Abstract: Devices, systems, methods, and techniques are disclosed herein for automatic testing with feature tags trained by machine learning for updates in version control systems. An example method includes deploying multiple updates in a code repository of a version control system and mapping the multiple updates using multiple feature labels. The multiple feature labels have been trained in a machine learning model to represent corresponding functional features. A processing device then identifies a subset of codes in the code repository. The subset of codes in the code repository is functionally affected by the multiple updates and is identified based on the multiple feature labels. The processing device performs a verification job on each of the subset of codes in the code repository in preparation for committing the multiple updates in the code repository.

Abstract: The invention provides a gold-supporting catalyst comprising gold nanoparticles and a carrier consisting of porous ceramic obtained by firing a mixture comprising an aluminum compound, a lime component, and a plastic clay containing 1% by mass or less of feldspars and quartz, wherein the gold nanoparticles are supported in an amount of 0.01 to 10 parts by mass on the carrier based on 100 parts by mass of the carrier.

Abstract: The invention provides a gold-supporting catalyst comprising gold nanoparticles and a carrier consisting of porous ceramic obtained by firing a mixture comprising an aluminum compound, a lime component, and a plastic clay containing 1% by mass or less of feldspars and quartz, wherein the gold nanoparticles are supported in an amount of 0.01 to 10 parts by mass on the carrier based on 100 parts by mass of the carrier.