  Ensuring correctness is a pivotal aspect of software engineering. Among the
various strategies available, software verification offers a definitive
assurance of correctness. Nevertheless, writing verification proofs is
resource-intensive and manpower-consuming, and there is a great need to
automate this process. We introduce Selene in this paper, which is the first
project-level automated proof benchmark constructed based on the real-world
industrial-level operating system microkernel, seL4. Selene provides a
comprehensive framework for end-to-end proof generation and a lightweight
verification environment. Our experimental results with advanced large language
models (LLMs), such as GPT-3.5-turbo and GPT-4, highlight the capabilities of
LLMs in the domain of automated proof generation. Additionally, our further
proposed augmentations indicate that the challenges presented by Selene can be
mitigated in future research endeavors.
