The Algorand Foundation has released an upgrade to its blockchain protocol adding decentralized finance (DeFi) features and smart contracts, the company revealed in a press release on Thursday.
According to the announcement, Algorand 2.0 is the biggest expansion of the network’s capabilities since its launch in June. In order to improve the speed, scalability and finality, it directly adds capabilities such as the Algorand Standard Asset (ASA), Atomic Transfers and Algorand Smart Contracts (ASC) into Layer-1.
The CEO of Algorand, Steve Kokinos, commented:
“Building decentralized financial applications requires the right foundational technology and vision. At Algorand, we’re committed to continuous innovation and the development of technology that solves real-world challenges. With this release, new features and simple developer resources enable new use cases and broader adoption of blockchain overall.”
The upgrade’s ASA function has brought a widespread tokenization feature to the Algorand blockchain, which the team claims can be used to digitize any asset, and store it on-chain.
The Atomic Transfer functionality allows for simultaneous transfers of a number of assets among multiple parties in one transaction, which enables users to perform complex token transfers such as internal account settlements and circular trades.
With this upgrade to the protocol the Algorand blockchain will for the first time support smart contracts. The ASC have a small back-end difference from smart contracts used on blockchains such as Ethereum though, its in-house programming language, called Transaction Execution Approval Language (TEAL), is not Turing-complete.
Algorand’s team argues that even though its TEAL has more limited potential functionality, such as the lack of support for recursive logic, it makes smart contracts safer to write and execute.
Back in April, Algorand released its public testnet to gather feedback on the quality, function, and overall experience of its protocol.
Prior to this, the testnet was only available to several hundred early participants from research, academic and partnership businesses, which helped Algorand to improving the performance, scale and speed of the platform.