 🚢 code-theseus

**The design behind 10,000+ open-source repositories: intent, requirements
and architecture, aligned with the code, ready for training coding agents.**

| 📦 **10,813** | 📄 **21,623** | 🌐 **4** | 🤖 **2** |
|:---:|:---:|:---:|:---:|
| repositories | document sets | languages: Java, Python, C/C++, C# | generator LLMs |



</div>

## 🧭 Why this dataset

Coding agents increasingly design before they code, but almost no data
connects code to the requirements and architecture behind it: real projects
rarely keep these documents, and when they do they are outdated or private.
code-theseus recovers them from the source code, at scale.

## 📦 What's inside

Every repository comes with three aligned documents, generated from its
dependency graph and key project files:

| | Document | What it captures |
|---|---|---|
| 🎯 | **`intent`** | The "initial prompt": mission, problem, capabilities, user workflows, quality expectations |
| 📋 | **`requirements`** | `REQ-FUNC-*` / `REQ-NFR-*` items with statement, rationale, acceptance criteria, verification method and priority |
| 🏗️ | **`architecture`** | A C4 design (context, container, component) with Mermaid C4 diagrams |

…plus the **package-level dependency graph** each document was generated
from, and a link to the exact commit it describes. No source code is
redistributed: check out `url` at `commit_sha` to recover it.

## 🔁 Does it carry the design?

In the paper's Ship of Theseus test, a coding agent rebuilt
[Commit0](https://github.com/commit-0/commit0) libraries from these
documents alone. With requirements and architecture, it built a module
structure **significantly closer to the original** than with intent alone
(module F1 0.54 → 0.63), at the same test pass rate.

## 🏢 Use it for

- **Fine-tuning** models that write specs from code (graph → intent,
  requirements, architecture) or code from specs.
- **Spec-driven coding agents.** Realistic requirements and architecture
  briefs as agent inputs.
- **Evaluating** the intermediate steps of multi-agent development, not just
  the final code.
- **Research** on requirements engineering, software architecture recovery
  and traceability.

## 🚀 Quick start

```python
from datasets import load_dataset
docs = load_dataset("anonymous/code-theseus", "documents", split="train")
repos = load_dataset("anonymous/code-theseus", "repos", split="train")
graphs = dict(zip(repos["repo_id"], repos["arcan_graph"]))
graph = graphs[docs[0]["repo_id"]]  # input graph for the first document
```

## 🗂️ Configs

### `documents` (21,623 rows): one row per (repository, generator)

| column | description |
|---|---|
| `repo_id` | `owner\|repo`; join key to `repos` |
| `generator` | `gemma-4-31b-it` / `qwen3.5-122b-a10b` |
| `checkpoint` | Hugging Face checkpoint served with vLLM |
| `intent`, `requirements`, `architecture` | generated Markdown; null if missing, truncated or empty (56 docs) |
| `reasoning_*` | the generator's thinking trace (Qwen only, null otherwise) |

### `repos` (10,813 rows): one row per repository

| column | description |
|---|---|
| `repo_id` | `owner\|repo` |
| `branch` | `main` (GitHub corpus) or `commit0` ([Commit0](https://github.com/commit-0/commit0) libraries) |
| `url` | GitHub URL |
| `commit_sha` | analysed commit; documents describe the repository at this commit |
| `language`, `description`, `stars` | GitHub metadata at collection time |
| `arcan_graph` | package-level dependency graph from [Arcan](https://www.arcan.tech/): `nodes` (`vertex_id`, `name`, `component_type`, `fan_in`, `fan_out`, `lines_of_code`, `pagerank`) and weighted `edges` (`source`/`target` are `vertex_id`s) |

## 📜 License

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). This covers the
generated documents and dependency graphs. The original repositories keep
their own licenses.

	---
	license: cc-by-4.0
	pretty_name: code-theseus
	task_categories:
	- text-generation
	language:
	- en
	size_categories:
	- 10K<n<100K
	tags:
	- software-engineering
	- requirements-engineering
	- software-architecture
	- reverse-engineering
	- c4-model
	- code-generation
	- coding-agents
	- llm
	- synthetic
	configs:
	- config_name: documents
	data_files: documents/train.parquet
	default: true
	- config_name: repos
	data_files: repos/train.parquet
	---

	<div align="center">

	# 🚢 code-theseus

	**The design behind 10,000+ open-source repositories: intent, requirements
	and architecture, aligned with the code, ready for training coding agents.**

	\| 📦 10,813 \| 📄 21,623 \| 🌐 4 \| 🤖 2 \|
	\|:---:\|:---:\|:---:\|:---:\|
	\| repositories \| document sets \| languages: Java, Python, C/C++, C# \| generator LLMs \|



	</div>

	## 🧭 Why this dataset

	Coding agents increasingly design before they code, but almost no data
	connects code to the requirements and architecture behind it: real projects
	rarely keep these documents, and when they do they are outdated or private.
	code-theseus recovers them from the source code, at scale.

	## 📦 What's inside

	Every repository comes with three aligned documents, generated from its
	dependency graph and key project files:

	\| \| Document \| What it captures \|
	\|---\|---\|---\|
	\| 🎯 \| `intent` \| The "initial prompt": mission, problem, capabilities, user workflows, quality expectations \|
	\| 📋 \| `requirements` \| `REQ-FUNC-` / `REQ-NFR-` items with statement, rationale, acceptance criteria, verification method and priority \|
	\| 🏗️ \| `architecture` \| A C4 design (context, container, component) with Mermaid C4 diagrams \|

	…plus the package-level dependency graph each document was generated
	from, and a link to the exact commit it describes. No source code is
	redistributed: check out `url` at `commit_sha` to recover it.

	## 🔁 Does it carry the design?

	In the paper's Ship of Theseus test, a coding agent rebuilt
	[Commit0](https://github.com/commit-0/commit0) libraries from these
	documents alone. With requirements and architecture, it built a module
	structure significantly closer to the original than with intent alone
	(module F1 0.54 → 0.63), at the same test pass rate.

	## 🏢 Use it for

	- Fine-tuning models that write specs from code (graph → intent,
	requirements, architecture) or code from specs.
	- Spec-driven coding agents. Realistic requirements and architecture
	briefs as agent inputs.
	- Evaluating the intermediate steps of multi-agent development, not just
	the final code.
	- Research on requirements engineering, software architecture recovery
	and traceability.

	## 🚀 Quick start

	```python
	from datasets import load_dataset

	docs = load_dataset("anonymous/code-theseus", "documents", split="train")
	repos = load_dataset("anonymous/code-theseus", "repos", split="train")
	graphs = dict(zip(repos["repo_id"], repos["arcan_graph"]))
	graph = graphs[docs[0]["repo_id"]] # input graph for the first document
	```

	## 🗂️ Configs

	### `documents` (21,623 rows): one row per (repository, generator)

	\| column \| description \|
	\|---\|---\|
	\| `repo_id` \| `owner\\|repo`; join key to `repos` \|
	\| `generator` \| `gemma-4-31b-it` / `qwen3.5-122b-a10b` \|
	\| `checkpoint` \| Hugging Face checkpoint served with vLLM \|
	\| `intent`, `requirements`, `architecture` \| generated Markdown; null if missing, truncated or empty (56 docs) \|
	\| `reasoning_*` \| the generator's thinking trace (Qwen only, null otherwise) \|

	### `repos` (10,813 rows): one row per repository

	\| column \| description \|
	\|---\|---\|
	\| `repo_id` \| `owner\\|repo` \|
	\| `branch` \| `main` (GitHub corpus) or `commit0` ([Commit0](https://github.com/commit-0/commit0) libraries) \|
	\| `url` \| GitHub URL \|
	\| `commit_sha` \| analysed commit; documents describe the repository at this commit \|
	\| `language`, `description`, `stars` \| GitHub metadata at collection time \|
	\| `arcan_graph` \| package-level dependency graph from [Arcan](https://www.arcan.tech/): `nodes` (`vertex_id`, `name`, `component_type`, `fan_in`, `fan_out`, `lines_of_code`, `pagerank`) and weighted `edges` (`source`/`target` are `vertex_id`s) \|

	## 📜 License

	[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). This covers the
	generated documents and dependency graphs. The original repositories keep
	their own licenses.