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Its syntax is based on Ethereum’s smart contract language Solidity, but its functionality is very different since smart contracts on Bitcoin Cash differ greatly from smart contracts on Ethereum. It offers a strong abstraction layer over Bitcoin Cash’ native virtual machine, Bitcoin Script. The website ’s about section says:Ĭashscript is a high-level programming language for smart contracts on Bitcoin Cash.
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The initial release of Cashscript version 0.4 came with Bitwise operators, Variable size NUM2BIN, a Fluent Transaction interface, Manual UTXO selection, among other improvements. On July 10, Kalis released Cashscript version 0.4.3, “which includes some smaller bytecode optimisations,” according to the developer. A year later, Kalis revealed Cashscript version 0.4 on May 25 and a new website called.
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Our newsdesk spoke with Kalis in May 2019 when he told our readers about the Software Development Kit (SDK) and the syntax of the language which was inspired by Ethereum’s programming language. Moreover, Kalis has also been working on a high-level language for Bitcoin Cash called Cashscript. Kalis is also a software engineer for the General Protocols team and he’s contributing to the Anyhedge project. The tool provides people with the ability to revoke access for the ones they no longer need. For instance, Kalis created revoke.cash, a platform that allows people to inspect certain decentralized app (dapp) contracts that they approved to spend ERC20 tokens in the past. Rosco Kalis is a software developer who is involved with a number of different cryptocurrency projects.
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Cashscript’s new website highlights the high-level language that “offers a strong abstraction layer over Bitcoin Cash’ native virtual machine, Bitcoin Script.” Additionally, the developer Tendo Pein recently announced the “high-level smart contracts programming language for Bitcoin Cash” called Spedn now has a new website. Last May, the software developer and creator of revoke.cash, Rosco Kalis, released Cashscript version 0.4 that included a number of optimizations.