Making TransactionIsolation Checking Practical

2026-04-22

AI Summary

Verifying transaction isolation levels in modern key-value stores is highly challenging due to their operational complexity and opaque internal implementations. This work proposes Boomslang, the first general-purpose, modular framework for isolation level verification that requires no knowledge of database internals. Its frontend parses transaction traces into abstract semantic graphs and converts them into an intermediate representation, while its backend leverages SMT-based constraint solving for verification. A key innovation is the introduction of superpositions, an abstraction that effectively handles uncertainty, enabling support for five isolation levels previously unverifiable by existing tools. With only 271–386 lines of code, Boomslang reproduces three state-of-the-art checkers with comparable or superior performance, discovers a new vulnerability in TiDB, audits the metadata layer of JuiceFS, validates MariaDB’s behavior, and confirms the correctness of strict serializability theory.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Search and Optimization: Distributed Search

Application Category

• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Checking whether database transactions adhere to isolation levels is a crucial yet challenging problem. We present Boomslang, the first general-purpose checking framework capable of verifying configurations that were previously uncheckable. Boomslang advances beyond prior work in three key aspects: (1) it supports arbitrary operation types provided by modern transactional key-value stores, (2) it requires no knowledge of database internals, and (3) it offers a modular, extensible pipeline amenable to customization and optimizations. Boomslang adopts a front-/back-end separation. As the front-end, it parses a database trace into an Abstract Semantic Graph, which is then lowered -- via semantic analysis -- into a low-level intermediate representation (IR). The back-end converts this IR to a set of constraints for SMT solving. This design is enabled by a key abstraction in the IR, called superpositions, which capture the uncertainty and complexity caused by arbitrary operations and missing information. Our experiments show that with just 271--386 lines of code, the core logic of three prior checkers can be reimplemented as Boomslang modules, achieving comparable or superior performance. Using Boomslang, we also identify a new bug in TiDB, audit the metadata layer of the JuiceFS file system, check vendor-specific behavior in MariaDB, support five previously unchecked isolation levels, and confirm a theoretical result on the correctness of strict serializability.

Problem

• transaction isolation
• database verification
• isolation level checking
• consistency checking
• database correctness

Innovation

• transaction isolation
• abstract semantic graph
• superpositions
• SMT solving
• modular verification framework