Abstract: Various processes for efficiently and effectively determining or predicting whether data stored in a non-volatile storage device is unreadable and/or unrecoverable during a read-retry process. To make the determination, different dynamic read threshold (DRT) entries of a dynamic read threshold (DRT) table are applied, in parallel, across different planes of the non-volatile storage device to determine whether the data is unreadable and/or unrecoverable.

Abstract: Implementations of the present disclosure provide a system includes a memory device for storing memory data. The memory device includes an array of memory cells and a plurality of word lines arranged in a plurality of rows and coupled to the array of memory cells. The system also includes a memory controller, having a processor and a memory, operatively coupled to the array of memory cells. The system further includes a host, having another processor and another memory, operatively coupled to the memory controller. The other processor of the host is configured to perform a first RAID encode operation on memory data to form first parity data. The processor of the memory controller is configured to receive the first parity data and the memory data, and perform a second RAID encode operation on the first parity data and the memory data to form second parity data.

Abstract: The disclosure describes techniques that enable detection of memory leaks of software executing on devices within a computer network. An example network device includes memory and processing circuitry. The processing circuitry monitors a usage of the memory by a software component operating within the network device. The processing circuitry periodically determines a memory growth pattern score for the software component based on the usage of the memory. The processing circuitry also predicts whether the user-level process is experiencing a memory leak based on the memory growth pattern score. The processing circuitry applies confirmation criteria to current memory usage of the software component to confirm that the software component is experiencing the memory leak. When the software component is experiencing the memory leak, the processing circuitry generates an alert.

Abstract: The present disclosure refers to apparatuses and methods for initializing electronic devices. An electronic device according to various embodiments includes a memory, and a processor operatively connected to the memory. The processor is configured to record, in the memory, software binaries received from an external device during a download mode. The processor is further configured to, when the download mode has ended, perform booting in a normal mode using a bootloader based on a determination indicating that a predetermined software binary is present among the software binaries recorded in the memory, and perform booting in a recovery mode using the bootloader based on the determination indicating that the predetermined software binary is absent from among the software binaries recorded in the memory.

Abstract: An error associated with a read operation corresponding to a memory die of a memory sub-system is detected. In response to detecting the error, a first read throughput level of the memory sub-system is identified. A quantity of queues receiving operation requests is decreased, the decreased quantity of queues corresponding to a second read throughput level. A read retry operation associated with the memory die is initiated at the second read throughput level.

Abstract: An autonomous system for detecting primary site failure on a Replication Data Facility (RDF) and automating failover to a destination site includes a replication data facility health monitor on a destination site that monitors a plurality of health indicators of the primary site. Example health indicators include RDF session state of RDF sessions on the replication data facility, and reachability of a set of IP addresses. Example IP addresses include an IP address of a cluster master node on the primary site, IP addresses of all of the cluster nodes on the primary site, and IP addresses of Network Attached Storage (NAS) servers executing on the cluster nodes. The replication data facility health monitor generates a replication configuration and, upon detection of a failure of the replication data facility at the primary site, uses the replication configuration to automate failover of all of the NAS servers to the destination site.

Abstract: The embodiments provide a method for reading and writing and a memory device. The method includes: applying a read command to the memory device, the read command pointing to address information; reading data to be read out from a memory cell corresponding to the address information pointed to by the read command; and storing the address information pointed to by the read command into a preset memory space if an error occurs in the data to be read out, and backing up the address information stored in the preset memory space into a non-volatile memory cell according to a preset rule.

Abstract: Provided is a computer-implemented method for generating a Component Fault and Deficiency Tree of a multi-component system the method including: a. modeling the multi-component system using a Component Fault and Deficiency Tree, b. the Component Fault and Deficiency Tree includes a plurality of component fault and deficiency tree elements associated with the respective components; c. each component fault and deficiency tree element includes at least one inport and at least one outport; d. each component fault and deficiency tree element includes at least two events as internal fault tree logic; e. at least one gate, f. each component fault and deficiency tree element includes at least one mitigation logic; g. at least one Boolean AND-Gate, configured to connect the internal fault tree logic and the at least one mitigation logic; and h. providing the generated Component Fault and Deficiency Tree of the multi-component system as output.

Abstract: Techniques for monitoring based on a memory layout of an application are disclosed. A memory layout may be received, obtained, and/or generated from an application executing on a computer. Based on one or more attributes of a plurality of memory regions of the memory layout a memory layout fingerprint is generated. Additionally, memory region fingerprints are generated based on the one or more attributes for respective memory regions. The memory layout fingerprint and the memory region fingerprints are compared to respective previous memory layout fingerprints and the memory region fingerprints in order to determine whether malicious code and/or application drifting has occurred.

Abstract: Various embodiments described herein provide for copying (e.g., to cache) a portion of defect management data for a block of a memory device, such as a non-volatile memory device of a memory sub-system, based on activity of the memory device. For instance, the portion of defect management data can be copied from a first-type memory device of the memory sub-system to a second-type memory device of the memory sub-system, where the first-type memory device stores defect management data for a working set of blocks of the non-volatile memory device being operated upon by the memory sub-system, where the second-type memory device is used to store defect management data for an active block of the working set of blocks, and where the second-type memory device has a faster access (e.g., read or write access) than the first-type memory device.

Abstract: Techniques for performing cache operations are provided. The techniques include tracking performance events for a plurality of test sets of a cache, detecting a replacement policy change trigger event associated with a test set of the plurality of test sets, and in response to the replacement policy change trigger event, operating non-test sets of the cache according to a replacement policy associated with the test set.

Abstract: A vehicular device includes a control unit, a non-volatile first storage unit, a second storage unit, a notification unit, and a backup unit. Multiple operating systems operate in the control unit. The backup unit is provided in each operating system and is configured to back up, on the first storage unit, data temporarily stored in the second storage unit. The backup unit is configured to back up the data on the first storage unit upon being notified of the change in the power supply state by the notification unit. The backup unit running on one operating system is configured to pass, to the backup unit provided in another operating system, target data or information identifying the target data. When a failure occurred in the one operating system, the backup unit provided in the other operating system backs up the target data or the information identifying the target data.

Abstract: During an execution of a first executable entity, a computer system determines that a target chunk of executable instructions is to be recorded during the execution. Prior to executing the target chunk of executable instructions, the computer system identifies one or more input(s) of the target chunk of executable instructions, and adjusts a page table entry to cause a page fault based on an access by a second executable entity to a first memory page that corresponds to an identified input, and/or an access by the first executable entity to a second memory page that does not correspond to any identified input. Based on detecting an occurrence of a page fault during an execution of the target chunk of executable instructions, the computer system detects that there an interference with an identified input by the second executable entity and/or an incompleteness of the identified inputs.

Abstract: In various embodiments, a technique can be provided to address debug efficiency for failures found on an operational system. The approach can make use of an existing pin on a memory device with added logic to respond to a trigger signal structured different from a signal that is normally sent to the existing pin on the memory device such that the memory device performs a normal or routine function of the memory device in response to the signal. In response to detecting one or more error conditions associated with the memory device, a system that interfaces with the memory device can generate the trigger signal to the memory device. In response to receiving the trigger signal, the memory device can dump an error log of the memory device to a memory component in the memory device. The error log can later be retrieved from the memory component for failure analysis.

Abstract: Systems and methods are disclosed for monitoring features of a computing device of a distributed computing system using a self-monitoring module. The self-monitoring module can include multiple feature-specific monitoring modules and one or more parent nodes for the feature-specific monitoring modules. A feature-specific monitoring module can identify or detect a fault status change, such as a fault condition or fault resolution, for one or more features. Based on the identified fault conditions or fault resolutions, the feature-specific monitoring module can determine an internal status and communicate an updated status to a parent node.

Abstract: Artificial intelligence (AI) model monitoring and ranking includes obtaining metric values indicative of performance of AI model deployments, the metric values including respective metric values measured across metrics, determining violation statuses of the metrics for each of the AI model deployments, the violation statuses indicating, for each AI model deployment, which of the metrics are violated by the AI model deployment as reflected by respective metric values for that AI model deployment, ranking the AI model deployments against each other according to a ranking model and based on the determined violation statuses for each of the AI model deployments, and providing a rank of at least some of the AI model deployments to a user.

Abstract: In an example embodiment, a solution is provided that detects performance degradation of a particular functionality or an overall system problem using machine learning, Mann-Kendall tests, and correlation tests. After a problem has been automatically detected, the first steps of a root cause analysis may be automatically performed, indicating whether, for example non-optimal ABAP coding, a database issue, or hardware or software bottleneck, or some combination thereof. This approach allows a system to rapidly identify a system performance problem and its root cause by combing several data sources. One can see immediately, for example, whether an ABAP code change, an expensive SQL statement, or the combination of both led to an increase in the average response times of a transaction over time.

Abstract: A system is described herein for mitigating slow process instances in a streaming application. The system includes a slow process instance candidate identifier configured to identify, based on a relative watermark latency, a set of slow process instance candidates from among a plurality of process instances that comprise the streaming application. The system further includes a set of filters configured to remove false positives from the set of slow process instance candidates. The filters account for window operations performed by the process instances as well as stabilization time needed for downstream process instances to stabilize after a slow upstream process instance is mitigated by a mitigation implementer, which may also be included in the system.

Abstract: Telematics-based device troubleshooting, self-repair, and optimization are provided. A system, method, and computer readable storage device collect telemetry data associated with the health of networked CPE devices, service provider data, and service and repair data associated with CPE devices, analyze the collected information, and detect and predict issues that can affect the functioning and operation of CPE devices. Analysis of collected data can be based on self-check rules. In some implementations, troubleshooting steps or rules can be executed by a server device or communicated to a CPE device for enabling self-troubleshooting and self-correction of an issue. Self-check and troubleshooting rules can be configured according to insights derived from machine learning techniques applied to collected data (e.g.

Abstract: Described herein is a system and method for determining whether a detected issue in a computing system is a bug introduced by a developer or an intermittent issue. When an issue is detected, information about the issue is received. A determination is then made as to whether the issue is a new issue or whether it has been previously detected. When it is determined that the issue is a new issue, information about the issue is stored in a storage device. A feature vector is generated for the issue and is analyzed to determine a probability that the issue is a bug. When it is determined that the issue is a bug, the occurrence of the issue is reported to a user of the system that can correct the bug. Once the bug is corrected, the correction is provided back to the system and is used to train the system.