Abstract: Systems and methods may be implemented to prevent application crashes by correlating a history of operating system (OS) updates with occurrence of past client application crashes using information that is crowd-sourced from multiple information handling systems so that action/s may be taken to prevent occurrence of future client application crashes on the information handling system/s. Machine learning (e.g., deep learning) may be employed to automatically correlate the history of OS updates with a record of past client application crashes that have occurred on multiple client information handling systems, and then the likely root cause/s for the client application crashes identified based on this correlation. These likely root cause/s may be corrected or otherwise addressed, e.g., by further investigation into the details of the root cause, and/or user or automatic system action to remove or block the root cause.

Abstract: In some examples, a server may receive, from a computing device, an error message generated by an executable file that is being executed by the computing device. The server may create, based at least in part on the error message, a search query and perform a search of one or more resources, such as, for example, knowledgebase(s), coding-related forum(s), and the like. The server may receive search results associated with the search query and rank the search results based on one or more criteria to create ranked results. For example, a particular result of the ranked results may include (1) a link to a page that includes a potential solution to an error that caused the error message to be generated and (2) a rank identifying a relevancy of the potential solution to the error. The server may send the ranked results to the computing device.

Abstract: A system and method is disclosed for providing memory performance states in a computing system. The operating system power management component of the computing system establishes a set of performance states, with each performance state being defined by a number of factors, including the core frequency of memory. The operating system power management component also defines the number of memory performance states that are supported by the computing system and the number of supported memory performance states that are available for use by the computing system. Whether a supported memory performance state is available is dependent upon a measure of the power being consumed by the computing system, the thermal output of the computing system, or both measures.

Abstract: An apparatus and method is provided for scheduling USB transaction processing tasks. A periodic queue head list associated with a USB host controller is configured to be processed once every polling period. The periodic queue head list describes a location of the USB transaction processing tasks scheduled for processing. The entries in a frame list of the USB host controller are linked to identify a corresponding periodic queue head list. A USB transaction processing task processed by the USB host controller is assigned to one of the periodic queue head list. A desired response time for the USB transaction processing task is matched with the polling period of the periodic queue head list.