Cognitive design assistant

A computer program product for facilitating generation of a user interface design, the computer program product comprising:

• one or more computer-readable storage media, and program instructions stored on the one or more computer-readable storage media, the program instructions, when executed by one or more computer processors, cause the one or more computer processors to:
• train a machine learning model based on data associated with historic projects, data associated with a project type, data associated with an industry type, data associated with accessibility guidance and standards, and data associated with design best-practices associated with application design;
• detect one or more elements added to a screen design of a user interface of an application by a first designer during the application design, wherein the application design includes a type of the one or more elements of the user interface, positioning of the one or more elements on the user interface, sizing of the one or more elements, and attributes of the one or more elements;
• predict one or more next design elements of the screen design, based on the detected one or more elements added to the screen design and the trained machine learning model;
• control presentation of the one or more next design elements that are visual elements selectable on a design artboard for a design file as a recommendation to the first designer;
• whether the one or more next design elements from the recommendation are selected and added to the design artboard by the first designer;
• and
• update the trained machine learning model, based on the determination that the one or more next design elements are selected and added to the design artboard.

A computer system for facilitating generation of a user interface design, the computer system comprising:

• one or more computer processors;
• one or more computer-readable storage media, and program instructions stored on the one or more computer-readable storage media, the program instructions, when executed by the one or more computer processors, cause the one or more computer processors to:
• train a machine learning model based on data associated with historic projects, data associated with a project type, data associated with an industry type, data associated with accessibility guidance and standards, and data associated with design best-practices associated with application design;
• detect one or more elements added to a screen design of a user interface of an application by a first designer during the application design, wherein the application design includes a type of the one or more elements of the user interface, positioning of the one or more elements on the user interface, sizing of the one or more elements, and attributes of the one or more elements;
• predict one or more next design elements of the screen design, based on the detected one or more elements added to the screen design and the trained machine learning model;
• control presentation of the one or more next design elements that are visual elements selectable on a design artboard for a design file as a recommendation to the first designer;
• whether the one or more next design elements from the recommendation are selected and added to the design artboard by the first designer;
• and
• update the trained machine learning model, based on the determination that the one or more next design elements are selected and added to the design artboard.