Add dataset card

README.md

@@ -1,27 +1,85 @@
----
-dataset_info:
-  features:
-  - name: method_name
-    dtype: string
-  - name: sample_id
-    dtype: string
-  - name: input
-    dtype: string
-  - name: input_types
-    dtype: string
-  - name: output
-    dtype: string
-  - name: output_type
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 568062502
-    num_examples: 2840000
-  download_size: 71133925
-  dataset_size: 568062502
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+# AutoStub Training Dataset
+
+This dataset contains input-output pairs used for training the AutoStub system, which automatically generates symbolic stubs for external functions during symbolic execution.
+
+## Dataset Description
+
+The dataset consists of input-output pairs for 273 methods from Java standard libraries, focusing on primitive types and string operations. It was generated using a stratified sampling approach to ensure diverse inputs across different data types.
+
+### Dataset Structure
+
+The dataset is organized as a single CSV file with the following columns:
+
+- `method_name`: The name of the Java method
+- `sample_id`: Unique identifier for each sample (method_name + sample index)
+- `input`: Input values provided to the method (as string representation)
+- `input_types`: Types of input parameters
+- `output`: Output value returned by the method
+- `output_type`: Return type of the method
+
+### Method Coverage
+
+The dataset covers methods from the following Java classes:
+- `java.lang.Boolean`
+- `java.lang.Double`
+- `java.lang.Float`
+- `java.lang.String`
+- `java.lang.Byte`
+- `java.lang.Short`
+- `java.lang.Character`
+- `java.lang.Integer`
+- `java.lang.Long`
+- `java.lang.Math`
+- `java.lang.StrictMath`
+
+### Dataset Creation
+
+The dataset was created by:
+1. Identifying suitable methods in Java standard libraries
+2. Using reflection to dynamically invoke methods with random inputs
+3. Collecting input-output pairs for each method
+4. Applying stratified sampling to ensure diverse inputs
+
+## Usage
+
+### Loading the Dataset
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("username/autostub-dataset")
+
+# Get samples for a specific method
+method_samples = dataset["train"].filter(lambda x: x["method_name"] == "public_boolean_java_lang_Boolean_booleanValue__")
+
+# Access a specific sample
+sample = dataset["train"][0]
+print(f"Method: {sample['method_name']}")
+print(f"Input: {sample['input']}")
+print(f"Output: {sample['output']}")
+```
+
+### Applications
+
+This dataset can be used to:
+- Train machine learning models to approximate Java method behavior
+- Evaluate the accuracy of symbolic stubs for symbolic execution
+- Study the behavior of Java standard library methods across diverse inputs
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@inproceedings{maechtle2025autostub,
+  title={AutoStub: Genetic Programming-Based Stub Creation for Symbolic Execution},
+  author={Felix M{"a}chtle, Nils Loose, Jan-Niclas Serr, Jonas Sander, Thomas Eisenbarth},
+  booktitle={Proceedings of the 18th ACM/IEEE International Workshop on Search-Based and Fuzz Testing, SBFT 2025},
+  year={2025}
+}
+```
+
+## Source
+
+This dataset is derived from the [AutoStub](https://github.com/UzL-ITS/AutoStub) project.