Abstract: A method and technique for data lifecycle management includes storing in a memory from a monitored system one or more metrics. A fault from the monitored system is identified and a first metric from the one or more metrics as being related to the fault is identified. A lifespan is assigned to the first metric, and the first metric is removed from the memory if the lifespan is over.

Abstract: Examples of techniques for function modification for software application testing are described herein. An aspect includes, based on a function call to a function by an application under test that is being tested using a test case in a testing environment, determining whether modification of the function is enabled. Another aspect includes, based on determining that modification of the function is enabled, running the function in a modified mode.

Abstract: A method is provided. The method of resetting a system, comprising: receiving data from the electronic sub-system; determine if a non-hardware fault is detected; if a non-hardware fault is detected, then performing a software reset of the electronics sub-system; if no non-hardware fault has been detected, then determining if a hardware fault is detected; and if a hardware fault is detected, then performing a hardware reset of the system.

Abstract: Embodiments for preemptive substitution of resources in a disaggregated computing environment. Failure patterns and mitigation actions are analyzed for specific failures of respective resources within the disaggregated computing environment. Responsive to determining a failure threshold has been reached for a first resource of a first type of the respective resources, a mitigation action is performed according to the analyzed failure patterns. A result of the mitigation action is determined and the result is used to improve the failure pattern analyzation.

Abstract: A method and technique for data lifecycle management includes identifying a fault from a monitored system. A time period window is defined associated with the fault based on a time the fault occurred. One or more metrics that are related to the fault that fall within the time period window are identified from the monitored system and stored in a memory. A lifespan is assigned to the one or more metrics based on the fault, and the one or more metrics are removed from the memory when their associated lifespans are over.

Abstract: A storage device includes at least one nonvolatile memory device configured to store self-diagnosis firmware and a storage controller configured to communicate with an external device through a sideband interface. The storage controller is configured to perform self-diagnosis of the storage device using the self-diagnosis firmware according to the control of the external device. The storage controller is configured to transmit a result of the self-diagnosis to the external device through the sideband interface.

Abstract: Aspects include monitoring for occurrences of selected events at a computer system, the monitoring by a processor that is coupled to the computer system. A list of event records for each of the selected events is built by the processor. The building of event records includes generating an event record for each occurrence of an event detected by the monitoring. The lists of event records for the selected events are merged into a merged list of event records that are in chronological order. A machine report for the computer system that includes the merged list of event records is stored.

Abstract: A data processing system includes technology for detecting and tolerating faults. The data processing system comprises an electronic control unit (ECU) with a processing core and a fault-tolerant elliptic curve digital signature algorithm (ECDSA) engine. The fault-tolerant ECDSA engine comprises multiple verification state machines (VSMs). The data processing system also comprises nonvolatile storage in communication with the processing core and ECU software in the nonvolatile storage. The ECU software, when executed, enables the data processing system to operate as a node in a distributed data processing system, including receiving digitally signed messages from other nodes in the distributed data processing system. The ECU further comprises a known-answer built-in self-test unit (KA-BISTU). Also, the ECU software comprises fault-tolerant ECDSA engine (FTEE) management software which, when executed by the processing core, utilizes the KA-BISTU to periodically test the fault-tolerant ECDSA engine for faults.

Abstract: Examples of the present disclosure describe implementing bitmap-based data replication when a primary form of data replication between a source device and a target device cannot be used. According to one example, a temporal identifier may be received from the target device. If the source device determines that the primary replication method is unable to be used to replicate data associated with the temporal identifier, a secondary replication method may be initiated. The secondary replication method may utilize a recovery bitmap identifying data blocks that have changed on the source device since a previous event.

Abstract: Managing storage volumes in a point-in-time copy cascade. The cascade includes a first source volume, a first target volume and a second target volume. The method detects a corruption of the first source volume and, if a first restoration of the first source volume from the first target volume is in progress, creates a third target volume from the second target volume and directs I/O operations for the first source volume to the third target volume. The first source volume is then restored from the third target volume.

Abstract: A method for diagnosing and repairing a first computing device that is not able to be booted due to a malfunction of the first computing device is provided. The method comprises providing a boot tool stored on a removable computer readable storage medium; allowing the first computing device to be booted using the boot tool; providing for communication between the first computing device and a remote help desk computing device over a network; remotely identifying the malfunction of the first computing device; and pushing at least one repair data file from the remote help desk computing device to the first computing device or downloading the at least one repair data file from the Internet using the first computing device, wherein the at least one repair data file is configured for repairing the first computing device so that the first computing device is bootable without use of the boot tool.

Abstract: Techniques are provided for decompression of compressed log data, such as for a real-time viewing of compressed log data. An exemplary method comprises: obtaining a compressed log file comprised of a plurality of compressed log messages, wherein a given compressed log message is comprised of one or more message variables and a message signature corresponding to a message template of the given compressed log message; and presenting a first subset of the compressed log file by translating, in memory, the message signatures of the compressed log messages within the first subset to corresponding message templates using a decompression index that maps a plurality of the message signatures to corresponding message templates. The first subset of the compressed log file may comprise a predefined number of lines surrounding a requested line of the compressed log file. In further variations, at least one additional subset of the compressed log file is precomputed using the disclosed decompression techniques.

Abstract: According to one embodiment, a monitoring device includes a variable selector and an anomaly detector. The variable selector is configured to select context variables which indicate conditions when content variables were obtained based on values of the content variables and values of the context variables included in base data, and values of the content variables and values of the context variables included in target data. The anomaly detector is configured to detect anomalies in the target data using the context variables which were selected by the variable selector.

Abstract: The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Abstract: This disclosure relates generally to a human machine interface (HMI) application, and more particularly to modular testing kits and testing framework for testing the HMI application. In one embodiment, a method for developing a modular testing kit for testing a modular component of the HMI application is disclosed. The method may include generating a plurality of test cases for testing the modular component based on a definition of each of a set of interfaces configured to implement the modular component on a target platform, developing the modular testing kit to execute the plurality of test cases by simulating each of the set of interfaces, and creating a test script for each of the plurality of test cases using the modular testing kit.

Abstract: The invention provides, in one aspect, a server load balancer (SLB) recovery method that replicates a primary SLB's connection data after the primary SLB experiences a failure, as opposed to before it experiences a failure as is currently done in the known hot stand-by recovery method. In some embodiments, this is made possible by (1) employing a replication agent on each target processing unit (e.g., each processing unit on which a server application runs) and (2) transmitting, from the primary SLB, connection data information (i.e., information comprising a session identifier) to the replication agent running on the target processing unit to which the session is mapped, which replication agent will store the data until it is required to transmit the data to a cold stand-by SLB.

Abstract: A wide variety of software support functionality can be improved via error incident fingerprinting with unique static identifiers. Such unique identifiers can originate within an integrated development environment and be propagated to runtime, where they can be harvested from execution context at the time of an error. The fingerprint created from such a unique identifier can then be used for a variety of purposes, including indexing knowledge base records, criticality detection, service innovation, alerting, incident resolution, impacts to the development process, and machine learning.

Abstract: In some examples, a system identifies a potential issue based on comparing measurement data acquired at different hierarchical levels of a computing environment. Within a hierarchical level of the different hierarchical levels, the system determines, based on measurement data acquired for objects in the hierarchical level, whether the potential issue is localized to a subset of the objects.

Abstract: Methods, systems, and apparatus for parallel optimization of continuously running quantum error correction by closed-loop feedback. In one aspect, a method includes continuously and effectively optimizing qubit performance in-situ whilst an error correction operation on the quantum system is running. The method directly monitors the output from error detection and provides this information as feedback to calibrate the quantum gates associated with the quantum system. In some implementations, the physical qubits are spatially partitioned into one or more independent hardware patterns, where the errors attributable to each hardware pattern are non-overlapping. The one or more different sets of hardware patterns are then temporarily interleaved such that all physical qubits and operations are optimized. The method allows for the optimization of each section of a hardware pattern to be performed individually and in parallel, and can result is O(1) scaling.

Abstract: Techniques for handling failures in the execution flow of provisioning operations for a computer infrastructure system are disclosed. The techniques can include determining a service type of a service that generated an error during provisioning. An error handler can be selected based on the service type.