| --- |
| license: apache-2.0 |
| task_categories: |
| - text2text-generation |
| - feature-extraction |
| language: |
| - en |
| tags: |
| - code-generation |
| - swe-agent |
| - swe-bench |
| - program-synthesis |
| - self-healing-code |
| - deepseek-coder |
| - ast |
| - formal-verification |
| pretty_name: AI Code Generation & SWE Agents 2026 |
| size_categories: |
| - n<1K |
| --- |
| |
| # 💻 AI Code Generation, SWE Agents & Program Synthesis Dataset (2026 Edition) |
|
|
| A structured research dataset featuring **3,181 domain-verified research papers and 771 official code repositories** focused on Autonomous Software Engineering Agents (SWE-bench), Program Synthesis, DeepSeek-Coder-V2, Qwen2.5-Coder, Test-Driven Code Repair, Self-Healing Software, AST Semantic Modeling, and Formal Logic Verification (2023–2026). |
|
|
| Built with **Universal Scientific Engine V17.1 Gold**, providing 47 schema attributes with verified repository attribution, 8 AI topological semantic clusters, pre-calculated Top-3 Semantic Nearest Neighbors Graph, structured benchmark leaderboards, and native 384-dimensional dense PyTorch embeddings. |
|
|
| --- |
|
|
| ## 📊 Dataset Schema Highlights (47 Columns) |
|
|
| | Field | Type | Description | |
| | :--- | :--- | :--- | |
| | `paper_id` | String | Unique ArXiv identifier | |
| | `title` | String | Research paper title | |
| | `cluster_topic_name` | String | 1 of 8 AI Topological Semantic Clusters | |
| | `code_agent_execution_mode` | String | Execution mode (SWE-bench Agent, Pair Programmer, Self-Repair) | |
| | `coding_foundation_backbone` | String | Model backbone (DeepSeek-Coder-V2, Qwen2.5-Coder, Claude-3.5) | |
| | `programming_languages_supported`| List[String] | Supported languages (Python, Rust, C++, TypeScript, Go) | |
| | `tested_benchmarks` | List[String] | Benchmarks evaluated (SWE-bench, HumanEval, MBPP, LiveCodeBench) | |
| | `benchmark_leaderboard_json` | List[Struct] | Structured pass@1 & resolved scores | |
| | `semantic_nearest_neighbors_top3`| List[Struct] | Pre-calculated top-3 related papers with cosine similarity | |
| | `commercial_ip_safety_score` | Integer | 0–100 commercial compliance index (94% Enterprise Safe) | |
| | `tldr_neural_summary` | String | 15-word executive summary of key innovation | |
| | `title_vector_384d` | List[Float] | 384d PyTorch embedding (`all-MiniLM-L6-v2`) | |
| | `abstract_vector_384d` | List[Float] | 384d dense contextual PyTorch embedding | |
| | `reproduction_recipe` | String | 1-line bash setup command | |
|
|
| --- |
|
|
| ## 🧩 8 AI Semantic Clusters Breakdown |
|
|
| 1. `Test-Driven Program Repair & Self-Healing Code Synthesis` (599 papers) |
| 2. `Code Foundation Models & Specialized Instruction Distillation` (501 papers) |
| 3. `Formal Verification, Theorem Proving & Symbolic Logic` (452 papers) |
| 4. `Syntax-Guided AST Modeling & Semantic Code Search` (421 papers) |
| 5. `Interactive Coding Assistants & Human-AI Pair Programming` (356 papers) |
| 6. `Static Analysis, Vulnerability Detection & Automated Security Patching` (336 papers) |
| 7. `Autonomous Repo-Level Software Engineering Agents (SWE-bench)` (276 papers) |
| 8. `Multi-Language Code Translation & Cross-Platform Migration` (240 papers) |
|
|
| --- |
|
|
| ## 📊 Interactive OpenAngels Visual Dashboard Included |
| Open `DATASET_ANALYTICS_DASHBOARD_100_SAMPLE.html` directly in your browser (Chrome/Edge/Safari) to explore the interactive visual intelligence directory with real-time filtering, search, and paper metrics. |
|
|
| --- |
|
|
| ## 💻 1-Click Python Quickstart |
|
|
| ```python |
| import pyarrow.parquet as pq |
| |
| # Load 100-Sample Teaser |
| table = pq.read_table("AI_CODE_GENERATION_SWE_AGENTS_PROGRAM_SYNTHESIS_2026_100_SAMPLE.parquet") |
| df = table.to_pandas() |
| |
| print(f"Loaded {len(df)} sample AI Coding papers.") |
| print(f"Top Paper: {df['title'].iloc[0]}") |
| print(f"Execution Mode: {df['code_agent_execution_mode'].iloc[0]}") |
| print(f"Top-3 Nearest Neighbors: {df['semantic_nearest_neighbors_top3'].iloc[0]}") |
| ``` |
|
|
| --- |
|
|
| ## 🚀 Get the Full 3,181-Paper Enterprise Edition |
|
|
| The complete commercial production dataset (3,181 papers in Parquet with 384d vectors, SQLite DB, Clean CSV, Interactive OpenAngels HTML Dashboard, and JSON) is available here: |
|
|
| 👉 **[BeatsProm AI Code Generation & SWE Agents Dataset Full Edition](https://beatsprom.gumroad.com/l/ai-code-generation-swe-agents-2026)** |
