Microsoft Technology Licensing, LLC

Matthew Steven Johnson

Donna Katherine Long

Arthur Charles Leonard

Bryant Daniel Hawthorne

Jeffrey D Robison

Khaled Waleed Al-Sherif

Andrew W Sarratori

Adam D Nathan

Aaron Burns

Christian Michael Sadak

Jean-Pierre Duplessis

Adolfo Hernandez Santisteban

Monty Hammontree

Deon Brewis

Vikram Padmakar Bapat

Andrew Austin Jackson

Steven Clarke

Jamie R Cabaccang

Zachary S Zaiss

Mario Emmanuel Maltezos

Adrian Michael Collier

Benjamin John Sugden

Weston Hutchins

Embodiments relate to enabling a user of data-sharing applications executing on a computing device to indirectly exchange objects between the applications by adding objects from the applications to a journal application that manages a display area. The objects are displayed in the display area. The journal application collects metadata related to the objects and automatically curates lists of the objects according to the metadata. Curation of a list may involve moving objects into a list, merging objects, creating new objects out of content of existing objects, grouping objects according to a commonality thereof, etc. Machine learning services may be invoked to acquire additional metadata about the objects and to make curation decisions.

Polymorphic smart context-aware lists

A method to display a virtual object includes receiving virtual-object data representing a virtual object, a first rendering of the virtual object being displayed on a display screen during a first interval. The method also includes receiving display-screen data indicating a physical size, position, and orientation of the display screen, and receiving display-device data indicating a position and orientation of a near-eye display device. The method includes composing a second, 3D rendering of the virtual object based on the virtual-object data and on the relative position and orientation of the display screen versus the near-eye display device, as indicated by the display-screen and display-device data, and, displaying the second rendering binocularly on the near-eye display device during a subsequent second interval, such that the second rendering coincides with the first rendering in an augmented field of view of the user.

Virtual object hand-off and manipulation

Embodiments are directed to providing an image in response to a request for an image and to requesting an image for a specified context. In one scenario, a computer system stores multiple image representations of a corresponding visual asset identified by an identifier. The image representations include a vectorized representation of the visual asset and/or a rasterized representation of the visual asset. The computer system receives a request that includes an identifier for one of the visual assets and usage parameters. The computer system evaluates at least one of the usage parameters to identify an image representation of the identified visual asset that substantially corresponds with the usage parameters. The computer system then obtains the identified image representation of the corresponding visual asset based on the evaluation and provides the obtained image representation in response to the request.

Dynamic, parameterized image resource selection

Multi-faceted relationship hubs can support browsing an extensible set of relationship types from within a single tool window. A user can switch between relationship types within a single tool window without disrupting user flow by having to change context in a plurality of tool windows. Multiple instances of relationship hubs can be created. Browsing navigation history can be stored, allowing a user to maintain and reacquire relationship contexts. A user can preview the content of one or more files without opening the file.

Multi-faceted relationship hubs

Various technologies and techniques are disclosed for using heuristics to determine source code ownership. A request is received to identify at least one owner of a particular source code unit. Initial ownership totals are calculated for the source code unit based upon a code contribution heuristic. The code contribution heuristic counts lines of code that were added and that were modified in the totals for contributing users. The initial ownership totals of the particular source code unit are adjusted based upon at least one other heuristic. The at least one owner of the particular source code unit is then output to an output device. The at least one owner is determined by selecting a contributing user that has a highest ranking total after adjusting the initial ownership totals. For example, there can be a primary owner and a backup owner selected based on the ranking of the ownership totals.

Heuristics for determining source code ownership

Growing community of inventors

Kirkland, WA, United States of America

Matthew Steven Johnson