Programming languages to build smart contracts

Development teams use various tools to create high-quality smart contracts that allow users to perform secure and transparent transactions. One of such tools is special programming languages.

The rise in the popularity of decentralization and blockchain in recent years has seen several programming languages coming up. In today's post, OQTACORE will talk about the three most popular smart contract programming languages – Solidity, Vyper, and Rust.

Solidity

Solidity supports blockchains that are compatible with Ethereum (ERC20 and ERC721 standards) and Ethereum Virtual Machine (EVM), such as Binance Smart Chain, Tron, Polygon, xDAI, TomoChain, Cronos and Quorum. The language is based on JavaScript, Python and C++. Therefore, Solidity has similarities with their syntax, as well as good writability and readability.

The functionality of the language is largely similar to that of modern popular languages – it has functions, string operations, classes, variables, arithmetic operations, etc. Furthermore, Solidity supports mapping data structures, which act as hash tables and consist of key types and key value pairs. The programming language is very popular – it has a well-established community, detailed documentation, and many video and text tutorials are available on Stack Overflow.

There are also plenty of tools. OpenZeppelin provides open-source battle-tested libraries for secure smart contract development. So, developers can use existing smart contracts that have proven to be secure; Truffle & Hardhat provides an easy-to-use development and testing environment for app development.

However, there are syntax differences between different versions of Solidity, codes written in earlier versions difficult to be reused.

Vyper

Vyper was designed to fix the vulnerabilities Solidity had at the time of its emergence. Therefore, the languages are quite similar in terms of application. For example, Vyper supports the same blockchains and standards as Solidity. It is based on Python, and both are also similar in terms of syntax and readability.

With respect to functionality, the language allows you to check bounds and overflow for array access as well as arithmetic. Its simple compiler code gives beginners an ideal foundation for learning Vyper.

Popular Vyper tools include Brownie, a Python-based development and testing framework for smart contracts, and Etherscan that provides an online editor for writing your contracts.

Compared to Solidity, there are far fewer projects on Vyper. There are 1,000 Vyper and 740,000 Solidity smart contracts on Github. Vyper continues to be updated, but many of the features available on Solidity are not present in Vyper. For instance, the language has no modifiers, class inheritance or reusability, recursive calls, and dynamic data types. Vyper improves its security by abandoning such features, as they affect the secrecy of smart contracts.

Rust

Rust is a smart contract language for Solana. It supports Solana, Near, and Polkadot blockchains. The syntax is similar to C++, it’s difficult to write and read.

The language creates binaries and restricts code bloat or overly long lines of code. The language compiler also protects against integer overflow, creating a numeric value that is outside of the range that can be represented by a given number. So, Rust data structures are very compact, in many cases even more compact than in C. However, the compilation itself can take a long time – about 10 minutes in some cases.

This language, compared to the previous two, was not originally designed for smart contracts, so it hasn’t many libraries and tools. The most popular ones are published by other developers on GitHub.

Experts at OQTACORE use the latest development tools, from programming languages to frameworks and front-end tools. For a complete technical implementation of your project, please contact us!