View source for Google llc (20240264807). Automatically Generating Machine Learning Models for Software Tools That Operate on Source Code simplified abstract

=Automatically Generating Machine Learning Models for Software Tools That Operate on Source Code=


==Organization Name==

[[:Category:google llc|google llc]]


[[Category:google llc]]

==Inventor(s)==

[[:Category:Marko Ivankovic of Obfelden (CH)|Marko Ivankovic of Obfelden (CH)]][[Category:Marko Ivankovic of Obfelden (CH)]]

[[:Category:Vedrana Jankovic of Mountain View CA (US)|Vedrana Jankovic of Mountain View CA (US)]][[Category:Vedrana Jankovic of Mountain View CA (US)]]

==Automatically Generating Machine Learning Models for Software Tools That Operate on Source Code - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240264807 titled 'Automatically Generating Machine Learning Models for Software Tools That Operate on Source Code

The abstract describes a method for generating code insights using machine learning models based on the type of software development tool requested.

* Receiving a code insight request for target source code.
* Request includes target source code and tool type indicator.
* Obtaining a machine learning model based on the tool type indicator.
* Generating code insight using the machine learning model.
* Code insight includes predicted label or code transformation based on tool type indicator.

Potential Applications:
- Software development tools
- Code labeling and transformation
- Machine learning in software development

Problems Solved:
- Enhancing code development process
- Improving code quality and efficiency
- Providing automated insights for developers

Benefits:
- Faster code development
- More accurate code insights
- Enhanced software quality

Commercial Applications:
Title: Machine Learning Code Insight Generation for Software Development Tools
This technology can be used in various software development tools to provide automated code insights, improving the efficiency and quality of code development processes. Market implications include increased productivity for developers and enhanced software performance.

Questions about Machine Learning Code Insight Generation for Software Development Tools:
1. How does this technology impact the software development process?
This technology streamlines the code development process by providing automated insights based on machine learning models, improving efficiency and code quality.

2. What are the potential benefits of using machine learning for code insights?
Using machine learning for code insights can lead to faster development cycles, more accurate predictions, and overall improved software quality.


==Original Abstract Submitted==

a method includes receiving a code insight request requesting a code insight for target source code. the code insight request includes the target source code and a tool type indicator specifying that the software development tool includes one of a code labeling type of software development tool or a code transformation type of software development tool. the method also includes obtaining a machine learning model based on the tool type indicator and generating the code insight using the machine learning model. the code insight includes one of a predicted label for the target source code when the tool type indicator specifies that the software development tool includes the code labeling type of software development tool, or a predicted code transformation for the target source code when the tool type indicator specifies that the software development tool includes the code transformation type of software building tool.



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