Abstract: A system including a deep learning processor obtains response data of at least two data types from a set of process stations performing operations as part of a manufacturing process. The system analyzes factory operation and control data to generate expected behavioral pattern data. Further, the system uses the response data to generate actual behavior pattern data for the process stations. Based on an analysis of the actual behavior pattern data in relation to the expected behavioral pattern data, the system determines whether anomalous activity has occurred as a result of the manufacturing process. If it is determined that anomalous activity has occurred, the system provides an indication of this anomalous activity.

Abstract: Embodiments of the present disclosure are directed to an efficient and uniform process for generating multiple outputs for different generated test cases for an input request that share a common section in a pseudo-random software system. An enhanced disclosed method comprises processing an input request and a sequence of instructions until a state or condition of interest is reached in a first process. The condition of interest is marked as a split point in the first process. At the split point, a next process for generating multiple outputs is created to include a common section of the first process from the input request to the split point, an added form of randomization, and at least one instruction after the split point. The common section is generated only once in the first process, which can provide significantly enhanced performance.

Abstract: A server device is provided for analyzing communication interfaces. The server device includes a processor including a memory configured to store computer-executable instructions. When executed by the processor, the instructions cause the server device to store a plurality of test scenarios from a plurality of sources; receive a plurality of proposed interfaces from the plurality of sources; for each of the plurality of proposed interfaces, execute the plurality of test scenarios using the corresponding proposed interface of the plurality of proposed interfaces; score the plurality of proposed interfaces based on the execution of the plurality of test scenarios for the corresponding interface; and provide the plurality of scores for the plurality of proposed interfaces to the plurality of sources.

Abstract: Statistical sampling of diagnostic data within an apparatus for processing data 2 is performed based upon sample interval monitoring and address monitoring. A program instruction has its diagnostic data stored when it meets a sample interval criteria and an address match criteria. The address match may correspond to an instruction address of the program instruction or a target address to be read or written by the program instruction.

Abstract: Crash-related information for a secure workspace can be collected. An extended paging table (EPT) handler can be registered in a hypervisor used to deploy a secure workspace on a user computing device. When a secure workspace is about to crash, the EPT handler can be invoked to collect crash-related information about the secure workspace and the hypervisor on which the secure workspace is hosted. After the crash and when the secure workspace is again deployed, a workspace agent running inside the secure workspace can collect additional crash-related information. All of this crash-related information can be communicated to a host agent and relayed to a management service on a management server to allow the crash-related information to be reviewed and analyzed.

Abstract: A system including a deep learning processor obtains response data of at least two data types from a set of process stations performing operations as part of a manufacturing process. The system analyzes factory operation and control data to generate expected behavioral pattern data. Further, the system uses the response data to generate actual behavior pattern data for the process stations. Based on an analysis of the actual behavior pattern data in relation to the expected behavioral pattern data, the system determines whether anomalous activity has occurred as a result of the manufacturing process. If it is determined that anomalous activity has occurred, the system provides an indication of this anomalous activity.

Abstract: Methods are provided for supervising a motor control unit with at least two separate channels, each of the two channels including at least: means for executing a given application task AS, the application task AS including a plurality of successively executed computations between which latency periods elapse; a first component capable of performing the computations; a second component capable of storing data; the application tasks AS of the channels being capable of communicating. The method includes the following steps: a) detecting a latency period; b) performing, during this latency period, an operating state test of at least one of the components; and c) determining a state of the component corresponding to a failure state or a healthy state.

Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

Abstract: The invention relates to system and methods for accessing transaction servers to obtain particular information related to the transaction processing. In particular, the system 10 is adapted to interact with the internal trace 14 of the CICS 12 for reading the trace entries generated by CICS 12 during transaction processing and written to the internal trace 14. The system 10 is adapted to interact with the internal trace 14 in such a manner that the performance of the transaction processing being conducted in the CICS is not negatively impacted. In accordance with an arrangement of the invention, there is provided a method (to be described at a later stage) for reading and interpreting the content of the internal trace in a period of time that is less than the period of time needed for an internal trace to become full and wrap losing the trace entries stored therein.

Abstract: A test automation system is provided that enables “codeless” code test generation and execution. Various embodiments allow users to create automation tests, sets variables in test scripts, set validation criteria, etc. all without having to write code for the operation being tested. In some examples, the system is configured to provide access to mobile device emulation based on selection of or from any number of mobile devices. By automatically defining a suite of tests that can be run on a mobile device population, automated testing can improve validation of any developed software, functionality, and identification of test failures over many existing approaches. Once the codeless tests are created on the system, they can be scheduled to run repeatedly, periodically, a-periodically, all without supervision. Any errors can be communicated to the user, with recommendations to resolve, re-test, among other options.

Abstract: An on-chip debugging device and method is provided. The on-chip debugging device includes: an external interface module configured for outputting chip debugging state information to an external debugger and receiving a control instruction of the external debugger; a debugging mode control module configured for setting a to-be-sampled type of a specified chip internal signal and setting a debugging trigger condition according to the debugging configuration of the external debugger or the internal CPU; a debugging monitor module configured for sampling and recording the internal signal of the chip of the specified type so as to identify the running state of the chip; and a debugging information processing module configured for storing the running state of the chip in an internal debugging memory and sending it to the external debugger by the external interface module or sending it to the internal CPU via an internal bus.

Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

Abstract: An arrangement for handling shared data memory access for a TCF-aware processor. The arrangement comprises at least a flexible latency handling unit (601) comprising local memory (602) and related control logic, said local memory being provided for storing shared data memory access related data.

Abstract: A system including a deep learning processor obtains response data of at least two data types from a set of process stations performing operations as part of a manufacturing process. The system analyzes factory operation and control data to generate expected behavioral pattern data. Further, the system uses the response data to generate actual behavior pattern data for the process stations. Based on an analysis of the actual behavior pattern data in relation to the expected behavioral pattern data, the system determines whether anomalous activity has occurred as a result of the manufacturing process. If it is determined that anomalous activity has occurred, the system provides an indication of this anomalous activity.

Abstract: Target port resets sent from a host server are used to identify HBA faults. A storage array monitors receipt of resets and calculates reset counts for each HBA port of each host server. If there are more than X resets within Y seconds received by a storage array port from a particular HBA port, that HBA port is identified as faulty if the storage array port has not received resets from other HBAs or other ports of the same HBA. If the storage array port has received resets from other ports of the same HBA but not from other HBAs, then the HBA is identified as faulty. If the initiators are grouped, both the HBA port and HBA are identified as potentially faulty. If none of the HBAs or HBA ports are identified as faulty, the cause of the resets is localized to the storage array, inter-switch links, or congestion.

Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

Abstract: A chip having a debug memory interface includes a processing unit, an internal storage unit, a debug memory interface, and a detection unit. The internal storage unit is used to record status data during operation of the processing unit. The detection unit is used to detect whether the debug memory interface is electrically connected to an external memory device. When the debug memory interface is judged to be electrically connected to the external memory device, a control signal is transmitted to the processing unit in order to trigger the processing unit to read a debug program from the external memory device and execute the debug program to run a debug mode based on the status data.

Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

Abstract: A tracking device can use a permanent encryption key pair to encrypt one or more temporary encryption key pairs, which can then be provided to a central tracking system. When a community mobile device subsequently detects the tracking device, the central tracking system provides an encrypted temporary encryption key pair to the community mobile device. The community mobile device uses the encrypted temporary encryption key pair to encrypt location data representative of a location of the community mobile device, and provides the encrypted location data to the central tracking system. When a user subsequently requests a location of the tracking device from the central tracking system, the central tracking system provides the encrypted location data, and a device of the user can decrypt the encrypted temporary encryption key pair using the permanent encryption key pair, and can decrypt the location data using the decrypted temporary encryption key pair.

Abstract: An information handling system may include at least one processor and a memory. The information handling system may be configured to: execute a plurality of microservices, wherein each microservice is configured to generate logging information relating to its operation, and wherein a logging level is configured to determine an amount of logging information generated by the microservice; monitor the execution of the plurality of microservices to determine a failure rate associated with application programming interface (API) calls to the plurality of microservices; and based on the determined failure rate, alter the logging level.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: Systems and methods for monitoring a robotic process automation (RPA) system are provided. Job execution data for one or more jobs in the RPA system is determined based on logs of the RPA system. The job execution data for the one or more jobs in the RPA system is caused to be displayed in substantially real time.

Abstract: A data storage blade includes a plurality of data storage cartridges, with each of the plurality of data storage cartridges comprising at least one data storage medium. The data storage blade also includes shared drive electronics (SDE) external to the plurality of data storage cartridges. The SDE is configured to control data access operations on different data storage cartridges of the plurality of data storage cartridges. The data storage blade further includes a controller-override mechanism activatable to disable communication between the SDE and the plurality of data storage cartridges.

Abstract: A testing device includes: a first update unit that updates a screen transition diagram that is displayed on a display device and shows a transition of a screen state according to input of an operation on a screen relating to a program to be tested; and a second update unit that divides or integrates a node according to an operation of the node for each screen or each screen state in the screen transition diagram. Thus, the testing device makes it possible to obtain the advantage of exploratory testing while reducing a man-hour to perform the exploratory testing.

Abstract: An example method of monitoring computing resources in a cloud computing environment may include receiving a request to subscribe to a monitoring service with respect to computing resources associated with a user account, the request specifying access information for a cloud computing system comprising a plurality of virtual machines associated with the computing resources. The method may further include monitoring, using the access information, the plurality of virtual machines. The method may further include identifying, in view of the monitoring, a virus-infected application running on a virtual machine of the plurality of virtual machines. The method may further include terminating the virus-infected application. The method may further include receiving, in view of the monitoring, resource usage data reflecting types and duration of usage of the computing resources. The method may further include generating, in view of the usage data, a report reflecting usage of the computing resources.

Abstract: Systems and techniques are disclosed for multiplexing database connections with a database proxy, in association with prepared statements. When a client sends initial messages, via a client connection, that set up a prepared statement with a database, the database proxy stores corresponding prepared statement setup data in state data associated with the client connection. When the client sends subsequent messages via the client connection that invoke the prepared statement, the database proxy selects a database connection to use to forward the subsequent messages to the database. The database proxy uses the stored prepared statement setup data to select a database connection that the database already associates with the prepared statement, or to inject prepared statement setup messages that cause the database to set up the prepared statement with the selected database connection.

Abstract: One example method includes acquiring data from a knowledge base that includes message codes indicating conditions that occurred during performance of one or more test runs of a computing operation, and the message codes are included in message code sequences, processing the data by mapping the message codes, and message codes included in a customer issue log, to codes that are readable by a machine learning process, transforming the data to generate an output that comprises, for each message code sequence, relationships between each of the message codes in that message code sequence, extracting features from the transformed data, and the extracting generates multiple datasets that include the features, performing a similarity comparison by comparing a customer field issue with the datasets, and based on the similarity comparison, identifying and recommending a solution to the customer field issue.

Abstract: A processor includes a range register to store information that identifies a reserved range of memory associated with a secure arbitration mode (SEAM) and a core coupled to the range register. The core includes security logic to unlock the range register on a logical processor, of the processor core, that is to initiate the SEAM. The logical processor is to, via execution of the security logic, store, in the reserved range, a SEAM module and a manifest associated with the SEAM module, wherein the SEAM module supports execution of one or more trust domains; initialize a SEAM virtual machine control structure (VMCS) within the reserved range of the memory that is to control state transitions between a virtual machine monitor (VMM) and the SEAM module; and authenticate the SEAM module using a manifest signature of the manifest.

Abstract: A computer-implemented method that includes monitoring execution of program code by first and second processor components. A computing system detects that a trigger condition is satisfied by: i) identifying an operand in a portion of the program code; or ii) determining that a current time of a clock of the computing system indicates a predefined time value. The operand and the predefined time value are used to initiate trace events. When the trigger condition is satisfied the system initiates trace events that generate trace data identifying respective hardware events occurring across the computing system. The system uses the trace data to generate a correlated set of trace data. The correlated trace data indicates a time ordered sequence of the respective hardware events. The system uses the correlated set of trace data to analyze performance of the executing program code.

Abstract: Embodiments of the present disclosure relate to debugging of an accelerator circuit using a packet limit breakpoint. A vector circuit reads a subset of instruction packets from an instruction memory and receives a portion of input data from a data memory corresponding to the subset of instruction packets. The vector circuit executes a set of vector operations in accordance with multiple instruction packets from the subset using data from the received portion of input data identified in the multiple instruction packets to generate output data. A program counter control circuit coupled to the instruction memory triggers a breakpoint in a program stored in the instruction memory causing the accelerator circuit to stop executing remaining instruction packets in the program following the multiple instruction packets responsive to a number of instruction packets executed in the program from a time instant of an event reaching a predetermined number.

Abstract: Systems, apparatuses, and methods related log compression are described. In an example, a system log that identifies targeted data may be compiled in a memory resource during an execution of an operation using that memory resource. The system log may be analyzed utilizing a portion of the memory resource that would otherwise be available to be utilized in the execution of the operation. The system log may be compressed during the execution of the operation, the level or timing of such compression may be based on the analysis that occurs contemporaneous to or as a result of executing the operation. In some examples, compressing the system log may include discarding a portion of the system log. Compressing the system log may also include extracting the targeted data from the system log as the system log is being compiled and converting the extracted targeted data to structured data.

Abstract: Methods of encoding and decoding are described which use a variable number of instruction words to encode instructions from an instruction set, such that different instructions within the instruction set may be encoded using different numbers of instruction words. To encode an instruction, the bits within the instruction are re-ordered and formed into instruction words based upon their variance as determined using empirical or simulation data. The bits in the instruction words are compared to corresponding predicted values and some or all of the instruction words that match the predicted values are omitted from the encoded instruction.

Abstract: A system and method for quantifying impact of script error exceptions on performance of an online retail platform. A method includes selecting at least one performance metric for a webpage, wherein the selected performance metric has an impact due to at least one script error exception encountered on the webpage visited by a first user device; retrieving a normal value for each of the at least one selected performance metric for the webpage visited by a second user device; retrieving an abnormal value for each of the at least one selected performance metric for the webpage visited by the second user device; comparing the abnormal value to the normal value of a respective selected performance metric; and determining a performance impact score based on the comparison, wherein the performance impact score is indicative of a reduction in a performance metric of each of the least one selected performance metric.

Abstract: A method and apparatus for storing autonomous driving test data and an electronic device are provided. The method may include: acquiring a task type of a test task of an autonomous vehicle; receiving message data acquired in a test of the autonomous vehicle and corresponding to the task type, and writing the message data into a data queue; creating a log file corresponding to the task type, writing the message data corresponding to the task type in the data queue into the log file, and transferring the log file and a file name of the log file to the data queue; acquiring preset disk drop scenario information corresponding to the task type; and adding, according to the preset disk drop scenario information, an unclearable mark to the log file in the data queue having data acquisition time consistent with the time of triggering disk drop storage of data.

Abstract: Systems, devices, and methods for linking orders to develop a consolidated audit trail (CAT) are configured to receive event data for one or more orders based on one or more order characteristics; determine linkages between the one or more orders based on parent relationships of the one or more orders; verify the linkages between the one or more orders based on the event data; and determine order lifecycles based on the linkages between the one or more orders.

Abstract: A computer-implemented method for providing explainable diagnostics fora water metering system. The method can include receiving data from a water metering system regarding a potential issue in the water metering system; curating the data with a machine learning model; receiving ground truth data associated with the curated data from a user of the water metering system; comparing the curated data with the ground truth data; and optimizing the machine learning model based on the comparing.

Abstract: The presentation invention relates to methods and apparatus for coordinating the buffering and transmission of data between a Cable Modem Termination System (CMTS) and a wireless base station. An exemplary method in accordance with one embodiment includes the steps of: receiving a buffer management mode message at a CMTS from a wireless base station; switching, by the CMTS, from operating in a first mode of operation to operating in a second mode of operation with respect to buffering and communicating downlink data to the wireless base station; and while operating in the second mode of operation: (i) creating a plurality of CMTS downlink data buffers, each of the plurality of CMTS downlink data buffers corresponding to a different user equipment device to which the wireless base station is actively providing services; and (ii) storing a received downlink data packet in one of the plurality of CMTS downlink data buffers.

Abstract: An information generation apparatus includes a feature information generator that generates feature information on transition to a first screen based on a log including a transition timepoint and identification information, the transition timepoint being a timepoint when a foreground screen transitioned from a second screen to the first screen among a plurality of screens displayed by a plurality of program modules that differ from each other, and the identification information identifying from among the program modules a first program module for displaying the first screen, an index value generator that generates an index value indicative of a degree to which the first screen draws attention from a user based on the feature information, and a determiner that determines based on the index value whether to use the identification information that identifies the first program module in a process of estimating the state of the user.

Abstract: Techniques for managing a disk involve acquiring a message for an access operation for a disk, the message including a first status code at an operating system level for the access operation. The techniques further involve acquiring a second status code at a disk hardware level for the access operation if it is determined that the first status code indicates that the access operation fails. The techniques further involve determining, according to a handling policy corresponding to the second status code, whether the disk will be marked as faulty. The techniques further involve managing the disk based on a count of failed access operations for the disk if it is determined that the disk is not marked as faulty. Such techniques may quickly determine a specific reason for a failure of a disk access operation, making it possible to solve problems quickly, save time and improve the user experience.

Abstract: Methods, systems, and devices for techniques for error correction at a memory device are described. In some examples, as part of transmitting a command to access data stored at a memory device, a host device may transmit a combined error control code to the memory device that may be generated using the command and associated inversion information. The memory device may use the received combined error control code to perform an error control procedure on both the command and the inversion information. In some examples, while in a direct link error control code procedure mode, the host system may transmit a command to access data stored at the memory device. The host system may use a same pin or channel to transmit both an error control code for the command and an error control code for the associated data.

Abstract: A system for tracing transactions includes a system mapping engine configured to generate a multi-tier control point map based on linked transactions across one or more systems having different management software, wherein the linked transactions are identified from transaction records obtained from parsed source code and transaction data of the one or more source systems; and a tracing engine configured to trace the linked transactions across the one or more source systems based on the multi-tier control point map. The multi-tier control point map provides end-to-end transaction traceability via the linked transactions.

Abstract: An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: A method for detecting, identifying, and mitigating advanced persistent threats in a computer network having one or more computers includes a processor in the computer network: receiving a request to access a resource in the computer network; identifying the request as originating from an application executing on the computer network; executing an anomaly operation to determine a behavior of the application is one of anomalous and not anomalous; executing a privilege operation to determine the request is one of permanently allowed and not-permanently allowed; granting access to the resource for both a non-anomalous-behaving application and a permanently allowed request; and generating and displaying, on a graphical user interface of the computer network, and prompt for either an anomalous-behaving application or a not-permanently allowed request.

Abstract: 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.

Abstract: Devices and techniques for fatal error logging in a memory device are described herein. For example, a read request can be received for a component of the memory device. A fatal error indication of an error that prevents correct execution of read request can be detected. Diagnostic information for the failure indication can be collected. A response to the read request can then be made with a portion of the diagnostic information as payload instead of the user data that would have occupied the payload had the read succeeded. Metadata in the response can be used to communicate an error code.

Abstract: Diffing a subject replayable trace against a comparison replayable trace includes identifying a first plurality of functions within a first sequence of instructions recorded in the subject trace, and identifying a second plurality of functions a second sequence of instructions recorded in the comparison trace. A first plurality of groups of the first plurality of functions, and a second plurality of groups of the second plurality of functions are identified. The first and second pluralities of groups are compared, including determining, based on an identity of each group, and on function(s) corresponding to the group, if each first group in the first plurality of groups is at least one of: equal to a second group in the second plurality of groups, a replacement of a second group in the second plurality of groups, deleted from the second plurality of groups, or inserted into the second plurality of groups.

Abstract: Disclosed techniques relate to automatically instrumenting a web application. In an aspect, a method identifies that a web application includes an event that is triggered by a user interaction. The method associates the event with a tracer that is configured to log tracing information based on an execution of a first set of operations caused by the event and to obtain a first measurement of performance of a first span. The method identifies, in the code, that the execution of a first set of operations causes a request to be made to a server. The method associates the request with the tracer. The tracer is configured to log tracing information based on an execution of a second set of operations caused by the request and to obtain a second measurement of performance of a second span that is a child span of the first span.

Abstract: A processor includes a range register to store information that identifies a reserved range of memory associated with a secure arbitration mode (SEAM) and a core coupled to the range register. The core includes security logic to unlock the range register on a logical processor, of the processor core, that is to initiate the SEAM. The logical processor is to, via execution of the security logic, store, in the reserved range, a SEAM module and a manifest associated with the SEAM module, wherein the SEAM module supports execution of one or more trust domains; initialize a SEAM virtual machine control structure (VMCS) within the reserved range of the memory that is to control state transitions between a virtual machine monitor (VMM) and the SEAM module; and authenticate the SEAM module using a manifest signature of the manifest.

Abstract: An electronic communication device includes a controller which controls, according to the number of bit data in which an error has occurred of packet data transferred in serial communication, whether to start logging of information about the error of the packet data or stop logging of information about the error of the packet data.