Why Does My Transaction Fail? A First Look at Failed Transactions on the Solana Blockchain
Xiaoye Zheng, Zhiyuan Wan, David Lo, Difan Xie, Xiaohu Yang
TL;DR
This work presents the first large-scale empirical study of failed transactions on the Solana blockchain, analyzing 2.9 billion non-vote transactions over a year and distinguishing 1.51 billion failures. It develops a robust error taxonomy (10 types) and links error patterns to specific programs and account initiators, uncovering that bot-driven activity strongly drives failures and that top programs account for most failed attempts. The authors show that failed transactions tend to appear deeper in blocks, incur higher fees, and use fewer compute units, signaling inefficiencies in failed executions and opportunities for targeted tooling and ecosystem-level mitigations. The study offers concrete recommendations for protocol designers, DeFi developers, and users (e.g., dynamic fee structures, bot-mitigation strategies, and automated tooling), aiming to enhance reliability and user experience on Solana and informing cross-chain resilience research.
Abstract
Solana is an emerging blockchain platform, recognized for its high throughput and low transaction costs, positioning it as a preferred infrastructure for Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), and other Web 3.0 applications. In the Solana ecosystem, transaction initiators submit various instructions to interact with a diverse range of Solana smart contracts, among which are decentralized exchanges (DEXs) that utilize automated market makers (AMMs), allowing users to trade cryptocurrencies directly on the blockchain without the need for intermediaries. Despite the high throughput and low transaction costs of Solana, the advantages have exposed Solana to bot spamming for financial exploitation, resulting in the prevalence of failed transactions and network congestion. Prior work on Solana has mainly focused on the evaluation of the performance of the Solana blockchain, particularly scalability and transaction throughput, as well as on the improvement of smart contract security, leaving a gap in understanding the characteristics and implications of failed transactions on Solana. To address this gap, we conducted a large-scale empirical study of failed transactions on Solana, using a curated dataset of over 1.5 billion failed transactions across more than 72 million blocks. Specifically, we first characterized the failed transactions in terms of their initiators, failure-triggering programs, and temporal patterns, and compared their block positions and transaction costs with those of successful transactions. We then categorized the failed transactions by the error messages in their error logs, and investigated how specific programs and transaction initiators are associated with these errors...