Deterministic Parsing The same input code will always produce the same structured output based purely on defined rules, not probability.
-> Basically what Deterministic Parsing means, it does't guesses the code patters like normal LLcode (break down data/code into manageable components to understand them) by using real parsers like babel for javascript and ast module for python.
The parser converts code into an Abstract Syntax Tree (AST). It’s mathematically derived from syntax rules.
Example => Code: function add(a, b) { return a + b; }
AST Output: FunctionDeclaration name: add params: a, b body: ReturnStatement BinaryExpression (+)
-> If you let an LLM analyze raw code, it can: Invent relationships Miss edge cases Misidentify architecture
-> But if you parse via AST: Every function is real. Every import is real. Every class inheritance is provable. Every dependency edge is factual.
LLMs doesn't read the code, the parser does that in the backend. LLMs just generates a Learning path.