Update README.md

README.md

@@ -11,7 +11,7 @@ size_categories:
 
 # Overview
 
-This dataset contains 18,219 rows of code-docstring-ast data along with additional metadata. Data was gathered from various Python libraries and frameworks
+This dataset contains 18,219 rows of code-docstring-ast data along with additional metadata. Data was gathered from various Python libraries and frameworks and their
 publicly available GitHub repos. Initial raw dataset count was 25,480 down to 18,219 after preprocessing.
 
 # Sources
@@ -63,4 +63,82 @@ An instance of the dataset is as follows:
   <line_number> : <The line number of the function, method, or class within the file>,
   <ast_sequence> : <The ast sequence of the raw source code. Scroll down for more info about this>
 }
-```
+```
+
+# The AST Sequence
+
+A function recursively converts the AST tree into a linear sequence. It uses depth markers (├1>, └2>, etc.) to show parent-child relationships. It also adds node identifiers by pairing
+each node type with a meaningful identifier. Furthermore, pruning is also applied to irrelevant and shallow identifiers to denoise the dataset. 
+
+Here's an example of how the AST sequence is generated:
+
+Example Code
+```
+def calculate_area(radius):
+    """
+    Calculate the area of a circle.
+    
+    Parameters:
+        radius (float): The radius of the circle
+        
+    Returns:
+        float: The area of the circle
+    """
+    PI = 3.14159
+    area = PI * radius * radius
+    return area
+```
+
+Resulting AST Sequence
+```
+FunctionDef:calculate_area
+├1> args:[radius]
+├1> Assign:PI
+│ └2> Constant:
+├1> Assign:area
+│ └2> BinOp:
+│   ├3> BinOp:
+│   │ ├4> Name:PI
+│   │ └4> Name:radius
+│   └3> Name:radius
+└1> Return:
+  └2> Name:area
+```
+
+1. The code is parsed via Python's `ast` module
+2. A method traverses this tree and linearizes the sequence
+3. Each node is then converted to a string with type-identifier keys
+4. Structural relationships are preserved using the depth markers
+5. Denoising of irrelevant and shallow nodes are applied
+
+# Preprocessing
+
+The following preprocessing steps were applied:
+
+## Text Cleaning
+
+- Removed comments
+- Filtering unusual/control characters
+- Removed trailing whitespaces
+- Converts all whitespace into a single spaces
+- Removed tags from docstrings
+
+## AST Cleaning
+
+- Removed noise using a custom blacklist
+- Removed abnormally long nodes (>100)
+- Stripped blank AST entries
+- Ensured ASTs start with the proper root nodes (FunctionDef or ClassDef)
+
+## Language Filtering
+
+- Removed non-English documentations
+- Keeps an item if detection fails
+
+## Similarity Filtering
+
+- Removed entries where similarity exceeds threshold (0.7)
+
+# Split
+
+- Dataset was split into a 70/15/15 ratio