LLM-Based Invariant Testing for Software Functional Bugs

• URL: http://arxiv.org/abs/2607.18711v1
• Date: Tue, 21 Jul 2026 05:07:22 GMT
• Title: LLM-Based Invariant Testing for Software Functional Bugs
• Abstract summary: We present LISA, a novel LLM-based invariant testing framework for software functional bugs.<n> LISA iteratively generates API sequences and program invariants guided by API n-gram feedback.
• Score: 4.8632580114281065
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Manually writing unit tests to uncover functional bugs in software libraries is not only time-consuming but also requires a deep understanding of the intended semantics of the APIs. Heuristic-based test generation methods suffer from low usability because they cannot reason about program semantics or interpret source code and documentation as humans do. Traditional fuzzing techniques like OSS-Fuzz often rely on crashes to detect bugs, but functional bugs do not always cause crashes. To overcome these limitations, we present LISA, a novel LLM-based invariant testing framework for software functional bugs. LISA iteratively generates API sequences and program invariants guided by API n-gram feedback, achieving higher bug-detection rates and competitive code coverage compared with both fuzzing and prior LLM-based test generation approaches, and reporting each finding as a high-confidence bug candidate for developer confirmation.

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