Abstract: Systems and methods for capturing and transforming content from a source application to a destination application are provided. In particular, a computing device may detect a capture request to capture content from a source application, in response to the capture request, capture the content and source context associated with the source application, detect a paste request to paste captured content to a destination application, in response to the paste request, capture destination context associated with the destination application, generate code for transforming the captured content based at least upon the source context and the destination context, execute the generated code to transform the captured content, and provide the transformed content into the destination application.

Abstract: 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.

Abstract: Systems for dynamically synthesizing widgets for chart modification are provided. A method can include receiving data indicating a dataset of structured data. The data can be provided by a user through a user interface (UI). The UI can display the data on a chart. A request can be received by the UI. The request can be provided by the user. The request can indicate an alteration to a representation of the data on the chart. A widget can be dynamically synthesized based on the request. The widget can be operable to alter the representation of the data on the chart based on user interaction with the widget. The UI can present the widget on the UI alongside the chart. The chart can be altered based on user interaction with the widget.

Abstract: 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.