abstract-invariant-generator

# Abstract Invariant Generator ## Overview This skill uses abstract interpretation to automatically infer loop invariants, function preconditions, and postconditions. It generates formal specifications that support verification and reasoning about program correctness. ## Invariant Generation Workflow ### Step 1: Identify Specification Points Analyze the code to identify where invariants are needed: **Loop Invariants**: For each loop ```python while condition: # Need: invariant that holds before/after each iteration body ``` **Function Contracts**: For each function ```python def function(params): # Need: precondition (what must be true on entry) body # Need: postcondition (what is guaranteed on exit) ``` **Assertions**: For verification points ```python # Need: invariant that holds at this point assert property ``` ### Step 2: Perform Abstract Interpretation Use abstract domains to infer properties: **Interval Analysis**: Infer numeric ranges ```python i = 0 while i < n: # Inferred: 0 ≤ i < n i += 1 # Inferred: i = n ``` **Relational Analysis**: Infer relationships between variables ```python i = 0 j = 0 while i < n: # Inferred: i = j i += 1 j += 1 ``` **Shape Analysis**: Infer data structure properties ```python while node is not None: # Inferred: node is in the linked list node = node.next ``` ### Step 3: Generate Loop Invariants For each loop, generate an invariant that: 1. Holds before the loop (initialization...