ConcoLixir uses a reactive LLM oracle to improve line coverage in Python concolic testing by 8.6 to 17 percentage points on synthetic, real-world, and library targets.
Python Symbolic Execution with LLM-powered Code Generation, September 2024
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A framework combining legal ontology, rule extraction, and solver reasoning verifies whether AI explanations for CalFresh eligibility align with statutory constraints.
citing papers explorer
-
ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing
ConcoLixir uses a reactive LLM oracle to improve line coverage in Python concolic testing by 8.6 to 17 percentage points on synthetic, real-world, and library targets.
-
A Neuro-Symbolic Framework for Accountability in Public-Sector AI
A framework combining legal ontology, rule extraction, and solver reasoning verifies whether AI explanations for CalFresh eligibility align with statutory constraints.