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Synthesis-aided crash consistency for storage systems

By Jacob Van Geffen, Xi Wang, Emina Torlak, James Bornholt
2023
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Reliable storage systems must be crash consistent – guaranteed to recover to a consistent state after a crash. Crash consistency is non-trivial as it requires maintaining complex invariants about persistent data structures in the presence of caching, reordering, and system failures. Current programming models offer little support for implementing crash consistency, forcing storage system developers to roll their own consistency mechanisms. Bugs in these mechanisms can lead to severe data loss for applications that rely on persistent storage.

This paper presents a new synthesis-aided programming model for building crash-consistent storage systems. In this approach, storage systems can assume an angelic crash-consistency model, where the underlying storage stack promises to resolve crashes in favor of consistency whenever possible. To realize this model, we introduce a new labeled writes interface for developers to identify their writes to disk, and develop a program synthesis tool, DepSynth, that generates dependency rules to enforce crash consistency over these labeled writes. We evaluate our model in a case study on a production storage system at Amazon Web Services. We find that DepSynth can automate crash consistency for this complex storage system, with similar results to existing expert-written code, and can automatically identify and correct consistency and performance issues.
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