Bybit Learn

Glossary

 Turing-complete is a term used to describe a computing machine capable of solving any problem that a Turing machine could solve given an unlimited amount of time and memory. To understand Turing completeness, you must first understand what a Turing machine is.

First proposed by mathematician Alan Turing in 1936, a Turing machine is a hypothetical computing machine capable of solving any problem. It's important to understand that a physical Turing machine doesn't and can't exist, because its construction would require infinite physical resources.

The late mathematician's hypothetical machine consists of an infinite tape (much like a film reel) divided into squares, a read or write head that can move along the tape and analyze it as it goes, and a regulator capable of knowing what "state" the machine is in. The symbols on the tape represent the input and output data of the computation, while the "state" tells the computer how to adapt.

Now that you have a basic understanding of a Turing machine, you can start to get your head around Turing completeness.

Many programming languages are Turing-complete, including Python, Java, C++ and Ruby. This means any program that can be written using a Turing machine can also be written using these programming languages. In other words, these languages are powerful enough to solve any problem that can be solved using a Turing machine.

Blockchain is a decentralized digital ledger technology that records transactions on a network. Essentially, it's a database maintained by a network of computers, each of which has a copy of the database. Whenever a new transaction is added to the database, all of the computers on the network have to agree to the transaction's validity before it can be added to the database. Once a transaction is added to the blockchain, it can neither be altered nor deleted.

Not all blockchain platforms are Turing-complete, but some are. Remember, a Turing-complete system can compute any calculable function as long as it has ample resources and time. In the context of blockchain technology, Turing completeness means that the programming language used to write smart contracts on the blockchain can solve any computational problem.

The Ethereum blockchain, for example, is Turing-complete; it can execute any arbitrary computation that can be expressed as a smart contract, which makes Ethereum a popular platform for building decentralized applications (DApps).

On the other hand, the Bitcoin blockchain uses a more straightforward scripting language that is not considered to be Turing-complete. This language is designed to support basic transactions and some simple smart contracts, but it has a different level of complexity.

Turing Complete: Explained

Get your daily dose of crypto and trading info