Turing Complete

What is Turing Completeness?

Turing Completeness is a fundamental computer science theory that refers to the capability of a system that can execute any computational problem. It is named after Alan Turing, a British Mathematician and logician who contributed to the early development of the computing field.

A system is Turing Complete if it can perform any computation that a Turing Machine can if given enough time and memory. This means that Turn Complete systems can solve any problem that can be defined algorithmically. Turing Completeness is an important aspect in the design and analysis of programming languages and compilers.

What are the Features of a Turing Complete Programming Language?

A Turing Complete system must be able to perform the following computations:

1. Read and Write Operations: Read input from an infinite memory and write output to an infinite memory.
2. Move Storage: Move the storage left or right one cell at a time.
3. Change Symbol: Change the symbol on the memory at the current position.
4. Conditional Jump: Jump to a different location on the memory based on the current symbol.
5. Loop: Repeat a sequence of instructions indefinitely.
6. Subroutines: Call and return from subroutines (functions) to perform complex tasks.
7. Arithmetic Operations: Perform basic arithmetic operations like addition, subtraction, multiplication, and division.
8. Logical Operations: Perform logical operations like AND, OR, and NOT.
9. Comparison: Compare two values and jump to a different location based on the result.
10. Halting: Halt the computation at a specific point, indicating the end of the program.

All of the features above are required of a system or programming language for it to be considered Turing Complete.

What is the Use of Turing Completeness in Blockchain Technology?

Blockchain technology, through smart contracts, relies on Turing Complete programming languages for their capability as a tool for creating any type of application. The following are ways through which it helps:

1. Flexibility: Turing completeness allows smart contracts to implement any algorithmic logic imaginable. This flexibility enables developers to create a wide range of decentralized applications (dApps) on blockchain platforms.
2. Complexity: Smart contracts often require complex logic to execute various functions autonomously, such as managing digital assets, enforcing agreements, or executing conditional transactions.
3. Conditional Logic: Turing completeness enables smart contracts to create conditional statements, loops, and branching logic, which are essential for creating dynamic and responsive applications.
4. Decentralized Autonomous Organizations (DAOs): Turing completeness enables the implementation of DAOs, which are decentralized organizations governed by smart contracts. DAOs require voting mechanisms and other governance structures that can only be realized using Turing Complete programming languages.
5. Interoperability: Turing completeness allows interoperability between different smart contracts and blockchain platforms. Developers can reuse code and interact with multiple smart contracts within a single application. This helps improve user-experience across multiple blockchain ecosystems.

Applications of Turing Complete Systems in Blockchain Technology

Bitcoin, the world’s first successful implementation of blockchain technology, is not a Turing Complete Machine. It was not developed with the intention of creating a system that enables programmability and complex logic but as a means of exchange and a store of value.

Although Bitcoin works well for its use case, other researchers have produced blockchains with Turing Complete features in-built.

These blockchains are all examples of how Turing Complete programming languages are used in the blockchain space to enable complex smart contracts and decentralized applications. Some of them include:

• Ethereum: Ethereum was the first Turing Complete blockchain to launch. It showed the possibility of smart contracts in blockchains. Programming on Ethereum is done majorly using Solidity, a Turing Complete programming language.
• Solana: Solana’s smart contracts are written in a Turing Complete language called Rust, which is also used for building the Solana runtime environment.
• Polkadot: Polkadot’s substrate framework uses a Turing Complete programming language called ink!, which is similar to Rust and allows developers to create complex decentralized applications.

Conclusion

It is important to note that at the theoretical level, Ethereum and other blockchain protocols are Turing Complete but because transactions require gas, it is impossible for any transaction to run till infinity. Even though infinite loops are one of the features of a Turing Complete language, for blockchains, it is exempted by design. An infinite loop on a public network with finite resources that helps secure the protocol is not feasible.

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