arXiv AI
SWE-Proof: Can Language Models Resolve Real-World Issues with Machine-Checked Proofs?
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arXiv AI
Oct 9
Beyond Type-checking: Towards Holistic Evaluation of Formal Specification Generation
The paper presents a unified dataset of 350 Lean tasks to evaluate specification generation (SpecGen) for verifiable code, combining metrics of formal validity, reference similarity, equivalence, and behavioural adequacy. It highlights that restricting similarity measures to a subset of tasks can shift rankings, and shows that a perfect postcondition score can still miss critical input coverage, underscoring the need for separate feedback on input and output constraints.
arXiv AI
Oct 15
claimcheck: Measuring and Improving Specification Faithfulness
arXiv:2610.17358v1 Announce Type: cross Abstract: Formal verification proves that a program satisfies its specification, but says nothing about whether the specification captures what the author mean...
arXiv AI
Aug 11
P$^{3}$: Joint Program-and-Proof Planning for Verified Code Generation
arXiv:2608. 09277v1 Announce Type: new Abstract: Verified code generation asks a large language model (LLM) to generate both an executable program and a machine-checkable proof that the program meets a formal specification, promising software that is correct by construction.
arXiv AI
Oct 1
Self-Spec Verifiable Code Generation
arXiv:2609.39568v1 Announce Type: cross Abstract: Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable...
Hugging Face Trending Papers
Jul 7
Harnessing Code Agents for Automatic Software Verification
Formal verification offers the strongest guarantee of software correctness, but it does not scale: the proofs demanded by interactive theorem provers such as Coq require enormous expert effort. Large language models (LLMs) promise to generate these proofs automatically, yet existing approaches wire a fixed, human-designed proof strategy into the system and constrain the model to follow it (retrieving premises and predicting tactics one step at a time, or splitting goals by divide-and-conquer), and still prove only a fraction of their target theorems.
Hugging Face Trending Papers
Aug 13
Vero: Can AI Agents Build Formally Verified Software Repositories?
AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code. Verified code generation, in which an agent produces both an implementation and a machine-checked proof of its specification, offers a stronger path toward trustworthy AI-generated software.