Extending Elle for Transaction Workloads with Duplicate Values

2026-07-19

AI Summary

This work addresses a critical limitation of existing black-box isolation verification tools, such as Elle, which rely on the unique-value assumption and thus struggle to analyze real-world transaction workloads containing duplicate values—a common source of isolation anomalies. To overcome this constraint, the paper introduces the first black-box isolation verification method capable of handling duplicate values. By employing fine-grained, operation-level dependency modeling combined with formal reasoning, the approach enables precise analysis of transaction logs with repeated values. The proposed method achieves both theoretical completeness and practical feasibility, as demonstrated by its prototype implementation, which successfully detects a variety of isolation violations with high precision while maintaining strong performance.

Abstract

Elle is one of the most widely adopted black-box isolation validators. It crucially relies on the unique-value assumption for sound and efficient isolation validation. Yet, transaction workloads with duplicate values are highly relevant in practice: they naturally arise in real database systems, and many isolation bugs manifest only in their presence. In this paper, we extend Elle to handle such workloads by introducing a fine-grained dependency model that enables reasoning about dependencies between individual operations. We establish the soundness and completeness of our approach and implement it in a prototype. We also demonstrate its effectiveness in detecting isolation bugs and its promising performance.

Problem

• isolation validation
• duplicate values
• transaction workloads
• database systems
• Elle

Innovation

• isolation validation
• duplicate values
• fine-grained dependency
• transaction workloads
• black-box verification