Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code is created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.

Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.

Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.

Abstract: Systems and methods for making source code annotations available across software code repository commits are disclosed. An example method for creating an incremental blame structure for determining which annotations should be shown begins with receiving a commit including at least one file that has been updated with respect to a parent commit. Then, parent file revisions for the at least one file should be identified. An example method determines the differences between the at least one file and the identified parent file revisions and traces an origin of each line in the file based on the determined differences. An identifier of the line and the line's origin may be added to the incremental blame data structure of the file.

Abstract: Systems and methods for making source code annotations available across software code repository commits are disclosed. An example method for creating an incremental blame structure for determining which annotations should be shown begins with receiving a commit including at least one file that has been updated with respect to a parent commit. Then, parent file revisions for the at least one file should be identified. An example method determines the differences between the at least one file and the identified parent file revisions and traces an origin of each line in the file based on the determined differences. An identifier of the line and the line's origin may be added to the incremental blame data structure of the file.