On the 26th of December 2022, DefiLlama tweeted that the Cairo programing language is now the third most prominent smart contract language, with a total locked volume of above $400 million.
— DefiLlama.com (@DefiLlama) December 26, 2022
DefiLlama is an analysis platform where users may examine analytical data from several blockchain networks. It is the largest Total Volume Locked aggregator in the Defi market, collecting data from over 100 decentralized networks and apps.
The DefiLlama platform released a chart showing the distribution of TVL by smart contracts. And as of Dec 2022, the chart showed Solidity as the highest, followed by Vyper and Cairo.
Cairo is a computer language designed for developing proven programs for generic computations. Cairo, like C++, Java, and Rust, enables general-purpose computation like other programming languages. However, it has another unique feature. Cairo may generate proof for the calculation executed as part of its computation.
The University certificates issued to graduates can be used to understand the notion of proof. It is a proof mechanism that allows alumni to prove that they have completed their allotted program. The certificate’s integrity may be checked on the university’s website. As a result, it acts as a proof of claim.
Computational proofs serve a similar purpose as the university degree in Web3. Computation-proof systems aid in generating cryptographic evidence that a third party can validate. A successful programmatic verification of the evidence proves that the presented output actually resulted from a valid computation.
This contributes to the establishment of confidence between the two parties, the prover (the person who conducted the calculation and its computational evidence) and the validator (the one who performs the programmatic validation of the proof).
What are the implications of this?
This implies that smart contracts, along with their proof, may be created on the layer 2 system and confirmed on layer 1 using an EVM. This would show if the Cairo program output was calculated appropriately. This also improves scalability since the running time for producing evidence is roughly linear. However, the cost of verification is poly-logarithmic because the algorithm’s memory increases more slowly than other exponents. As a result, the cost of on-chain computing does not vary much with computation size.
Simply put, calculations occur on layer 2 rather than layer 1, and the full node on layer 1 uses fewer compute resources to validate the proofs created. Thus, there is no re-execution of calculation throughout the verification process. This makes Cairo attractive to developers.