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- name: dependencies
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list: string
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- name: has_bug
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dtype: bool
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- name: bug_types
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list: string
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- name: bug_line_offsets
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list: int32
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- name: bug_absolute_lines
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list: int32
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- name: bug_severities
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list: string
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- name: bug_traces
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list: string
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- name: category
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dtype: string
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- name: difficulty
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dtype: string
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- name: requires_interprocedural
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dtype: bool
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- name: start_line
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dtype: int32
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- name: end_line
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dtype: int32
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splits:
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- name: test
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num_bytes: 197434
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num_examples: 523
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download_size: 62235
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dataset_size: 197434
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configs:
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- config_name: default
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data_files:
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- split: test
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path: data/test-*
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---
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license: mit
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task_categories:
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- text-classification
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- text-generation
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language:
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- en
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tags:
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- code
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- static-analysis
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- bug-detection
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- c
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- memory-safety
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size_categories:
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- n<1K
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---
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+
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# Infer Pulse Static Analysis Evaluation Dataset
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## Dataset Description
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+
This dataset contains **523 C functions** extracted from Meta's [Infer](https://fbinfer.com/) static analyzer test suite, specifically the Pulse analyzer tests. It's designed for **evaluating** Large Language Models (LLMs) on static analysis tasks, particularly memory safety bug detection in C code.
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**Note:** This is an evaluation-only dataset. All examples are provided in the `test` split.
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### Key Features
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- **523 individual C functions** with ground truth bug annotations
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- **51 unique source files** from Infer's test suite
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- **5 bug categories**: NULL pointer dereference, memory leak, use-after-free, uninitialized value, resource leak
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+
- **Smart anonymization**: Function names preserve semantic meaning while removing evaluation hints (`_bad`, `_ok` suffixes)
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- **Multiple bugs per function**: Some functions contain multiple bug types (2.5% of dataset)
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- **Realistic code**: Actual test cases from a production static analyzer
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## Dataset Statistics
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- **Total examples:** 523
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- **With bugs:** 217 (41.5%)
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- **Safe (no bugs):** 306 (58.5%)
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- **Unique source files:** 51
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### Bug Category Distribution
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| Category | Count | Percentage |
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|----------|-------|------------|
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| safe | 306 | 58.5% |
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| nullptr_dereference | 112 | 21.4% |
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| other | 68 | 13.0% |
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| memory_leak | 18 | 3.4% |
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| uninitialized_value | 12 | 2.3% |
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| use_after_free | 4 | 0.8% |
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| resource_leak | 3 | 0.6% |
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### Difficulty Distribution
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| Difficulty | Count | Percentage |
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|------------|-------|------------|
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| advanced | 523 | 100.0% |
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## Dataset Structure
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Each example contains:
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- **id**: Unique identifier
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- **source_file**: Original file in Infer test suite
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- **original_function_name**: Original name from Infer tests
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- **anonymized_function_name**: Name with hints removed (e.g., `malloc_no_check_bad` → `malloc_no_check`)
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- **function_code**: Complete C function code
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- **includes**: Required #include statements
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- **dependencies**: Helper functions/structs needed
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- **has_bug**: Boolean indicating if function has bugs
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- **bug_types**: List of bug types (NULLPTR_DEREFERENCE, MEMORY_LEAK, etc.)
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- **bug_line_offsets**: Line numbers relative to function start
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- **bug_absolute_lines**: Absolute line numbers in original file
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- **bug_severities**: Bug severity levels
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- **bug_traces**: Detailed trace information from Infer
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- **category**: Primary bug category or "safe"
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- **difficulty**: basic/intermediate/advanced
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- **requires_interprocedural**: Whether analysis requires understanding function calls
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- **start_line/end_line**: Location in original source file
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## Example
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```python
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from datasets import load_dataset
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dataset = load_dataset("YOUR_USERNAME/infer-pulse-eval")
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# Get first test example
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example = dataset['test'][0]
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print(f"Function: {example['anonymized_function_name']}")
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print(f"Has bug: {example['has_bug']}")
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if example['has_bug']:
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print(f"Bug types: {example['bug_types']}")
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print(f"\nCode:\n{example['function_code']}")
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```
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## Intended Use
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This dataset is designed for:
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1. **Evaluating LLMs on static analysis tasks**
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2. **Benchmarking bug detection capabilities**
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3. **Training models for code understanding**
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4. **Researching AI-assisted program analysis**
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### Evaluation Protocol
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Send the LLM:
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- System prompt with bug type definitions and analysis rules
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- User prompt with the `function_code` and any needed `includes`
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Expected LLM response format:
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```json
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{
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"has_bug": true|false,
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"bugs": [
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{
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"type": "NULLPTR_DEREFERENCE",
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"line": 3,
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"explanation": "malloc can return NULL, dereferenced without check"
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}
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]
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}
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```
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Compare against ground truth `has_bug` and `bug_types` fields.
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## Anonymization Strategy
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Function names are "anonymized" by removing evaluation hints while **preserving semantic meaning**:
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- **Removed**: `_bad`, `_ok`, `_good`, `_latent` suffixes, `FP_`, `FN_` prefixes
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- **Preserved**: Descriptive parts (e.g., `malloc_no_check`, `use_after_free_simple`)
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This maintains realistic code analysis conditions without giving away answers.
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## Data Source
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All examples are extracted from Meta's Infer static analyzer:
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- Repository: https://github.com/facebook/infer
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- Test suite: `infer/tests/codetoanalyze/c/pulse/`
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- Ground truth: `issues.exp` file from Infer's test expectations
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## License
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MIT License (same as Infer project)
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## Citation
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If you use this dataset, please cite:
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```bibtex
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@misc{{infer-pulse-eval-2024,
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title={{Infer Pulse Static Analysis Evaluation Dataset}},
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author={{Extracted from Meta's Infer project}},
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year={{2024}},
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url={{https://github.com/facebook/infer}}
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}}
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```
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## Contact
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For questions or issues, please open an issue on the dataset repository.
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## Changelog
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### Version 1.0 (2024-11-08)
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- Initial release
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- 523 examples from 51 source files
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- Smart anonymization preserving semantic meaning
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- Multiple bugs per function support
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