Annibale Panichella
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XRP Ledger
DRVN at the ICST 2025 Tool Competition – Self-Driving Car Testing Track
Abstract DRVN is a regression testing tool that aims to diversify the test scenarios (road maps) to execute for testing and validating self-driving cars. DRVN harnesses the power of convolutional neural networks to identify possible failing roads in a set of generated examples before applying a greedy algorithm that selects and prioritizes the most diverse roads during regression testing.
Antony Bartlett
,
Cynthia Liem
,
Annibale Panichella
Preprint
Rocket: A System-Level Fuzz-Testing Framework for the XRPL Consensus Algorithm
Abstract Byzantine fault tolerant algorithms are critical for achieving consistency and reliability in distributed systems, especially in the presence of faults or adversarial behavior. The consensus algorithm used by the XRP Ledger falls into this category.
Wishaal Kanhai
,
Ivar van Loon
,
Yuraj Mangalgi
,
Thijs van der Valk
,
Lucas Witte
,
Annibale Panichella
,
Mitchell Olsthoorn
,
Burcu Ozkan
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