Code prompting method and related device

Abstract

The invention discloses a code prompting method. The method comprises the steps of analyzing a code document object written by a user to obtain a corresponding abstract syntax tree; obtaining a code prompt set according to the abstract syntax tree; by taking the code document object and the code prompt set as input of a trained neural network model, predicting the type of a code to be written by auser through the neural network model, screening prompt contents in the code prompt set according to a prediction result, and retaining the prompt contents corresponding to the prediction result; andsending the remaining prompt content in the screened code prompt set to a code editor, so that the code editor prompts the remaining prompt content in the code prompt set when the user newly writes the code. According to the method, code prompting can be carried out in a targeted mode, and the code writing efficiency can be improved. The invention further discloses a code prompting device and equipment and a computer readable storage medium which all have the above technical effects.

Description

Technical field[0001]This application relates to the field of programming technology, in particular to a code prompting method; it also relates to a code prompting device, equipment, and computer-readable storage medium.Background technique[0002]In the Internet age, the development of many industries, especially the IT industry, is closely related to the coding work of programmers. Prompting code during the coding process will undoubtedly help improve the efficiency of code writing. Currently, there are mainly two code prompting schemes as follows. One is that the local device analyzes local text and performs code prompting; the other is to build a language server, which analyzes the text and sends the prompt to the editor for code prompting. However, no matter which method is mentioned above, there is a problem that the prompt content is poorly targeted. For example, when the letter a is input, the editor will prompt all variables, functions, objects, etc. related to the letter a, ...

AI Technical Summary

Problems solved by technology

However, no matter which method is used above, there is a problem that the prompt content is poorly targeted. For example, when the letter a is entered, the editor will prompt all variables, functions, objects, etc. related to the letter a, and various types fixed priority

As a result, programmers cannot find what they need quickly and efficiently, which will greatly affect the efficiency of code writing

Images