Abstract: The disclosed computer-implemented method includes accessing data that is to be used as part of a test implementation that has multiple potential outcomes. The method also includes determining that the test implementation is to be carried out using specified testing algorithms that test for at least one of the potential outcomes. The method next includes identifying portions of the accessed data that are to be used in the specified testing algorithms, and compressing the identified portions of the accessed data to remove portions of the accessed data that are unused in the specified testing algorithms. The method also includes executing the test implementation using the specified testing algorithms with the compressed accessed data. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: Embodiments facilitating performance anomaly detection are described. A computer-implemented method comprises: detecting, by a device operatively coupled to one or more processing units, based on monitoring data of a plurality of performance metrics of a monitored device, at least one trend within the monitoring data of the respective performance metrics; removing, by the device, the at least one trend from the monitoring data of the respective performance metrics to generate modified data of the respective performance metrics; and detecting, by the device, a performance anomaly based on the modified data of the respective performance metrics and a behavior clustering model comprising at least one steady state.

Abstract: A method and device for managing a storage system comprising multiple storage devices in a first layer and at least one backup storage device in a second layer. In response to receiving a request for writing target data to the storage system, storing the target data to a first portion of storage devices among the multiple storage devices in the first layer; storing a first parity, determined on the basis of a first algorithm, of data in the first portion of storage devices to a second portion of storage devices among the multiple storage devices in the first layer; and storing a second parity, determined on the basis of a second algorithm, of data in the first portion of storage devices to a first backup storage device of the at least one backup storage device in the second layer.

Abstract: A self-correcting secure computer system is provided. The computer system includes a read-only memory (ROM) device, a random access memory (RAM) device, and at least one processor in communication with the ROM device and the RAM device. The at least one processor is programmed to receive an activation signal; retrieve, from the ROM device, data to execute a first configuration including an encryption suite; execute, on the RAM device, the first configuration including the encryption suite; execute the encryption suite to generate a key; store the key at a first memory location; and delete volatile memory associated with the encryption suite.

Abstract: A memory system and operating method thereof includes a semiconductor memory device, and a memory controller controlling actions of the memory device. The memory controller contains a processor executing instruction and programs stored in the memory controller, a memory characterizer characterizing the memory system, and generating an index decision table, an in-flight assessor assessing read command, and predicting a proposed error recovery action in accordance with the index decision table, and a selective decoder executing the proposed error recovery action.

Abstract: A semiconductor system according to an embodiment includes: a semiconductor system including a normal memory cell array and a redundancy memory cell array for repairing a defective cell among memory cells within the normal memory cell array, and configured to output to an external a fail flag generated according to a number of fail bits within read data output from the redundancy memory cell array; and a host configured to store an address corresponding to the read data into a selected register group from among a plurality of register groups, the selected register group being matched to the fail flag.

Abstract: A method includes reserving memory capacity in a first memory device as patch memory region for backing faulted memory, receiving a memory error indication indicating an uncorrectable error in a faulted segment in a second memory device and, in response to the memory error indication, associating in a remapping table the faulted segment with a patch segment in the patch memory region. The faulted segment is smaller than a memory page size of the second memory device. The method also includes, in response to receiving a memory access request directed to the faulted memory segment, servicing the memory access request from the patch segment by querying the remapping table to determine a patch segment address corresponding to a requested memory address, where the patch segment address identifies the location of the patch segment, and based on the patch segment address, performing the requested memory access at the patch segment.

Abstract: An example operation may include a method comprising one or more of receiving a heartbeat failure notification message when a VNFCI is in standby state, building, at a VNFCI, a next state request message with standby and heartbeat failure parameters, sending the next state request message to an EMS, retrieving, at the EMS, a peer VNFCI state when the next state request message is received, sending a next state response message to the VNFCI with active state when one or more of: a peer VNFCI admin state is not online, and when a peer VNFCI is not reachable when the peer VNFCI admin state is online, sending a next state response message with standby state when the peer operational state is active, and sending the next state response message with standby to the VNFCI when the request of current issues on resources associated with the VNFCI from the VNFM is received and there are critical issues at the EMS.

Abstract: A self-correcting secure computer system is provided. The computer system includes a read-only memory (ROM) device, a random access memory (RAM) device, and at least one processor in communication with the ROM device and the RAM device. The at least one processor is programmed to receive an activation signal; retrieve, from the ROM device, data to execute an operating system; execute, on the RAM device, the operating system based on the data from the ROM device; receive a clear RAM signal; end execution of the operating system on the RAM device; and depower the RAM device such that all data on the RAM device is deleted.

Abstract: Techniques described herein relate to a method for forecasting backup failures. Such techniques may include: obtaining data items associated with backup jobs; writing entries in a time series database, the entries comprising successful backup jobs and failed backup jobs; performing a first analysis to predict future failed backup jobs based on the entries in the time series database to obtain a future backup job failure predictions; performing a second analysis to determine a confidence prediction for each of the future backup job failure predictions; ranking the future backup job failure predictions based on the second analysis; performing a third analysis to determine at least one variable leading to each of the future backup job failure predictions; and sending results of the second analysis and the third analysis to an administrator of a data domain.

Abstract: Provided is a method for correcting untrusted data and avoiding logical device swapping for at least one logical subsystem of at least one computer system. A processor may monitor a primary storage for one or more errors that indicate untrusted data on the primary storage. An error indicating that a data set on the primary storage is an untrusted data set may be identified. In response to the error being identified, a corresponding uncompromised version of the data set may be read from a secondary storage. The corresponding uncompromised version of the data set may be written over the untrusted data set on the primary storage.

Abstract: A failure detection and correction module (FDCM) uses statistical measurement to detect failures in a distributed computing system caused by hardware, software, workflow, deployment, environmental factors, etc. in a component of the computing system, the computing system, or multiple computing systems and produces corrective actions. The FDCM identifies issues from various components, correlates the estimated failures in each level of components and rolls up failures and estimated failures from each level of components to system level estimations of failures, reevaluates the system reliability factors, readjusts the system reliability and system functions from the adjusted reliability factors, and produces intelligent corrective actions to improve both system reliability and the system efficiency. Corrective action includes changing slice storing parameters and rebuild priorities on a dispersed storage system.

Abstract: Technologies for monitoring performance of a machine learning model include receiving, by an unsupervised anomaly detection function, digital time series data for a feature metric; where the feature metric is computed for a feature that is extracted from an online system over a time interval; where the machine learning model is to produce model output that relates to one or more users' use of the online system; using the unsupervised anomaly detection function, detecting anomalies in the digital time series data; labeling a subset of the detected anomalies in response to a deviation of a time-series prediction model from a predicted baseline model exceeding a predicted deviation criterion; creating digital output that identifies the feature as associated with the labeled subset of the detected anomalies; causing, in response to the digital output, a modification of the machine learning model.

Abstract: Stabilizing a container-based application includes determining a health of a container. Based on the container health, a most recent stable version of an image for the container is identified. A container image is considered stable if containers spawned from the image have a relatively high MTTF and relatively low MTTR compared to other versions of same image. The container is then deployed using the most recent stable version of the image for the container.

Abstract: For incident management, parsing, responsive to an incident ticket being opened relative to a first application. The parsing identifying a set of incident data. Identifying, using a dependency graph, a set of applications, wherein each application in the set of applications is dependent on the first application through at least one dependency relationship. Notifying, responsive to the incident ticket, a subset of a set of users of a second application about the incident ticket related to the first application, the second application being a member of the set of applications, the subset of the set of users of the second application performing a type of transaction with the second application wherein the type of transaction is indicated in a dependency relationship between the first application and the second application. Preventing a user in the subset of users from creating a second incident ticket.

Abstract: Disclosed is a system and method for providing program verify adaptation for flash memory. The method includes performing an adjustment iteration, which includes accessing error counts for respective N states of a plurality of memory cells, applying a weighting to the error counts based on a binary data coding for the N states, determining a state Smin of the N states having a minimum error count Emin from the error counts, determining a state Smax of the N states having a maximum error count Emax from the error counts, determining a difference between the Emax and the Emin satisfies an error count threshold, and adjusting, by a predefined value, a respective program verify offset of a lowest state from Smin and Smax, and of each state between Smin and Smax in the N states, wherein the adjusting is a decrement when Smin is less than Smax and an increment otherwise.

Abstract: A packet and inspection system for monitoring the performance of one or more flows on a packet network comprises a processor and memory coupled to each other and to a network bus. The memory stores instructions to be executed by the processor and data to be modified by the execution of the instructions. A processor-controlled arbiter is coupled with the processor and the network bus, and upon reception of a packet on the bus or prior to transmission of a packet on the bus for one of said flows, the arbiter requests execution by the processor of selected instructions stored in the memory by providing the processor with the address of the selected instructions in the memory. The memory provides the processor with data associated with the selected instructions, and the processor modifies the data upon execution of the selected instructions.

Abstract: Aspects of the invention include determining a functional coverage model for a system under test (SUT), the functional coverage model comprising a plurality of attributes, wherein each attribute includes a set of values, determining a set of test cases having n-wise test coverage for the SUT, executing one or more test cases to determine an execution bottleneck value in a first set of values for a first attribute, analyzing the set of test cases to determine a first test case having the execution bottleneck value for the first attribute, the execution bottleneck value having a larger execution metric than a second value, determining that the first set of values for the first attribute in the first test case is moot for the n-wise test coverage for the SUT, and replacing the execution bottleneck value for the first attribute in the first test case with the second value.

Abstract: A processing device, operatively coupled with the memory device, is configured to perform an operation on a page of a plurality of pages of a data unit of the memory device to modify data on the page. The processing device also determines a first operation execution time of the page upon performing the operation on the page of the data unit. The processing device further determines whether the first operation execution time satisfies a condition that is based on a predetermined second operation execution time, the predetermined second operation execution time is indicative of lack of defect in at least one other data unit. Lastly, responsive to determining that the first operation execution time satisfies the condition, the processing device performs a scan operation of at least a subset of the plurality of pages of the data unit to decide whether the data unit has a defect.