Netflix Inc.

Altera Corporation

Prasanna Padmanabhan

Justin Derrick Basilico

Jakob Raymond Jones

Faisal Zakaria Siddiqi

Mohammad Hossein Taghavi

Dong-Bang Tsai

Gaurav Agrawal

Mehmet Yilmaz

Vivek Kaushal

David Gevorkyan

Ajinkya More

Richard Wellington

Gaurav Agrawa

The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces. Various other methods, systems, and computer-readable media are also disclosed.

Page simulation system

A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.

Feature generation for online/offline machine learning

Systems and methods for reconfiguration of a hardened intellectual property (IP) block in an integrated circuit (IC) device are provided. Reconfiguration of the hardened IP block in the IC device may transition between functions supported by the hardened IP block. A transition may occur as a pre-configured profile is selected to reconfigure the hardened IP block. Further, configuration data associated with each of the pre-configured profiles of the hardened IP block may be generated and storage space to store the configuration data may be created. Additionally, reconfiguration control logic to read and implement the configuration data in hard IP design primitives may also be generated.

Selectable reconfiguration for dynamically reconfigurable IP cores

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Fremont, CA, United States of America

Prasanna Padmanabhan