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README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-generation
+- feature-extraction
+language:
+- en
+tags:
+- system-calls
+- strace
+- linux
+- syscalls
+- operating-systems
+- code
+pretty_name: Linux Strace Traces Dataset
+size_categories:
+- n<1K
+---
+
+# Linux Strace Traces Dataset
+
+A comprehensive collection of strace traces from common Linux utilities, designed for training AI models on system call patterns, program behavior analysis, and operating system interactions.
+
+## Dataset Description
+
+This dataset contains **357 strace traces** captured from 119 different Linux command-line utilities, with each utility executed 3 times to capture runtime variations. Each trace includes detailed system call information with timestamps, arguments, and execution times.
+
+### Dataset Statistics
+
+- **Total traces**: 357 (119 unique commands × 3 runs each)
+- **Categories**: 8
+- **Format**: Parquet (Hugging Face native)
+- **Raw size**: ~40 MB
+- **Compressed size**: ~5 MB (Parquet)
+- **License**: MIT
+
+### Runtime Diversity
+
+Each command was executed 3 times to capture natural variations in program execution:
+- Different process IDs (PIDs)
+- Different memory addresses (ASLR randomization)
+- Different timestamps with microsecond precision
+- Slight variations in syscall timing
+
+This diversity helps train more robust AI models that can generalize across different execution contexts.
+
+### Categories
+
+1. **File I/O Operations** (75 traces = 25 commands × 3 runs)
+   - File reading: `cat`, `head`, `tail`, `less`
+   - File manipulation: `cp`, `mv`, `touch`, `rm`
+   - Directory operations: `mkdir`, `rmdir`, `find`
+   - File information: `stat`, `file`, `ls`, `du`, `df`
+
+2. **Text Processing** (69 traces = 23 commands × 3 runs)
+   - Pattern matching: `grep` (simple, case-insensitive, recursive, count)
+   - Text transformation: `sed`, `awk`, `tr`
+   - Sorting & filtering: `sort`, `uniq`, `cut`, `paste`
+   - Analysis: `wc`, `diff`, `cmp`
+
+3. **Process & System Info** (51 traces = 17 commands × 3 runs)
+   - Process listing: `ps`, `top`, `pgrep`
+   - System information: `uptime`, `who`, `whoami`, `id`, `uname`, `hostname`
+   - Environment: `env`, `printenv`
+   - Time: `date`, `cal`
+   - Resources: `free`, `vmstat`
+
+4. **Networking** (33 traces = 11 commands × 3 runs)
+   - Network requests: `ping`, `curl`, `wget`
+   - DNS queries: `host`, `dig`, `nslookup`
+   - Network info: `ip`, `ss`, `netstat`
+
+5. **Compression & Archives** (36 traces = 12 commands × 3 runs)
+   - Tar operations: create, extract, list (with/without gzip)
+   - Compression: `gzip`, `bzip2`
+   - Zip operations: `zip`, `unzip`
+
+6. **Scripting & Execution** (45 traces = 15 commands × 3 runs)
+   - Shell execution: `bash`, `sh`
+   - Python execution: scripts and inline commands
+   - Utilities: `sleep`, `echo`, `printf`, `yes`, `seq`
+   - Tests: `true`, `false`, `test`, `expr`
+
+7. **Permissions & Ownership** (18 traces = 6 commands × 3 runs)
+   - Permission modification: `chmod` (numeric, symbolic, recursive)
+   - Permission viewing: `ls -l`
+   - Umask operations
+
+8. **Data Operations** (30 traces = 10 commands × 3 runs)
+   - Random data: `dd` with `/dev/urandom` and `/dev/zero`
+   - Encoding: `base64` (encode/decode)
+   - Hashing: `md5sum`, `sha1sum`, `sha256sum`
+   - Binary analysis: `hexdump`, `od`, `strings`
+
+## Dataset Structure
+
+### Data Fields
+
+- `id` (string): Unique identifier for the trace (e.g., "cat_simple_run1")
+- `category` (string): Category of the utility (e.g., "file_io")
+- `command` (string): Full command executed (e.g., "cat test.txt")
+- `strace` (string): Complete strace output with system calls
+- `duration` (float): Execution time in seconds
+- `timestamp` (string): ISO 8601 timestamp of trace capture
+- `num_lines` (int): Number of lines in the strace output
+- `size_bytes` (int): Size of the strace output in bytes
+- `run_number` (int): Run iteration (1, 2, or 3)
+
+### Data Splits
+
+This dataset contains a single split:
+- `train`: 357 examples (119 unique commands × 3 runs)
+
+### Example
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("YOUR_USERNAME/strace-dataset")
+
+# View first example
+example = dataset['train'][0]
+print(f"Command: {example['command']}")
+print(f"Category: {example['category']}")
+print(f"Duration: {example['duration']}s")
+print(f"Strace output (first 500 chars):\n{example['strace'][:500]}")
+```
+
+## Dataset Creation
+
+### Source Data
+
+All traces were generated in a controlled, isolated environment using the `strace` utility with the following flags:
+- `-f`: Follow child processes
+- `-s 256`: Capture up to 256 bytes of string arguments
+- `-tt`: Absolute timestamps with microsecond precision
+- `-T`: Show time spent in each syscall
+
+### Data Collection Process
+
+1. Temporary workspace created with test files (text, binary, CSV, etc.)
+2. Each utility executed with typical arguments/use cases
+3. Strace captured all system calls during execution
+4. Test data cleaned up after collection
+5. No sensitive information or system-specific paths included
+
+### Safety & Privacy
+
+- ✅ No sensitive data (passwords, keys, tokens)
+- ✅ No user-specific information
+- ✅ No production system paths
+- ✅ All operations performed in temporary directories
+- ✅ Safe for open-source release
+
+## Use Cases
+
+### Training AI Models
+
+- **System call prediction**: Predict next system calls based on program behavior
+- **Anomaly detection**: Identify unusual syscall patterns
+- **Program behavior modeling**: Learn normal execution patterns
+- **Security analysis**: Detect potential malicious behavior
+
+### Analysis & Research
+
+- Understanding program execution flows
+- Comparing syscall patterns across utilities
+- Educational resource for OS concepts
+- Benchmark for trace analysis tools
+
+### Code Examples
+
+#### Load and explore the dataset
+
+```python
+from datasets import load_dataset
+import pandas as pd
+
+# Load dataset
+ds = load_dataset("andrew000/straces")
+
+# Convert to pandas for analysis
+df = pd.DataFrame(ds['train'])
+
+# Group by category
+print(df.groupby('category').size())
+
+# Find longest-running commands
+print(df.nlargest(5, 'duration')[['command', 'duration']])
+
+# Analyze strace patterns
+for example in ds['train']:
+    if 'openat' in example['strace']:
+        print(f"{example['command']} opens files")
+```
+
+#### Extract specific syscalls
+
+```python
+import re
+
+def extract_syscalls(strace_output):
+    """Extract syscall names from strace output."""
+    pattern = r'\d+\s+[\d:.]+\s+(\w+)\('
+    return list(set(re.findall(pattern, strace_output)))
+
+# Find all syscalls used by cat
+cat_example = [ex for ex in ds['train'] if ex['id'] == 'cat_simple'][0]
+syscalls = extract_syscalls(cat_example['strace'])
+print(f"cat uses these syscalls: {syscalls}")
+```
+
+## Limitations
+
+- Traces captured on a specific Linux system (kernel version may affect syscalls)
+- Limited to common command-line utilities
+- No multi-threaded or complex concurrent workloads
+- Dataset size: 357 traces (medium-sized dataset)
+
+## Future Work
+
+- Add more utilities and use cases
+- Include long-running processes
+- Multi-threaded application traces
+- Different input sizes for scalability analysis
+- Traces from different Linux distributions/kernels
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{strace_traces_2025,
+  title={Linux Strace Traces Dataset},
+  author={andrew000},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/datasets/andrew000/straces}}
+}
+```
+
+## License
+
+MIT License - See LICENSE file for details
+
+## Acknowledgments
+
+Generated using the `strace` utility on Linux. All traces are from standard open-source utilities.

train.parquet

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