Abstract: A computer-implemented method for configuring a computing device for predictive maintenance, a computer-implemented method for predictive maintenance as well as a predictive maintenance apparatus are disclosed. Training log files including event sequences are examined iteratively for sequences of increasing length in order to determine a set of configuration data containing event sequences that have high predictive power for a system failure. Forward and backward gap values are defined such that not only sequences in the exact same temporal order as in the training log files are examined but also sequences with slightly different temporal ordering. In this way, possibly imprecise and/or incorrect time stamps in log files are compensated.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for analyzing a log file. The method may include: determining, based on a plurality of reference patterns, corresponding patterns for a plurality of log records in the log file. The method may further include: respectively determining the plurality of log records as a plurality of log identifiers corresponding to the corresponding patterns. The method further includes: determining, from the plurality of log identifiers, a log identifier to be analyzed corresponding to a predetermined event. In addition, the method may further include: selecting a target reference log identifier from a plurality of reference log identifiers corresponding to the plurality of reference patterns, wherein a first similarity between the target reference log identifier and the log identifier to be analyzed is higher than a first threshold similarity.

Abstract: In part, the disclosure relates to a real-time fault tolerant system. The system may include a first computing device, a second computing, and a hardware interconnect. The first computing device may include one or more memory devices, one or more processors, a first network interface operable to receive device data and transmit output data over a time-slot-based bus, wherein the output data is generated from processing device data, and a first real-time checkpoint engine. The second computing device may include similar components or the same components as the first computing device. The hardware interconnect is operable to permit data exchange between the first computing device and the second computing device. Checkpoints may be generated by checkpoint engines during lower-priority communication time slots allocated on the time slot-based bus to avoid interfering with any real-time communications to or from the first and second computing devices.

Abstract: A data verification apparatus embeds a log output code that outputs a log in a referring part that is in a source code and refers to definition data, and generates a test code. The data verification apparatus instructs a test execution apparatus to execute the test code that test data is provided as an input. The data verification apparatus refers to the log outputted by executing the test code. Then, the data verification apparatus determines whether the referring part has been executed when the test data has been provided as the input.

Abstract: A Recovery Maturity Index 1 (RMM) is used to determine whether a particular Information Technology (IT) production environment is relatively mature enough to successfully execute the disaster recovery (DR). The RMI provides a quantitative analysis in terms of a set of categories for elements that characterize the environment and multiple elements for each category. At least some of the elements depend upon the extent to which automation components have been leveraged for disaster recovery. A summation of the scoring elements, which may be a weighted summation, results in an overall quantitative metric. The metric can used to determine whether or not disaster recovery can be expected to be successful.

Abstract: A method for more effectively utilizing computing resources in a data replication environment is disclosed. In one embodiment, such a method detects, at a primary system, activity occurring on the primary system. This activity is recorded in systems logs located at the primary system. The method automatically mirrors the system logs from the primary system to a secondary system that is in a mirroring relationship with the primary system. The system logs are analyzed at the secondary system. In the event abnormal activity is detected in the system logs at the secondary system, the method identifies, on the secondary system, a data set that is associated with the abnormal activity. A snapshot is taken of this data set and saved on the secondary system for later analysis. A corresponding system and computer program product are also disclosed.

Abstract: A method for managing error messages includes obtaining, by a message resolution manager, a plurality of error messages, performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages, generating a plurality of message sequences using the plurality deduplicated error messages, applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, and initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.

Abstract: Correspondence information has a plurality of records in each of which a first warning type and a first malfunction cause type are associated with each other. Malfunction information has a plurality of second malfunction cause types. A weighting unit determines, by using the malfunction information and the correspondence information, a count of second malfunction cause types each corresponding to the first malfunction cause type. The scoring unit gives a score to the first warning type corresponding to the first malfunction cause type according to the determined count, and generates weighting information in which the first warning type and the score are associated with each other. The scoring unit gives the score having been given to the first warning type to a second warning type corresponding to the first warning type of the weighting information, the analysis result information including the plurality of second warning types.

Abstract: A computer-implemented method, according to one embodiment, includes: determining a current operating state of a block of memory. The block includes more than one type of page therein, and at least one read voltage is associated with each of the page types. The current operating state of the block is further used to produce a hybrid calibration scheme for the block which identifies a first subset of the read voltages, and a second subset of the read voltages. The read voltages in the second subset are further organized in one or more groupings. A unique read voltage offset value is calculated for each of the read voltages in the first subset, and a common read voltage offset value is also calculated for each grouping of read voltages in the second subset.

Abstract: A locally optimized plan for executing a command using a sequence of steps can be determined for a single computing node. However, the locally optimized sequence of steps may not be optimized for a combined system comprising multiple computing nodes, any one of which may be tasked with executing the command. A plan that is optimized for the combined system may be determined by comparing the predicted cost of locally optimized plans for computing nodes in the combined system.

Abstract: A system and a method for creating a defect identified during a test case run. A bug is detected during an execution of the test case on a functionality of a software. The bug is detected by comparing an actual output of the functionality with an expected output of the functionality. A setup, indicating actions performed on the software, associated with the bug is identified. Further, a video snippet is generated from a video recording of the test case being executed. The video snippet depicts an execution of the bug caused due to the setup. Furthermore, the setup is analysed using AI and ML techniques to determine an exact location of the bug. Further, a screen, from the video snippet, indicating the exact location of the bug is automatically highlighted. In addition, a defect comprising a recommendation to resolve the bug is created.

Abstract: In an approach to improve the extracting test datasets for testing and resource optimization, embodiments execute a test run on a full dataset of a job, and identify existing bottlenecks in the job through a run-time monitoring interface. Additionally, embodiments execute a run-time metrics analysis, a source code analysis, and a source data impact analysis of a distributed data processing engine executing a distributed data processing job, and generate, by an analysis and impact scoring engine, an impact scoring table of job transformations based on the source code analysis. Furthermore, embodiments generate data extraction rules based on the impact scoring table, and extract a test dataset based on the data extraction rules. Moreover, embodiments evaluate the data extraction rules against user defined thresholds, and prepare a representative test dataset, and output, through a user interface on a computing device, the representative test dataset to a user.

Abstract: A method identifies and prioritizes anomalies in received monitoring logs from an endpoint log source. One or more processors identify anomalies in the monitoring logs by applying a plurality of disparate types of anomaly detection algorithms to the monitoring logs, and then determine a likelihood that the identified anomalies are anomalous based on outputs of the plurality of disparate types of anomaly detection algorithms. The processor(s) then prioritize the monitoring logs based on the likelihood that the identified anomalies are actually anomalous, and send prioritized monitoring logs that exceed a priority level to a security information and event management system (SIEM).

Abstract: A method may include receiving telemetry data associated with one or more information handling resources, receiving failure statistics associated with the one or more information handling resources, merging the telemetry data and the failure statistics to create training data, and implementing a gated recurrent unit to: (i) impute missing values from the training data and (ii) train a pattern recognition engine configured to predict a failure status of an information handling resource from operational data associated with the information handling resource.

Abstract: The invention provides methods, systems and computer program products for image based detection of occurrence of an anomalous event within a process environment. Detection of occurrence of an anomalous event comprises (i) receiving a first set of information from a first image acquisition device, (ii) analyzing the first set of information for determining whether the first image frame images an occurrence of an anomalous event, (iii) receiving a second set of information generated at a second device, wherein the second set of information represents a state of the process environment, (iv) analyzing the second set of information for determining whether an anomalous event has occurred, and (v) generating an anomaly identification decision based at least on output from analysis of the second set of information.

Abstract: A method is provided comprising: generating a snapshot of a volume in a storage system; generating a snapshot marker and adding the snapshot marker to a transaction log of the storage system; scanning the transaction log to identify one or more records that have been added to the transaction log before the snapshot marker, and marking each of the identified records as a splitflush record; flushing any record that is stored in the transaction log by: (a) detecting whether the record is marked as a splitflush record, (b) when the record is marked as a splitflush record, copying the record both to a data store and to the snapshot, and (c) when the record is not marked as a splitflush record, copying the record to the data store only.

Abstract: Techniques to create and use cluster models to predict build failures are provided. In one aspect, clusters in a set of builds may be identified. The identified clusters may be used to create a model. The model may be used to predict causes of build failures. In another aspect, a failed build may be identified. A clustering model may be retrieved. A cause of problems with the failed build may be predicted using the clustering model.

Abstract: Methods and systems described herein are directed to troubleshooting anomalous behavior in a data center. Anomalous behavior in an object of a data center, such as a computational resource, an application, or a virtual machine (“VM”), may be related to the behavior of other objects at different hierarchies of the data center. Methods and systems provide a graphical user interface that enables a user to select a selected metric associated with an object of the data center experiencing a performance problem. Unexpected metrics of an object topology of the data center that correspond to the performance problem are identified. A recommendation for executing remedial measures to correct the performance problem is generated based on the unexpected metrics.

Abstract: A non-limiting example computer-implemented method includes receiving instructions to switch an operational context of a dynamic address translation (DAT) structure to a new operational context. It is determined if context switching has been enabled within the DAT structure. Based on determining that context switching is enabled, it is determined if the new operational context of the DAT structure is different than a current operational context of the DAT structure. It is chosen whether to switch to a full operational context based on the new operational context being different than the current operational context. If the full operational context is used, a full space DAT structure is set up and a private space bit is set to OFF, and if the full operational context is not used, a partial space DAT structure is set up and the private space bit is set to ON.

Abstract: A method for detecting anomalies in a computer network, in which a message transmitted over the computer network is received or recorded by a node of the computer network; based on at least the message, it is checked by a detection mechanism of the node whether the anomalies have occurred, and an occurrence of the anomalies is either confirmed or refuted according to a predefined detection rule of the detection mechanism.

Abstract: A system comprises a memory device comprising a plurality of memory cells; and a processing device coupled to the memory device, the processing device configured to iteratively: calibrate read levels based on associated read results, wherein the read levels are tracked via optimization target data that at least initially includes at least one read level in addition to a target trim; and remove a calibrated read level from the optimization target data when the calibrated read level satisfies a calibration condition.

Abstract: A storage system comprises a controller connected to blocks of non-volatile memory cells. The memory cells can be operated as single level cell (“SLC”) memory cells or multi-level cell (“MLC”) memory cells. To increase write performance for a subset of memory cells being operated as SLC memory cells, the controller performs a deeper erase process and a weaker program process for the subset of memory cells. The weaker program process results in a programmed threshold voltage distribution that is lower than the “nominal” programmed threshold voltage distribution. Having a lower programmed threshold voltage distribution reduces the magnitude of the programming and sensing voltages needed and, therefore, shortens the time required to generate the programming and sensing voltages, and reduces power consumption.

Abstract: A purpose of the present disclosure is to provide a communication system that are capable of maintaining a high security level in each divided network in the case of applying network slicing to a core network. A communication system according to the present disclosure includes a subscriber-information management apparatus (10) configured to manage subscriber information of a communication terminal; and a security apparatus (20) configured to manage identification information of the communication terminal in association with security information used in at least one network slice system usable by the communication terminal. The subscriber-information management apparatus (10) acquires, using the identification information of the communication terminal and identification information of a network slice system used by the communication terminal, security information used in the network slice system used by the communication terminal from the security apparatus (20).

Abstract: A method is provided for categorizing a problem report in a repository of a problem reporting system as an enhancement request or as a defect. Based on the problem report being the defect and having a high severity level, determining a score indicating a probability that a text portion of the problem report includes problem reproduction steps. In response to the score indicating the probability of problem reproduction steps, flagging the problem report to automate. For each problem report to automate, copying the text portion of the problem report to an automated test script, whereby the test script runs in a continuous pipeline.

Abstract: The performance of a cloud-based software product over time is determined by collecting telemetry data representing whether different features of online sessions of the software product are operating properly. The telemetry data represents shared performance metrics of the software product across different participants and components participating in an online session. The collected telemetry data is correlated with session identifiers identifying the online session from which the telemetry data was collected. The telemetry data for an online session is processed to establish a unit of failure when the telemetry data indicates that the online session operated outside of predefined performance metrics. The unit of failure is a function of vetoes applied to a candidate list of online sessions indicating that the online session may have problems. The performance of the software product may be determined as a function of the unit of failure over time.

Abstract: Techniques are provided for compression of log data using field types. An exemplary method comprises: obtaining at least one log message, wherein the at least one log message comprises a message template and at least one message variable, wherein the message template comprises at least one field corresponding to the at least one message variable; obtaining a compression index that maps a plurality of message templates to a corresponding message signature; identifying a predefined field type of the at least one field; selecting a compression technique to apply to the at least one message variable based on the predefined field type to obtain a compressed message variable; and writing the compressed message variable and a message signature corresponding to the message template of the at least one log message to a log file. The at least one log message can be a historical log message or part of a real-time stream of log messages.

Abstract: An improved system and method for detecting network anomalies comprises, in one implementation, a computer device and a network anomaly detector module executed by the computer device arranged to electronically sniff network traffic data in an aggregate level using a windowing approach. The windowing approach is configured to view the network traffic data through a plurality of time windows each of which represents a sequence of a feature including packet per second or flow per second. The network anomaly detector module is configured to execute a wavelet transform for capturing properties of the network traffic data, such as long-range dependence and self-similarity. The wavelet transform is a multiresolution transform, and can be configured to decompose and simplify statistics of the network traffic data into a simplified and fast algorithm.

Abstract: A log analysis device includes a correlation model generation unit that generates a correlation model between a pattern of a log output from a monitored target in a prescribed period and the monitored target, based on time series of the pattern and an operating status of the monitored target, and a determination unit that determines existence of an abnormality in the monitored target based on the correlation model.

Abstract: A computer-implemented method according to one embodiment includes receiving a first plurality of events occurring during a current time period, determining whether a number of the first plurality of events exceeds a threshold for the current time period, determining whether a predetermined issue is identified by comparing the first plurality of events to a second plurality of events occurring during an historical time period, in response to a determination that the number of the first plurality of events exceeds the threshold for the current time period, and resolving the predetermined issue, in response to a determination that the predetermined issue is identified.

Abstract: An analysis system, controller, and data processing device that are capable of avoiding the influence on control in the case where the names of the constituent elements are changed. The analysis system includes a plurality of constituent elements used for analysis; a controller configured to perform control on a basis of data received from the constituent elements; and a data processing device configured to process data received from the controller. The controller receives the control code, the additional code, and the name information from the plurality of constituent elements to generate an ID code on the basis of the control code and the additional code. The data processing device receives the ID code and the name information from the controller, and performs control on the basis of the control code included in the ID code.

Abstract: Techniques disclosed herein manage and resolve incidents in hybridity manager applications, without the back-and-forth manual steps of the traditional software support lifecycle. In one embodiment, a virtual network operations center (NOC) with a centralized view of distributed, cross-cloud hybridity manager installations is responsible for tracking incident reports relating to hybridity managers and associated bugs, and the virtual NOC automatically publishes notifications of upgrade builds that fix the tracked bugs to the appropriate hybridity managers. When the same bug is encountered again with another hybridity manager instance, the virtual NOC may also publish an upgrade notification to the other hybridity manager instance, without requiring a support ticket to be filed, etc.

Abstract: An apparatus for monitoring a computer system includes a data collecting unit that collects performance data on a plurality of performance items related to the performance of the computer system; a performance degradation cause model 30 in which a cause event and degradation performance items which are one or more performance items degraded by the cause event are associated with one another; and an outlier score calculator 50 that specifies a degree of deviation, when target performance data which is performance data of degradation performance items collected by the data collecting unit deviates from a normal range under a condition that the normal range of the performance data of the one or more degradation performance items for the cause event is predetermined, and outputs information on the cause event based on a temporal change in the degree of deviation.

Abstract: System and methods are disclosed for improving manufacturing processes, improving manufactured products, and improving deployed devices. The devices can be reconfigurable holographic antennas (“antennas”). Manufacturing test results for a plurality of antennas is collected. Field performance data and antenna management information is collected for a plurality of deployed antennas. Query selection criteria, machine learning correlation criteria and a minimum correlation threshold are passed to a server to query for matching records from a data store and to perform machine learning on the query results to generate improvements to processes, manufactured antenna performance and deployed antenna performance.

Abstract: This disclosure relates generally to the use of distributed system for computation, and more particularly, relates to a method and system for optimizing computation and communication resource while preserving security in the distributed device for computation. In one embodiment, a system and method of utilizing plurality of constrained edge devices for distributed computation is disclosed. The system enables integration of the edge devices like residential gateways and smart phone into a grid of distributed computation. The edged devices with constrained bandwidth, energy, computation capabilities and combination thereof are optimized dynamically based on condition of communication network. The system further enables scheduling and segregation of data, to be analyzed, between the edge devices. The system may further be configured to preserve privacy associated with the data while sharing the data between the plurality of devices during computation.

Abstract: A storage device having a wide range of operating temperatures is disclosed. Techniques disclosed herein may be used to operate MLC cells at higher temperatures before resorting to thermal throttling. Techniques disclosed herein may be used to operate MLC cells at lower temperatures without needing to pre-heat the storage device. SLC data stored in a first group of memory cells is folded to MLC data stored in a second group of memory cells while an operating temperature is outside a first temperature range. After the operating temperature is within a second temperature range, the data integrity of the MLC data is checked. The SLC data in the first group is folded to MLC data in a third group of memory cells responsive to the MLC data in the second group failing the data integrity check. The foregoing permits the storage device to increase its range in operating temperatures.

Abstract: A method to detect hardware and software errors in an embedded system is disclosed. The method includes: detecting or measuring, by a plurality of sensors, an operating state of the embedded system; operating a plurality of replicated computation engines in group synchrony, wherein the plurality of replicated computation engines are replicated instances of a single computation engine and wherein the plurality of replicated computation engines are grouped into one or more groups such that, for each group, each member of the group starts in a same processing logic state and processes same events in the same order; intercepting output of the plurality of sensors and transmitting the output to each replicated computation engine of a group in a defined order; and actuating selected computation engines of the plurality of replicated computation engines and arbitrating between outputs of the selected computation engines.

Abstract: Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve defining and deploying aggregate, predictive models and corresponding workflows, defining and deploying individualized, predictive models and/or corresponding workflows, and dynamically adjusting the execution of model-workflow pairs.

Abstract: A system analyzes periodically collected data associated with entities, for example, users, servers, or systems. The system determines anomalies associated with populations of entities. The system excludes anomalies from consideration to increase efficiency of execution. The system may rank the anomalies based on relevance scores. The system determines relevance scores based on various factors describing the sets of entities. The system may present information describing the anomalies based on the ranking. The system may use a machine learning based model for predicting likelihoods of outcomes associated with sets of entities. The system generates alerts for reporting the outcomes based on the predictions.

Abstract: This application discloses a service chain fault detection method and an apparatus. The method includes: determining, by a service forwarding entity (SFE), to communicate with a first service function (SF) node on a service chain after obtaining a first fault tracing detection request packet, wherein the first fault tracing detection request packet comprises a path identifier (ID), and the path ID is used to identify a path of the service chain; obtaining, by the SFE, an ID of the first SF node; and sending, by the SFE, a first fault tracing detection response packet to the device for initiating fault detection, wherein the first fault tracing detection response packet comprises the path ID and the ID of the first SF node.

Abstract: Techniques to search logs that contain a massive number of entries are disclosed. In various embodiments, logs are pre-scanned incrementally to identify logs of interest. A log is identified as a log of interest based at least in part on a determination that the log satisfies a symptom definition associated with a symptom. A symptom pre-scan result is generated for those logs of interest that satisfy the symptom definition. The symptom pre-scan result is stored in a searchable pre-scan result data store.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining an integration regression between a source system and a target system. An embodiment operates by selecting a first set of messages in a middleware system. The embodiment receives a baseline mapping for the first set of messages from the middleware system. The embodiment creates a test suite based on the first set of messages. The embodiment performs the test suite, wherein the performing generates a second set of messages in the middleware system and a current mapping for the second set of messages. The embodiment compares the first set of messages to the second set of messages based on the baseline mapping and the current mapping. The embodiment determines an integration regression between the source system and the target system based on the comparing.

Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.

Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace associated with a user-request, wherein an error span is a span that returns an error to a microservice initiating a call resulting in the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

Abstract: A method and device for realizing a snapshot function of a micro-engine processing packet intermediate data, and a computer storage medium. The method comprises: completing a snapshot of packet intermediate data via a debugging instruction to obtain packet snapshot data; completing the storage and outputting of the packet snapshot data according to a software command, so as to move and store the packet snapshot data in an external memory outside the micro-engine; and completing the bus-out of the packet snapshot data in the external memory.

Abstract: A method of circuit yield analysis for evaluating rare failure events includes performing initial sampling to detect failed samples respectively located at one or more failure regions in a multi-dimensional parametric space, generating a distribution of failed samples at discrete values along each dimension, identifying the failed samples, performing a transform to project the failed samples into all dimensions in a transform space, and classifying a type of failure region for each dimension in the parametric space.

Abstract: A client recovery orchestrator for recovering clients after faults includes a persistent storage and a recovery manager. The persistent storage stores a fault correction script. The recovery manager obtains a fault profile associated with a client of the clients, matches the fault profile to a corrective action based on an associative model that associates dimensions of the fault profile and the corrective action, obtains the fault correction script based on the corrective action, orchestrates execution of the fault correction script to obtain an updated client, and updates the associative model based on the updated client.

Abstract: Disclosed are various embodiments for automated vulnerability chaining. A vulnerability chaining engine receives data indicating that a plurality of vulnerabilities are present in at least one host. The vulnerabilities are individually assigned a respective default risk score. The vulnerability chaining engine determines that an exploitation of a combination of the vulnerabilities would result in a greater risk score for the host(s) than indicated by the respective default risk scores based at least in part on respective vulnerability types associated with the individual vulnerabilities. A chained risk score that is higher than the respective default risk scores is assigned to the individual vulnerabilities.

Abstract: Systems, methods, and software are disclosed herein for triaging test results of a failed code validation. Test results are received indicative of a failed code validation performed in a client device. Failure data is generated from the test results indicating one or more failure modes which occurred during the failed code validation. A follow-up action associated with each of the one or more failure modes is then determined by comparing each of the one or more failure modes to previously identified failure modes. Instructions are communicated to the client device based on the determined follow-up action associated with each of the one or more failure modes.

Abstract: There is provided an association analysis method and apparatus. An original database is divided into projection databases, each not contributing to a support count of a frequent item set of another. The projection databases are used for sequential-pattern association analysis performed respectively by nodes corresponding to the projection databases. Local frequent item sets and corresponding support counts obtained by the nodes are combined. Since an established projection database does not contribute a support count of a frequent item set of another projection database, different nodes can perform association mining, including pruning, on different projection databases respectively.

Abstract: A storage device which generates dump data for debugging at the occurrence of an error includes a memory device including a dump area for storing the dump data, and a storage controller that receives a dump request from a host through a first host interface, stores the dump data in the dump area in response to the dump request, and transmits the stored dump data to the host by using a second host interface after resetting the second host interface.