A vehicular control apparatus is used in an onboard system provided with a plurality of information processors mutually connected via a communication bus, and includes a storage section for storing information, and an arithmetic section for executing a process based on the information stored in the storage section. The information contains first management information relating to a security abnormality as a communication data abnormality owing to security attack from outside the onboard system, and second management information relating to a safety abnormality as a communication data abnormality owing to an abnormality in the onboard system. The first management information contains first limit condition information indicating a first limit condition for executing a security coping with the security abnormality. The second management information contains second limit condition information indicating a second limit condition for executing a safety coping with the safety abnormality. Upon detection of the communication data abnormality in the onboard system, the arithmetic section determines a coping content to the detected communication data abnormality based on the first management information and the second management information.

A method and/or system for automated detection and automated remediation of anomalies in Robotic Process Automation (RPA) environment is disclosed. The method comprises auto discovering resources (RPA components and its dependencies) in an RPA platform. The discovered resources are monitored though observation metrics whose values are obtained by executing pre-defined scripts. The obtained values are validated against threshold values to determine if there are any anomalies, wherein the threshold values may either be static values or dynamic values. If there is a breach of threshold, a remediation plan is automatically executed causing the remediation of anomalies. The system is trained to determine the dynamic threshold values through machine learning models which are developed and trained through metrics data and by determining error patterns from the historic unstructured log data.

Apparatus and method for high-performance page fault handling. For example, one embodiment of an apparatus comprises: one or more accelerator engines to process work descriptors submitted by clients to a plurality of work queues; fault processing hardware logic associated with the one or more accelerator engines, the fault processing hardware logic to implement a specified page fault handling mode for each work queue of the plurality of work queues, the page fault handling modes including a first page fault handling mode and a second page fault handling mode.

A computer-implemented method is provided that includes learning causal relationships between two or more application micro-services, and applying the learned causal relationships to dynamically localize an application fault. First micro-service error log data corresponding to selectively injected errors is collected. A learned causal graph is generated based on the collected first micro-service error log data. Second micro-service error log data corresponding to a detected application and an ancestral matrix is built using the learned causal graph and the second micro-service error log data. The ancestral matrix is leveraged to identify the source of the error, and the micro-service associated with the identified error source is also subject to identification. A computer system and a computer program product are also provided.

Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. An improved approach is provided for identifying log files that have undergone a change in status that would require retrieve of its log data, by including a module directly into the operating system that allows the log collection component to be reactively notified of any changes to pertinent log files.

A processor implementing techniques to supporting fault information delivery is disclosed. In one embodiment, the processor includes a memory controller unit to access an enclave page cache (EPC) and a processor core coupled to the memory controller unit. The processor core to detect a fault associated with accessing the EPC and generate an error code associated with the fault. The error code reflects an EPC-related fault cause. The processor core is further to encode the error code into a data structure associated with the processor core. The data structure is for monitoring a hardware state related to the processor core.

A system receives real-time log messages from an executing process that experiences a runtime error. Information such as a filename and line number for the underlying source code may be embedded in the log messages using compiler macros. When the log messages are received, a developer URL may be generated that links a developer workstation directly to the underlying source code file and line number in a source code repository. A support URL may also be generated with a link to a support center and an embedded search string that retrieves resources that are known to address the process error.

Adaptive read threshold voltage tracking techniques are provided that employ bit error rate estimation based on a non-linear syndrome weight mapping. An exemplary device comprises a controller configured to determine a bit error rate for at least one of a plurality of read threshold voltages in a memory using a non-linear mapping of a syndrome weight to the bit error rate for the at least one of the plurality of read threshold voltages.

A method, a system, and a computer program product for analyzing error messages. A first error log generated as a result of an execution of at least one task of a computing system at a first instance is received. The first error log include a plurality of first error messages. A first association rules model is generated using the first error messages. The first association rules model includes a plurality of association rules defining one or more relationships. A second error log, including a plurality of second error messages, generated as a result of an execution of the task at a second instance is received and a second association rules model is generated using the second error messages. Based on the first and second association rules models, at least one error message pattern associated with execution of the at least one task is determined.

In some examples, a system comprises a network interface; a storage device comprising machine-readable instructions; and a processor coupled to the network interface, the processor to access the storage device, wherein execution of the machine-readable instructions causes the processor to: collect crash event data; categorize the crash event data by an application executing when the crash event occurred; identify a crash event corresponding to the crash event data; create an identifier for the crash event; compare the identifier of the crash event to a list of work items, wherein each work item has an identifier; and update the list of work items based on the comparison.