Columbia and Yale Universities’ DeepSea Smart Contract Project Gets Ethereum Foundation Grant
The latest news involving the Ethereum Network and Foundation has been surfacing the Internet as the Foundation has supposedly offered a grant to researchers at Columbia and Yale universities.
The reason being mainly for the combined efforts said researchers inputted in developing a new smart contract programming language within the Ethereum Virtual Machine, reports news outlet Coin Telegraph (https://cointelegraph.com/news/ethereum-foundation-funds-columbia-yale-researchers-work-on-smart-contract-language).
The lucky project has been dubbed, “DeepSEA,” which is headed by Ronghui Gu and a team of Yale researchers, where the former serves as an assistant professor in Columbia’s Computer Science Department. Smart contracts and the several other aspects of blockchain technology isn’t new to Gu, as the assistant professor also serves as the Co-Founder of CertiK, a blockchain-based security entity.
Such offering by the Ethereum Foundation is not the first of its kind, and according to Coin Telegraph, it is the fifth, which revolves around supporting projects that include “Ethereum 2.0 and Layer scaling efforts.”
Layer scaling in its general definition involves understanding what prevents the processing of several transactions, which typically come with different constraints including data transfer time, bandwidth, CPUs, etc.
Further mention on the project was made by Gu, who appears to be grateful for the risks tied to the existing weaknesses in smart contracts. More specifically, he trusts it allowed himself and the team of researchers to keep digging into the matter, resulting in extending DeepSEA’s “protective features”.
As per Gu, “It is crucial that these [smart] contracts perform only as they are precisely intended.”
He also added that the DeepSEA would provide developers with added protection to ensure that their code, “conforms exactly to its specifications, using Formal Verificiation,” a process that uses mathematics to assess accuracy of proposed algorithms when it comes to formal specification/property.