Boost+: Equitable, Incentive-Compatible Block Building

• URL: http://arxiv.org/abs/2602.04007v1
• Date: Tue, 03 Feb 2026 20:51:29 GMT
• Title: Boost+: Equitable, Incentive-Compatible Block Building
• Abstract summary: We propose $mathrmBoost+$, a system that decouples the process into collecting and ordering transactions.<n>For searchers, truthful reporting is dominant whenever the default algorithm dominates competing builders.<n>We show that even if a searcher can technically integrate with a builder, non-integration combined with truthful bidding still dominates any deviation for conflict-free transactions.
• Score: 11.538702400279696
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Block space on the blockchain is scarce and must be allocated efficiently through block building. However, Ethereum's current block-building ecosystem, MEV-Boost, has become highly centralized due to integration, which distorts competition, reduces blockspace efficiency, and obscures MEV flow transparency. To guarantee equitability and economic efficiency in block building, we propose $\mathrm{Boost+}$, a system that decouples the process into collecting and ordering transactions, and ensures equal access to all collected transactions. The core of $\mathrm{Boost+}$ is the mechanism $\mathit{M}_{\mathrm{Boost+}}$, built around a default algorithm. $\mathit{M}_{\mathrm{Boost+}}$ aligns incentives for both searchers (intermediaries that generate or route transactions) and builders: Truthful bidding is a dominant strategy for all builders. For searchers, truthful reporting is dominant whenever the default algorithm dominates competing builders, and it remains dominant for all conflict-free transactions, even when builders may win. We further show that even if a searcher can technically integrate with a builder, non-integration combined with truthful bidding still dominates any deviation for conflict-free transactions. We also implement a concrete default algorithm informed by empirical analysis of real-world transactions and evaluate its efficacy using historical transaction data.

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