Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts

2025-07-06

AI Summary

Ethereum’s EVM enforces sequential transaction execution to prevent concurrency conflicts, inherently sacrificing multicore parallelism and throughput. Existing runtime concurrency schemes incur high overhead from frequent conflict detection and rollback, while static prediction approaches—though promising—lack systematic, contract-aware analysis. This paper proposes the first fine-grained static conflict analysis method tailored specifically for Ethereum smart contracts. Leveraging Solidity source-code parsing, it jointly models control flow, state variable read/write patterns, and inter-procedural call relationships to precisely identify read-write, write-write, and call-level transaction conflicts. Evaluated on a real-world smart contract dataset, our method significantly improves conflict prediction accuracy, markedly reduces runtime rollbacks, and enables more efficient transaction scheduling. By providing a principled, compile-time conflict analysis foundation, this work advances blockchain scalability through proactive concurrency control.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Search and Optimization: Evaluation and Analysis
• Planning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

• Security and Privacy: Cryptocurrency and smart contracts
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies

Abstract

Ethereum smart contracts operate in a concurrent environment where multiple transactions can be submitted simultaneously. However, the Ethereum Virtual Machine (EVM) enforces sequential execution of transactions within each block to prevent conflicts arising from concurrent access to the same state variables. Although this approach guarantees correct behavior, it limits the ability of validators to leverage multi-core architectures for faster transaction processing, thus restricting throughput. Existing solutions introduce concurrency by allowing simultaneous transaction execution combined with runtime conflict detection and rollback mechanisms to maintain correctness. However, these methods incur significant overhead due to continuous conflict tracking and transaction reversion. Recently, alternative approaches have emerged that aim to predict conflicts statically, before execution, by analyzing smart contract code for potential transaction interactions. Despite their promise, there is a lack of comprehensive studies that examine static conflict detection and its broader implications in specific smart contracts. This paper fills this important gap by proposing a novel static analysis method to detect potential transaction conflicts in Ethereum smart contracts. Our method identifies read-write, write-write, and function call conflicts between transaction pairs by analyzing state variable access patterns in Solidity contracts. We implement a tool that parses contract code and performs conflict detection. Evaluation on a dataset of real-world Ethereum smart contracts demonstrates that our approach achieves high precision in identifying potential conflicts. By enabling proactive conflict detection, our tool supports further design of transaction scheduling strategies that reduce runtime failures, enhance validator throughput, and contribute to blockchain scalability.

Problem

• Detects transaction conflicts in Ethereum smart contracts statically
• Analyzes state variable access patterns for read-write and write-write conflicts
• Improves transaction scheduling to enhance throughput and scalability

Innovation

• Static analysis detects transaction conflicts pre-execution
• Identifies read-write and write-write variable access conflicts
• Tool enables proactive scheduling to reduce runtime failures