476 results about "Error reporting" patented technology

The invention provides a method and device for generating a test case based on a large model and electronic equipment, and relates to the technical field of artificial intelligence such as natural language processing, large language models and deep learning. According to the specific implementation scheme, when a test case is executed to test a tested code, assertion error reporting information is obtained; generating a first prompt word based on at least one of the test case, the tested code and the assertion error report information; inputting the first cue word into the large model to obtain a first output result of the large model; the first output result comprises repair scheme information, and the large model is used for outputting the repair scheme information matched with the first cue word based on the first cue word; and performing multiple rounds of interactive dialogues with the large model based on the first output result to generate a test case of the tested code. By implementing the embodiment of the invention, the accuracy and the code coverage rate of the test case can be improved, the problem can be quickly positioned, the repair suggestion can be automatically generated, the manual intervention is reduced, and the test efficiency is improved.

The invention discloses a method for processing an uncorrectable error of bus equipment and a server, relates to the technical field of servers, and aims to reduce the reporting frequency of the uncorrectable error by setting a suppression identifier of the uncorrectable error of the bus equipment and a time window of uncorrectable error statistics, and improve the reporting efficiency of the uncorrectable error when the uncorrectable error is triggered for the first time. According to the method, uncorrectable errors are reported, the uncorrectable errors are captured, it is ensured that initial errors are not missed, and when the error count of a time window is larger than a reporting threshold value, reporting is carried out again, error missing processing of error aggravation is avoided, redundant error reporting is reduced, an error reporting storm is inhibited through an inhibiting identifier, and the error reporting efficiency is improved. Therefore, the influence of frequent error triggering on the availability of a server system and normal operation of other services is reduced, the reliability of the server is improved, and the technical problems that frequent error triggering cannot be corrected, other service requirements are covered and the availability of the server system is influenced in the related technology are solved.

The invention discloses an intelligent news content error correction system based on a large model, particularly relates to the technical field of big data, and aims to extract key entity information of figures, positions and institutions in news texts and identify time sequence feature words in position description so as to identify association relationships among entities; historical job change records and latest information are obtained from multiple data sources, reliability scoring is performed through a large model, a multi-modal evidence chain with time sequence attributes is constructed, a prediction model is trained based on historical job data, the change probability of a specific job in a future time period is calculated, and space-time consistency of job information is analyzed. And in combination with the output change probability, identifying errors by comparing a multi-source evidence chain, implementing priority verification on a high-probability change event, generating a hierarchical error report, outputting a correction suggestion, updating an error correction result in real time, implementing two-factor authentication on the correction suggestion, and storing a typical job change mode and a correction scheme by creating a historical case library.

The invention discloses a server and processor error processing method and device, a medium and a program product, and relates to the technical field of servers. The method comprises the following steps: when a correctable error occurs in a processor, displaying a setting interface containing error parameter configuration options, and setting a target fault-tolerant allowable value corresponding to the correctable error for the error parameter configuration options; in an execution environment corresponding to the system management mode, selecting error degree data corresponding to the processor from the multi-device error collection information according to error type identifiers allocated for different errors by an error register; and determining whether to generate an error reporting and clearing instruction according to the processor error degree data and the target fault tolerance allowable value. According to the method and the device, the problem that CPU CE faults cannot be found in time due to the fact that decoupling cannot be carried out when errors are reported in related technologies can be solved, a user can perceive CE error types, fault recognition accuracy and efficiency can be improved, the occurrence probability of CE storm can be reduced, and the reliability of a server can be improved.

An approach is provided for large language model (LLM) map feedback reporting. The approach involves, for example, processing an input specifying a map error / feedback using an LLM to classify a map error type. The approach also comprises determining a map error template based on the map error type that specifies structured data fields for the map error type. The approach further involves using the template to construct prompts for the LLM to generate questions to collect data items for populating the data fields, and providing the prompts to the LLM to generate the questions and collect the data items from the user. The approach further involves using template to generate additional prompts to generate a map error report of the data items in a structured data format, and providing the additional prompts to the LLM to generate the map error report for transmission to a map feedback system.

The invention discloses a dynamic expansion method and system for an S3 standard object storage interface and a medium, and belongs to the technical field of computer storage. The method comprises the following steps: a system initialization stage; in the uploading request stage, the file uploading request is subjected to dual verification, and if verification is passed, the file uploading request is sent to the file processing module; in the request processing stage, the file processing module verifies the received file uploading request again and executes different processing flows according to the type of the file uploading request; in the flow control recording stage, flow control and flow recording are carried out according to the uploaded flow data; and in the exception and security event processing stage, in the file uploading process, if any module has an internal error, an error report is immediately generated, and exception processing is carried out. Through triple verification, the data security is ensured, different processing modes are made according to different request types, and the processing efficiency is improved.

The invention discloses a cross-device memory dynamic complementary utilization method based on CXL protocol interconnection and a computer system. The method comprises the following steps that an ECC module of a memory detects data in the data transmission process; when a data error is detected, the error is positioned by the ECC module, the error counting module corresponding to the position is updated, and an error report is generated; when the counting value of the error counting module reaches a set threshold value, the area corresponding to the position is marked as a failure area; evaluating the states of all memories based on the spatial dimension, the health dimension, the time delay dimension and the load dimension, and selecting a target memory according to an evaluation result of the states of the memories; distributing a new logic address for the failure area based on the error report and a selected target memory; the logic address is transmitted to a target memory through a CXL protocol, and an address mapping table is updated at the same time; and after the mapping is successful, migrating the data of the failure area to the healthy area of the target memory by the system through a CXL protocol.

The invention discloses a cross-platform development board communication fault feedback method and device and a storage medium, and relates to the technical field of communication, after main and sub development boards are initialized, a communication state machine is established, a heartbeat timer is started, heartbeat packets are periodically received and sent, an overtime threshold value is dynamically set in an idle state, and error feedback is triggered if no heartbeat packet is received in an overtime state. The connection state periodically detects communication quality, a reconnection mechanism is triggered if continuous packet loss exceeds a threshold value, an error report is generated and reported when reconnection failure reaches an upper limit, error feedback comprises data packet sending, log recording, alarm triggering and the like, and a reconnection request comprises an identifier, a timestamp and a historical communication index; according to the method, communication interruption caused by misjudgment is reduced, and the communication stability and reliability are improved.

The invention discloses a large model query generation system and method combining graph structure analysis and execution, and the system comprises a graph mode standardization module which converts a description file into a unified structured representation; the large language model module is used for screening out nodes, edges and sub-graph modes required by query statements according to the natural language problem and the structured representation of the user; the graph mode detection module is used for detecting and modifying the screened nodes, edges and sub-graph modes through scripts; the large language model module generates an initial query statement according to a natural language problem of a user and detected and modified nodes, edges and subgraph modes; the query statement detection module is used for detecting the initial query statement through a script and generating an error report; and the large language model module generates a modified query statement. According to the large model query generation system and method combining graph structure analysis and execution, the accuracy of graph mode selection is remarkably improved through the thinking ability of the large language model and the script error detection ability, and therefore the quality of graph database query statement generation is improved.

The invention discloses a fault detection method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The method comprises the steps that enhanced error report register data and machine inspection architecture register data from a server are received, the enhanced error report register data and the machine inspection architecture register data are sent when the server detects that the graphics processing unit has uncorrectable errors and the number of times of correctable errors reaches a preset threshold value; under the condition that the enhanced error report register data and the machine check architecture register data are valid, determining whether the graphics processing unit is in a healthy state according to the machine check architecture register data; if not, the fault type and the fault position of the graphic processing unit are determined according to at least one of the processing core information and the memory information included in the enhanced error report register data, so that specific internal equipment with faults of the graphic processing unit can be accurately positioned.

A preferably cloud-based platform supports improvements in software development by assessing quality of source code files, for example, when files are pushed to a software repository. Various static analysis tools are executed on a source file, and the resulting bug reports, which reflect native features of the tools are assembled in a dataset. The bug dataset is enhanced by adding additional features that are not natively generated by the static analysis tool. An ML classifier is trained to predict a selected bug feature, and the classifier is used to update the bug dataset to include estimated values of the selected feature. In an embodiment, post-processing analysis of bug report datasets applies machine learning methods to predict the “severity” of bug reports, an indication of whether they are likely to be true or false. Further, a report of code quality can be returned based on the severity predictions.

The invention belongs to the technical field of integrated circuit testing, and particularly relates to an FPGA software and hardware cooperation testing platform based on a BFM. The test platform is formed by connecting a BFM with a Testbench, an AXI bus, an off-chip DDR and a DUT. The test process comprises the steps that the Testbench issues parameters through a transaction function interface, the BFM reads an excitation vector from the off-chip DDR / on-chip BRAM through an Avalon main interface, adaptive transmission of a system bus clock domain and a DUT clock domain is completed through double asynchronous FIFO (SNDfifo / RECfifo), and signal level interaction with the DUT is achieved through a pin protocol interface; the state machine dynamically switches long and short simulation modes according to the vector length, and drives the output vector to be written back and stored; the error monitoring unit monitors data flow faults in the whole process and outputs seven types of error reporting codes. The simulation equivalent frequency reaches a 10 megahertz level, and the method is suitable for efficient verification of the digital IC.

The invention provides a two-hop incremental interface consistency verification method and system based on a knowledge graph, and the method comprises the steps: 1, carrying out the language analysis of a modified source file, and extracting an interface entity; 2, mapping the interface entity into a language-independent meta-model, and writing the language-independent meta-model into a knowledge graph; 3, executing a two-hop breadth-first traversal algorithm by taking a modified node in the knowledge graph as a starting point to obtain an affected sub-graph; 4, a hot-pluggable rule set is operated on the affected subgraph for verification, the rule set comprises a parameter number matching rule, a type compatibility rule, a version number increasing rule and a field deletion forbidding rule, and if verification is illegal, an error report is generated, and a blocking instruction is output; and if no violation exists in the verification, merging the affected sub-graphs back to the knowledge graph cache. According to the method and the device, online faults caused by field missing during operation are avoided, and the influence of back-end change on the front end is automatically detected and blocked.

The invention provides a vehicle diagnosis method, a vehicle diagnosis server and a storage medium, and the method comprises the steps: obtaining the vehicle information of a to-be-diagnosed vehicle, the vehicle information comprising a vehicle type and ECU information, and the ECU information comprising each functional part in the to-be-diagnosed vehicle and a data structure of each functional part; a target diagnosis sequence is matched from the diagnosis sequence set according to the functions corresponding to the vehicle types and the functional parts, the diagnosis sequences in the diagnosis sequence set are constructed according to the data structures of the functional parts in the vehicle types, and the diagnosis sequences comprise diagnosis data packets of various functions in the vehicle types; issuing the target diagnosis sequence to the to-be-diagnosed vehicle for diagnosis, and obtaining diagnosis log information; and in combination with a preset diagnosis database and an exception pool, analyzing the diagnosis log information, positioning an exception error reporting point and feeding back a repair method. The diagnosis of the vehicle is realized by means of a diagnosis sequence issued by the server, a framework with a heavy cloud and a light client is provided, and the high expansibility of the diagnosis system is realized.

The invention discloses a travel expense management system based on a smart contract, and relates to the technical field of enterprise travel management, and the system comprises the steps: obtaining a travel application submitted by an employee, and analyzing travel information through a natural language processing framework to generate the smart contract; automatically auditing travel expenses in the smart contract through a rule matching algorithm and an expense calculation engine; the service provider generates an invoice through electronic data exchange and performs expense checking on the invoice, and if the checking is not passed, the employee modifies travel expense information according to an error report and submits the travel expense information again; after invoice checking is passed, a payment gateway interface is called to execute payment operation, and a payment voucher is generated; and comparing the actual expense invoice of the employee in the travel with the payment voucher, and generating a final settlement sheet through secondary expense checking and verification. According to the invention, through combination of the intelligent contract and the dynamic auditing model, automatic auditing, invoice comparison and dynamic adjustment of travel expenses are realized, the management precision and efficiency are improved, and compliance of the expenses is ensured.

The invention discloses a fault prediction method and device and a storage medium, and is applied to the technical field of computers, and the method comprises the steps: collecting ECS information, carrying out the statistics of error correction times completed in a memory particle, tracking an occurrence position, and positioning a potential weak address region where ECC frequently occurs in the particle; analyzing information such as fault types, fault addresses, error reporting time, error reporting memory temperatures, task types, task pressure and occupancy rates by the aid of the information reported by the BMC; through the above information, comprehensive working state information is obtained, the working state information is input into a probabilistic neural network PNN, probability distribution of different fault types occurring in a memory is predicted, the effect of assisting fault prediction and judgment is achieved, and prediction accuracy is improved. In addition, the working state information is input into the PNN, and the predicted probability that the memory bank has an uncorrectable fault can be obtained. Furthermore, the operation and maintenance personnel can set a fault excitation test scheme, and system risks brought by the CXL memory are eliminated.

The invention discloses an error reporting method of a processor platform and electronic equipment, and relates to the technical field of computer hardware, and the error reporting method comprises the steps that a plurality of error identifiers of the processor platform are acquired, and the error identifiers are used for representing information of fault types of the processor platform; the prediction model is constructed according to the historical data and the real-time operation parameters, the prediction model can improve the predictive maintenance capability of the processor platform, and then the fault type generated by the processor platform in a period of time in the future is determined according to the error identifier and the prediction model. The technical problem that a processor platform is difficult to warn potential faults in advance in the prior art can be solved, and the technical effects that the fault which is about to occur on the processor platform can be detected in time, then the fault is processed in time according to the prediction result, and the chance of taking preventive measures before the fault occurs is prevented from being missed easily are achieved.

The invention discloses a low-orbit satellite real-time orbit determination trigger starting method, which belongs to the field of satellite positioning time service and is used for ground data processing, and real-time low-orbit satellite satellite-borne GNSS observation updating conditions are detected, low-orbit satellite satellite-borne GNSS observation and real-time completeness and continuity detection calculation is carried out on GNSS products, so that the real-time low-orbit satellite orbit determination trigger starting is realized. Cyclic standard judgment is carried out among different GNSS systems, orbit determination arc lengths and GNSS products, real-time orbit determination is triggered and started only when observation and product quality reach the standard and orbit determination arc section observation is updated, the real-time orbit determination precision can be guaranteed, repeated calculation when observation is not updated is avoided, and the real-time orbit determination efficiency is improved. In addition, invalid / low-quality orbit determination or frequent error reporting when feeding observation and product quality have problems can be avoided, the calculation efficiency can be saved, and repeated problem tracing during operation and maintenance is avoided.

A fault management system (FMS) receives events indicating an issue with a component in the system and determines, based on an inventory database, the component associated with the events. The FMS creates, based at least in part on the events, an error report that includes: (i) an error type identifying a type of error described in the error report, (ii) a timestamp indicating when the error report was created, and (iii) a universal unique identifier (UUID) to uniquely identify the error report. The FMS determines, based at least in part on the error report, a policy associated with the events and classifies the events, based at least in part on the policy, as either a threshold event or a discrete event. The FMS performs one or more actions to address the events.

The invention relates to the technical field of bioinformatics processing, and relates to a system for a bioinformatics analysis process, which comprises a workflow, a task management module, a resource management module, a data management module and a cloud platform, a workflow file is pre-configured for the workflow; the task management module is used for issuing tasks, checking task running conditions and error reporting strategies of task errors and recording task logs; the resource management module is used for managing a memory, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit) and a running environment of a raw signal analysis task, and establishing a mirror image container for each process in a working process; the data management module is used for storing, circulating and backing up the data; and dynamically adjusting the computing resources of the CPU and the memory according to the demand of the analysis task based on the computing resources of the cloud platform, and processing the pre-configured workflow files in sequence. According to the method, Kubernetes is used as a base, a workflow module, a task management module, a resource management module and a data management module are included, calculation processing is carried out based on a cloud platform, and the functions of rapidly building a signal analysis process, constructing a tool mirror image, improving calculation efficiency, querying a task state, carrying out breakpoint continuous running and the like can be achieved.

The present application discloses a server system and a method for locating a faulty device, a computer system, a program product, and a storage medium. The method includes: in response to detecting a link failure, triggering a system management interrupt; parsing the advanced error reporting register of the faulty device to determine the fault information of the faulty device; determining the device asset information of the faulty device based on the fault information of the faulty device; in response to the device asset information of the faulty device not containing the silkscreen information of the faulty device, determining the physical location of the faulty device based on the fault information of the faulty device and the allocation relationship table. By implementing the server system disclosed in the embodiments of the present application and its method, device, system, computer program product, and readable storage medium for locating a faulty device, the utilization rate of server hardware resources can be greatly improved; the device with PCIe failure in the entire cabinet can be quickly located, the normal operation of the business can be restored in time, and the maintenance pressure of operation and maintenance personnel can be reduced.

According to the OPC detection and early warning method for the layout graph exceeding the process capability problem, when DRC check is completed and an error is reported, the following detection is carried out: a graph at an error reporting position of design rule check is marked and is used as a graph with a large risk class; and performing regular classification on the risk large-class graphs according to the graph features to divide the risk large-class graphs into first-class graphs and second-class graphs. The first-class graphs are high-risk graphs exceeding the process capability, and when the first-class graphs exist, the first-class graphs are fed back to the layout design end. The second type of graphs are potential risk graphs, when the second type of graphs exist, second screening is carried out on the second type of graphs, and the second screening comprises the step of carrying out local OPC correction to obtain the first layout layer. And adopting an OPC AEI model to carry out local OPC to judge whether a defect risk graph exists or not, and feeding back the defect risk graph to a layout design end when the defect risk graph exists. According to the method and the device, the defect problem caused by the problem layout graph exceeding the process capability can be quickly and comprehensively screened, so that the publishing efficiency can be improved.

The invention discloses an intelligent model service-oriented multi-source heterogeneous hybrid code unified standardization method, which aims at processing unified standardization and management of multi-source heterogeneous codes of the same intelligent model service development task, and comprises the following steps of: extracting names and meanings of key variables and methods from each subtask code block and description file; performing unified naming on related variables and methods in combination with a large language model; naming replacement of the code blocks is achieved in combination with a large language model, and the code blocks are integrated according to the description file; and combining the big language model with the integrated code and description file, and outputting the code and description file after unified specification. In order to optimize a code integration result, a traceability optimization strategy based on reinforcement learning is constructed, error report information is integrated to realize code reorganization, and the flexibility of a code development process and the multi-person cooperation efficiency oriented to intelligent model service can be effectively improved.

The invention discloses a fault prediction method and device and related equipment, and relates to the technical field of computers. Multiple pieces of error report data are obtained, wherein each piece of error report data is used for indicating that CE occurs in the storage medium; classifying the multiple pieces of error report data, performing fault prediction on the classified error report data of a first category by using a first machine learning model, and performing fault prediction on the classified error report data of a second category by using a second machine learning model to obtain a corresponding prediction result used for indicating whether UCE occurs in the storage medium, the accuracy of predicting the UCE by the first machine learning model is higher than a first threshold value, and the coverage rate of predicting the UCE by the second machine learning model is higher than a second threshold value. Thus, the machine learning model with the high prediction accuracy and the machine learning model with the high coverage rate are used for conducting fault prediction on different types of error report data, the accuracy rate and the coverage rate of fault prediction can be considered at the same time, and therefore the overall prediction effect for the multiple pieces of error report data can be effectively improved.

An apparatus for facilitating processing scalable centralized error queues in an architecture is disclosed. The apparatus comprises: a processor comprising a system interface hosting an error aggregator, where the processor is configured to: hosting at least one centralized error queue in the error aggregator, the at least one centralized error queue to store an error log for errors detected by components of the processor; receiving an error report message from one of the components of the processor, the error report message corresponding to an error detected by the component; and based on the error type of the error, recording the error as an entry in at least one centralized error queue.

An example operation may include one or more of receiving a report of an error from an installation process of a software program as the installation process is being performed by a computer, executing an artificial intelligence (AI) model to predict at least one instruction to fix the error based on the report of the error, and presenting the at least one instruction via a graphical user interface of the computer associated with the installation process.

The invention provides a data processing method of a distributed database, electronic equipment and a storage medium, and relates to the technical field of electric digital data processing. The method comprises the following steps: acquiring error reporting information; the error reporting information comprises an error reporting type and an error reporting node; determining nodes with the same serial number as voting nodes according to the serial number of the error reporting node so as to determine abnormal nodes and available nodes; when the error report type corresponding to the error report information is that the table structure is inconsistent, determining a voting result according to the table structure information; when the error report type corresponding to the error report information is metadata inconsistency, determining a voting result according to the target reference information; the target reference information comprises one or more of availability, row number and SCN; the voting result comprises abnormal nodes and available nodes; and performing data recovery on the corresponding node data according to the fragment information corresponding to the available nodes in the voting result. The method and the device can adapt to data recovery processing of two types of errors of adaptive metadata and table structures, and the data recovery efficiency is improved.

A system comprises a machine check architecture and a processor. The machine check architecture is configured to log hardware errors. The processor is configured to obtain a log of one or more of the hardware errors from the machine check architecture and / or to generate a copy of the log. The processor is further configured to either (1) deliver the log to an in-band agent and the copy of the log to an out-of-band agent or (2) deliver the copy of the log to the in-band agent and the log to the out-of-band agent. Various other devices, systems, and methods are also disclosed.

The invention particularly relates to a method for synchronizing hudi data based on Data X. The method for synchronizing the hudi data based on the Data X comprises the following steps of: compiling a package.xml file and a plugin.json file, and explaining basic information of a plug-in to a framework; writing a hudiwriter.java script based on a java language to prepare an object or a data stream for writing data, starting a write operation, and refreshing a cache; an auxiliary support type HudiWriterErrorCode.java file is compiled and used for capturing abnormities generated in the data transmission process, and error information is output to a log after being subjected to unified processing; and a framework of the Data X tool reads the file through a corresponding reserved interface, so that data extraction, conversion, loading and abnormal error reporting among the data sources are realized. According to the data X-based hudi data synchronization method, the data synchronization between the hudi and the relational library is realized by performing plug-in secondary development on the Data X tool, and the application range of the Data X tool in the field of big data integration is longitudinally extended.

The embodiment of the invention provides a fault processing method and device, computer equipment and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: receiving function error report data which is uploaded by a client and is generated in the running process of an application program; determining corresponding fault repair data in a preset fault repair database according to the function error reporting data, wherein the fault repair data comprises corresponding burying point data when the application program runs; sending the fault recovery data to the client, and receiving operation result data generated by triggering the burying point data in the process that the client operates the application program based on the fault recovery data; and when the function corresponding to the function error data is matched with the function corresponding to the operation result data, and the corresponding function is determined to be repaired according to the operation result data, generating corresponding fault repair knowledge according to the function error data and the fault repair data, and storing the fault repair knowledge in a preset fault repair database. According to the embodiment of the invention, the processing efficiency of the program fault can be improved.