Tootfinder

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
https://arxiv.org/abs/2510.07006

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
This study develops and analyzes an optimization model of smart contract adoption under bounded risk, linking structural theory with simulation and real-world validation. We examine how adoption intensity alpha is structurally pinned at a boundary solution, invariant to variance and heterogeneity, while profitability and service outcomes are variance-fragile, eroding under volatility and heavy-tailed demand. A sharp threshold in the fixed cost parameter A3 triggers discontinuous adoption collap…

BugMagnifier: TON Transaction Simulator for Revealing Smart Contract Vulnerabilities
Yury Yanovich, Victoria Kovalevskaya, Maksim Egorov, Elizaveta Smirnova, Matvey Mishuris, Yash Madhwal, Kirill Ziborov, Vladimir Gorgadze, Subodh Sharma
https://arxiv.org/abs/2509.24444

BugMagnifier: TON Transaction Simulator for Revealing Smart Contract Vulnerabilities
The Open Network (TON) blockchain employs an asynchronous execution model that introduces unique security challenges for smart contracts, particularly race conditions arising from unpredictable message processing order. While previous work established vulnerability patterns through static analysis of audit reports, dynamic detection of temporal dependencies through systematic testing remains an open problem. We present BugMagnifier, a transaction simulation framework that systematically reveals…