arXiv subjects

Diane Gallois-Wong

Publications and source records attributed to Diane Gallois-Wong.

2 recordsLinked to original sources

arXiv2026

Canonical LST: A Protocol-Native Liquid Staking Solution for Tezos

Canonical LST (sTEZ) is an enshrined, protocol-native mechanism designed to mitigate the centralization risks associated with liquid staking intermediaries. Intended to complement direct staking rather than replace it, Canonical LST provides a neutral, public alternative managed directly by the Tezos protocol. It allows any tez holder to participate in aggregated staking without reliance on third-party operators. sTEZ follows an accrual-based design: all slashing events and rewards are reflected in the token's exchange rate to tez, keeping balances fungible while exposing holders to the precise economics of staking. This approach ensures that liquid staking functions as fundamental network infrastructure--with deterministic lifecycle rules, transparent on-chain data, and governance anchored in the amendment process--rather than as a discretionary commercial product. This white paper summarises the motivation for enshrining liquid staking, the core mechanics, exchange-rate model, regulatory touchpoints, risk posture, and forward-looking roadmap for Canonical LST.

cs.DC↗

arXiv2019

Beginner's Luck: A Language for Property-Based Generators

Property-based random testing a la QuickCheck requires building efficient generators for well-distributed random data satisfying complex logical predicates, but writing these generators can be difficult and error prone. We propose a domain-specific language in which generators are conveniently expressed by decorating predicates with lightweight annotations to control both the distribution of generated values and the amount of constraint solving that happens before each variable is instantiated. This language, called Luck, makes generators easier to write, read, and maintain. We give Luck a formal semantics and prove several fundamental properties, including the soundness and completeness of random generation with respect to a standard predicate semantics. We evaluate Luck on common examples from the property-based testing literature and on two significant case studies, showing that it can be used in complex domains with comparable bug-finding effectiveness and a significant reduction in testing code size compared to handwritten generators.

cs.PL↗