标题： 以太坊智能合约中检测交易冲突的静态分析 显示英文标题

标题： Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts

摘要： 以太坊智能合约在并发环境中运行，其中可以同时提交多个交易。 然而，以太坊虚拟机（EVM）强制每个区块内的交易顺序执行，以防止由于对同一状态变量的并发访问而产生的冲突。 尽管这种方法保证了正确的行为，但它限制了验证者利用多核架构进行更快交易处理的能力，从而限制了吞吐量。 现有解决方案通过允许同时执行交易，并结合运行时冲突检测和回滚机制来保持正确性，从而引入了并发性。 然而，这些方法由于持续的冲突跟踪和交易回退而产生显著的开销。 最近，出现了另一种方法，旨在通过分析智能合约代码中的潜在交易交互，在执行前静态预测冲突。 尽管它们有潜力，但缺乏全面的研究来考察静态冲突检测及其在特定智能合约中的更广泛影响。 本文通过提出一种新的静态分析方法来检测以太坊智能合约中的潜在交易冲突，填补了这一重要空白。 我们的方法通过分析Solidity合约中的状态变量访问模式，识别交易对之间的读写、写写和函数调用冲突。 我们实现了一个工具，解析合约代码并执行冲突检测。 在真实世界以太坊智能合约数据集上的评估表明，我们的方法在识别潜在冲突方面具有高精度。 通过实现主动冲突检测，我们的工具支持进一步设计减少运行时故障的交易调度策略，提高验证者吞吐量，并有助于区块链可扩展性。 显示英文摘要

摘要： 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.