Intelligent contract function similarity sorting method and system, and storage medium

Abstract

The invention discloses an intelligent contract function similarity sorting method and a system, and a storage medium. The method comprises the following steps: obtaining an input intelligent contractfunction; obtaining a first grammar vector according to the intelligent contract function, and obtaining a grammar vector set according to a preset function library; obtaining a first semantic vectoraccording to the intelligent contract function, and obtaining a semantic vector set according to a preset function library; determining a similarity score result between the intelligent contract function and a preset intelligent contract function according to the first grammar vector, the grammar vector set, the first semantic vector and the semantic vector set; and according to the similarity score result, performing sorting processing on the preset intelligent contract function. The similarity analysis accuracy can be improved, the writing efficiency of programmers can be improved, and themethod can be widely applied to the technical field of information processing.

Description

Technical field [0001] The invention relates to the technical field of information processing, in particular to a method, system and storage medium for sorting the similarity of smart contract functions. Background technique [0002] With the development of Internet technology, the application of blockchain has become more and more extensive. There are smart contracts on the blockchain. Smart contracts are programs stored on the blockchain, which can assist and verify the negotiation and operation of the contract. For node operation, the person who runs the program needs to pay a fee to the node's miners or stakeholders. Smart contracts have the characteristics of data transparency, non-tampering, and permanent operation. Therefore, the application of smart contracts has an important impact on the application of blockchain. [0003] In the process of programming smart contract functions, in order to reduce the high threshold of smart contract development and improve the efficiency ...

AI Technical Summary

Problems solved by technology

At present, code recommendations are usually sorted according to the similarity of smart contract functions. However, there are two main problems in the current method of sorting functions by similarity. One is that the efficiency is relatively low, and the other is that only syntax or semantics are often considered. One aspect of the contract, without comprehensive consideration, and only sorting the commonly used languages ​​and frameworks, without discussing the smart contract scenario, but in fact, if only the grammatical structure is considered, even if the grammatical structure of the two contract functions is very similar, There may also be completely different information and applicable scenarios between the two.

Therefore, in fact, the recommendation results are inaccurate and have no practical reference value for programmers. As a result, programmers still need to write by themselves and find out the cause of code bugs by themselves, which is not conducive to improving writing efficiency.

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