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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Reactive Governance: A Selective Snapshotting Framework for Secure and Gas-Efficient DAO Voting

Authors: Kaushik, Aryan;

Reactive Governance: A Selective Snapshotting Framework for Secure and Gas-Efficient DAO Voting

Abstract

This work introduces Reactive Governance, a selective snapshotting framework designed to improve the security, scalability, and gas efficiency of on-chain DAO voting systems. Existing governance models impose trade-offs between security and ecosystem-wide efficiency. Reactive Governance resolves this by applying balance snapshots only when necessary, eliminating continuous checkpointing overhead while preserving resistance to flash loan and late-stake attacks. The paper includes: A formal system model Security analysis Empirical gas benchmarking using Foundry A production-ready Solidity reference implementation Key results demonstrate that governance security can be achieved with minimal marginal cost (~17,715 gas) while eliminating transfer overhead entirely. Full implementation, gas reports, and reproducibility artifacts are available in the associated GitHub repository:https://github.com/timburman/Reactive-Governance

Keywords

blockchain, Ethereum, Solidity, Governance systems, gas optimization, DAO governance, smart contracts

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green