Update README.md

README.md

@@ -22,20 +22,18 @@ The dataset bridges the gap between source-level vulnerability datasets and prac
 ## Dataset Structure
 
 - `CompRealVul_Bin.zip`: Contains all compiled `.exe` binary files  
-- `metadata.csv`: Metadata file with the following fields:
+- `CompRealVul_metadata.csv`: Metadata file with the following fields:
 
 | Column          | Description                                                                 |
 |-----------------|-----------------------------------------------------------------------------|
-| `name`          | Identifier of the function (matches CompRealVul)                            |
-| `binary_path`   | Relative path to the `.exe` file inside the ZIP archive                     |
-| `cwe`           | CWE identifier for the vulnerability (or `-1` if unknown or non-vulnerable) |
-| `target`        | Vulnerability label (`1.0` = vulnerable, `0.0` = non-vulnerable)            |
-| `split`         | Dataset split (currently only `train`)                                      |
+| `file_name`     | Name of the .exe file                                                       |
+| `function_name` | The name of the target function in the .exe file                            |
+| `label`         | Vulnerability label (`1.0` = vulnerable, `0.0` = non-vulnerable)            |
 
 **Example:**
 ```csv
-name,binary_path,cwe,target,split
-func_123,bin/func_123.exe,CWE-120,1.0,train
+file_name,function_name,label
+func_123.exe,func_123,1.0
 ```
 
 ## Usage
@@ -47,7 +45,7 @@ import pandas as pd
 import zipfile
 
 # Load metadata
-df = pd.read_csv("metadata.csv")
+df = pd.read_csv("CompRealVul_metadata.csv")
 
 # Access the ZIP archive
 with zipfile.ZipFile("CompRealVul_Bin.zip", "r") as zip_ref: