Microsoft Technology Licensing, LLC

Rohan Jagdish Malpani

Peter Groenewegen

Wenbo Wang

Priyan Vaithilingam

A computer system provides a context for a source code document to an artificial intelligence (AI) model and obtains a first suggested edit at a first source code location. At a code editor user interface (UI), the computer system presents a first chat indicator at the first source code location. Based on user interaction with the first chat indicator, the computer system presents the first suggested edit and receives a user response. The computer system provides an updated context to the AI model. The updated context comprises the context and the user response. The computer system obtains a second suggested edit at a second source code location. At the code editor UI, the computer system presents a second chat indicator at the second source code location. Based on user interaction with the second chat indicator, the computer system presents the second suggested edit.

Inline conversation with artificial intelligence within code editor user interface

Some embodiments use specialized machine learning models to generate computing system artifact names which reflect actions, states, conditions, or other aspects of artifact functionality. Artifact creation mechanisms such as method extraction mechanisms, test creation mechanisms, and template extraction mechanisms are enhanced with functionality by which they obtain and suggest meaningful generated names for new artifacts instead of merely prompting users with placeholder names. Specified artifact name formats and name styles are matched during name generation, thereby improving code maintainability and software development efficiency. Generated names are automatically and proactively derived from artifact source code by code summarization, conditional statement location, algorithm category recognition, or name format matching, for example. Generated names are also derived from natural language descriptions in comments and other documentation. Naming gaps left by autocompletion mechanisms are reduced. Inconsistencies between updated artifacts and their names are detected and remedied.

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Everett, WA, United States of America

Rohan Jagdish Malpani