Source code auto-suggestion based on structural and semantic features

a source code and semantic feature technology, applied in the field of source code autosuggesting based on structural and semantic features, can solve the problems of mass complexity in today's programming and no efficient way to automatically generate customized source code, and need a way to more efficiently develop complex software programs

Pending Publication Date: 2021-05-27
IBM CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The technical effect of this patented technology is that it allows for automatic generation of software documentation (SDF) documents based on specific characteristics found during the process of developing an application. This helps developers quickly identify issues related to their applications and improve efficiency.

Problems solved by technology

This patent describes a problem when trying to write source codes on computers or other devices. However, current methods have limitations in generating customizable source codes due to their lack of automatic generation capabilities. Therefore, this patent proposes a solution by providing better ways to create customized source codes.

Method used

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  • Source code auto-suggestion based on structural and semantic features
  • Source code auto-suggestion based on structural and semantic features
  • Source code auto-suggestion based on structural and semantic features

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Embodiment Construction

[0029]The invention will now be described with reference to the drawing figures, in which like reference numerals refer to like parts throughout. It is emphasized that, according to common practice, the various features of the drawing are not necessarily to scale. On the contrary, the dimensions of the various features can be arbitrarily expanded or reduced for clarity. Exemplary embodiments are provided below for illustration purposes and do not limit the claims. Moreover, please note that any of the steps can be performed in different sequences or combined or at the same time. In addition, any of structures shown can be modified or combined.

[0030]The present system provides auto-completed code block suggestions based on code and comments being written in a code editor, such as an interactive development environment or other type of source code editor. Code block suggestions are drawn from a large repository of previously written source code. Machine learning and similarity-matching a

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Abstract

A method, system and apparatus for source code auto-suggestion, including receiving and processing source code from a source code repository, extracting one or more features from the source code received from the source code repository, extracting one or more features from the source code within a development environment, comparing the one or more features from the source code received from the source code repository with the one or more features extracted from the source code within the development environment, and providing a segment of source code from the received and processed source code repository according to a similarity to the source code within the development environment.

Description

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Claims

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Application Information

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Owner IBM CORP
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