Despite recent advances, guaranteeing the correctness of large-scale distributed applications without compromising performance remains a challenging problem. Network and node failures are inevitable and, for some applications, careful control over how they are handled is essential. Unfortunately, existing approaches either completely hide these failures behind an atomic state machine replication (SMR) interface, or expose all of the network-level details, sacrificing atomicity. We propose a novel, compositional, atomic distributed object (ADO) model for strongly consistent distributed systems that combines the best of both options. The object-oriented API abstracts over protocol-specific details and decouples high-level correctness reasoning from implementation choices. At the same time, it intentionally exposes an abstract view of certain key distributed failure cases, thus allowing for more fine-grained control over them than SMR-like models. We demonstrate that proving properties even of composite distributed systems can be straightforward with our Coq verification framework, Advert, thanks to the ADO model. We also show that a variety of common protocols including multi-Paxos and Chain Replication refine the ADO semantics, which allows one to freely choose among them for an application's implementation without modifying ADO-level correctness proofs.

Jieung Kim is an assistant professor in the Department of Computer Engineering, College of Software and Convergence, Inha university. Before that, he was at Google (Google Core ML and Google Research) as a Research Engineer - Privacy & Security, and worked on various projects, including pKVM formal verification, HW/SW co-design for IoT devices, and developing machine learning model optimization frameworks. He obtained his Ph.D. from Yale University, M.S. from Korean Advanced Institute of Science and Technology (KAIST) with an outstanding M.S. thesis award, and B.S in Department of Computer Engineering at Sungkyunkwan University. During most of his research careers, his main focus is building models, frameworks, and techniques for formal verification of large-scale software and showing the feasibility of them with examples.