35 results about "Validation testing" patented technology

A computer-implemented method includes customizing artifacts of a large language model (LLM). A generative artificial intelligence (AI) (genAI) function of a software application that interfaces with the LLM and is instrumented for customer-side management is activated, as a genAI application. A verification test is activated to determine whether interactions between the LLM and genAI application generate expected results. Based on a result of the verification test, either adjusting the artifacts of the LLM or updating the genAI function of the software application. A new verification test is defined to determine whether interactions between the LLM and genAI application generate expected results. The new verification test is activated.

Systems and methods for bias testing and remediation are disclosed. Decentralized Web Application Testing Systems use a Holochain framework to distribute testing workloads across Full Nodes and Lightning Nodes. A Holochain Node Management Application for configuring nodes, a UI Application creates test cases, and a Version Management System tracks changes. Test results are stored and analyzed in a Test Result Store, with a Bias Intelligence module detecting biases and generating additional test cases. A Consensus Algorithm validates test cases through decentralized nomination. An AI-Driven Defect Remediation System automates defect detection, root cause analysis, and remediation using AI modules. Machine learning algorithms identify patterns and anomalies, while NLP techniques generate code fixes. Predictive maintenance monitors application performance to preemptively address issues. A feedback loop mechanism continuously improves AI models through reinforcement learning. Together, these systems provide a holistic approach to web application testing and maintenance.

The invention discloses a chip parameter verification method and device, equipment and a storage medium. The chip parameter verification method comprises the steps of sampling a to-be-tested parameter space of a chip to obtain a parameter point file; performing a regression test on the parameter point file to obtain verification test results, and associating each verification test result with the corresponding parameter point to obtain a data pair set; performing parameter point iteration prediction on the set through a model according to the data; and when it is determined that the predicted parameter points meet the optimization target, taking the predicted parameter points as to-be-applied target parameter points of the chip. The parameter point file is obtained by sampling from the to-be-tested parameter space, and the sampling result is used for the regression verification test, so that the number of tasks needing to be executed is reduced, the overall verification investment is reduced, fitting and prediction are carried out through the model according to the verification test result, the coupling effect and hidden defects among parameters are conveniently found, and the verification efficiency is improved. And the accuracy of the determined target parameter is improved.

A diversified validation test suite application (DVTSA) for a generative AI powered tool or large language model (LLM) tool includes at least first, second, and third control logics. The first control logic receives a seed test input or user input, analyzes the seed test input or user input, and extracts key elements for variations. The second control logic performs a coverage measurement of outputs of the first control logic. The third control logic causes a human validator to evaluate outputs of the second control logic relative to predefined coverage metrics and selectively and continuously iterate to cause outputs of the second control logic to increase LLM tool input robustness and output robustness from a first level to a second level greater than the first level, in both production and pre-production LLM tool processes.

This disclosure describes systems, methods, and devices related to enhanced validation of video codecs. A device may receive validation results for a video codec using a first computer programming language, the validation results indicative of invocations of functions and conditions of the code; identify, from the validation results, a first validation test that invoked a first function or condition of the code; identify, from the validation results, a second validation test that invoked the first function or condition of the code; determine, from the validation results, that the first validation test and the second validation test overlap in invoking the first function or condition of the code using the first computer programming language; and generate, based on the overlap, a first subset of the validation tests with which to validate code of the video codec using a second computer programming language.

The invention discloses an automatic generation method of an API process scene based on a gateway and a large model, and relates to the technical field of API testing. The method comprises the steps of marking and executing a test case, capturing and verifying gateway data, exporting a JMX test script, exporting request response details, intelligently analyzing a large model, storing returned content as a standard JMX file, and executing verification. Through cooperative work of the gateway and the large model, automatic capture, data association analysis and test script generation of an API test scene are realized, the generation time of the API test script is shortened from an hour level to a minute level, and the efficiency is improved by more than 10 times; non-professionals can generate complex test scripts through simple operation, and dependence on professional testers is reduced; a large model automatically analyzes data association, and omission and errors caused by manual analysis are avoided; full-process automation from interface calling and capturing to test script generation is achieved, and tool switching is reduced.

According to the test method for the high-low priority scheduling mechanism of the A664 switch, a minimum test environment is established, an A664 tester with four physical ports is used, and verification cases of high-priority data frame priority forwarding, priority data integrity and the number of high-low priority buffer areas in a congestion scene are designed. The integrity and accuracy of high-low priority transmission function verification are ensured, and the problem of verification test of the high-low priority working mechanism of the A664 network in the prior art is effectively solved. The method is high in universality and can be suitable for various A664 network devices and application scenes.

The application discloses a PLC code generation and verification method based on a large language model, which comprises the following steps: generating multi-stage multi-modal input data, wherein the multi-stage multi-modal input data is used for representing user requirements and formulating a system design scheme according to a requirement analysis result; the multi-stage comprises a requirement analysis stage and a design stage of a complete engineering cycle; the multi-modal input comprises a P&I D diagram and natural language; then, PLC code is generated according to the multi-stage multi-modal input data; then, the generated PLC code is verified and tested, wherein the verification and testing comprises code verification and compiler verification; finally, the PLC code is deployed after the verification and testing of the PLC code are completed. The embodiment of the application has high accuracy and high automation degree, can provide a network security researcher with an efficient and accurate PLC code deployment method, and can be widely applied to the technical field of computers.

The application discloses a kind of integrated power supply basic module test method and system, the method includes: establishing integrated power supply basic module unified test data model, based on the model, the basic module test index verification data sequence is constructed, with the sequence as foundation, local data and task processing thread are established to carry out the processing of each test data;Create local communication thread, and the automatic verification of each index of integrated power supply basic module is carried out in combination with test index verification data sequence and data and task processing thread, and module performance index verification test report is generated;Create enterprise cloud end interactive thread and carry out the association of test report and cloud end order data.The application improves the production test efficiency of integrated power supply basic module.

The application discloses a complex electronic hardware compliance verification test system based on simulation vector multiplexing, and belongs to the technical field of electronic hardware testing.The simulation test vector generation module is configured to receive a hardware design requirement document, establish a requirement pin mapping table, encapsulate a simulation excitation vector with timing annotation, generate a test vector file, and design a high-fidelity verification module board card module, so that the board card module is kept consistent with a target product board card, the measured hardware circuit is connected, preset test points monitor signals of the measured hardware circuit, the core control module includes a timing reconstruction engine, the test vector file is read, an actual output vector file is generated, the actual output vector file is verified by an automatic verification closed loop module, a test report including a compliance evidence chain is generated, efficient simulation vector multiplexing can be realized, simulation and actual measurement timing behaviors are consistent and aligned, synchronous linkage of excitation application and response acquisition is realized, and verification efficiency and checking accuracy are improved.

A method comprises selecting a first data set including a first magnetic anomaly map of a given area, the first map having a first accuracy; selecting a second data set including geological data for the given area; sending the first and second data sets to a machine learning model; and generating a second magnetic anomaly map of the given area based on the first and second data sets, the second map having a second accuracy higher than the first accuracy. The method further comprises comparing the second map with a ground truth map to train the machine learning model; and performing a validation test of the trained machine learning model by sending an additional data set including held-out magnetic anomaly map data to the machine learning model. In response to a validation threshold being met, the trained machine learning model is used to generate higher accuracy magnetic anomaly maps.

A computer-implemented method for performing a regulatory validation process is provided. The method includes receiving, via a web-based application, a request to initiate a validation study for a selected asset or process; retrieving, from a validation protocol database, a pre-approved validation protocol corresponding to a type of the selected asset or process; displaying, via a user interface, one or more verification tests of the validation protocol, each verification test having associated instructions, acceptance criteria, and / or required data entry fields; receiving, from an authenticated user, input data for at least one of the verification tests; receiving an electronic signature from the authenticated user, the electronic signature being applied using multi-factor authentication; automatically recording the user input data, electronic signature, and corresponding timestamps in an audit trail database; and generating, responsive to completion of the validation protocol, an electronic validation report in a compliance-ready format.

Generative artificial intelligence is applied to a manufacturing process to create a test plan for validation, including proof of execution of various test, process steps, and the like.

A system and method are provided for implementing a network component, such as a software-defined wide area network, a firewall, a router, or a load balancer. The network component can be an embedded network edge device that is implemented, e.g., in software, in circuitry, or using hardware acceleration (e.g., a data processing unit (DPU), a smart network interface card (SmartNIC), etc.). The system can a primary (first) dataplane and a shadow (second) dataplane. During verification testing, the network function (e.g., routing) is performed by transmitting the egress packets from the primary (first) dataplane, but using the egress packets from the shadow (second) dataplane only for verification testing. After verification testing, the shadow (second) dataplane is promoted to be a new primary dataplane by gradually increasing the ratio of the output packets that originate from the new primary (second) dataplane until all output packets originate from the second dataplane.

A diversified validation test suite application (DVTSA) for a generative AI-powered tool or a large language model (LLM) includes at least a first, a second, and a third control logic. The first control logic receives seed test input or user input, analyzes the seed test input or user input, and extracts key elements for variations. The second control logic performs a coverage measurement of the outputs of the first control logic. The third control logic prompts a human tester to evaluate the outputs of the second control logic against predefined coverage metrics and to iterate selectively and continuously to ensure that the outputs of the second control logic increase the LLM tool's input and output robustness from a first level to a second level that is higher than the first, in both production and pre-production LLM tool processes.

System (100) for verifying partial functions of advanced driver assistance systems (ADAS) and / or automated driving systems (ADS) at synchronization points (750, 755), wherein a synchronization point (750, 755) is a predefined point in time or phase in the development process of an ADAS / ADS system at which all necessary changes to the system architecture, software or hardware are integrated, and wherein specific test cases (350) are executed at this synchronization point (750, 755) to ensure that all relevant functional groups (450) function properly, comprising an input module (200) for inputting available functional groups (450) and synchronization points (750), in particular with specifications relating to the system architecture or software updates;a test case generation module (300) configured to generate a set of test cases (350) for testing and verifying an ADAS / ADS system; a function grouping module (400) configured to divide the set of test cases (350) into function groups (450), each function group (450) representing a sub-function of the ADAS / ADS system; a prioritization module (500) configured to assign priority classes (550) to the function groups (450) based on the probability of errors occurring and the effort required to correct them; a synchronization module (700) configured to assign the corresponding function groups (450) and the test cases (350) associated with the function groups (450) to the synchronization points (750, 755);a test management module (800) configured to consider the maximum number of test cases (350) per synchronization point (750) and, if this number (350) is exceeded, to move test cases (350) with a low priority class (550) to subsequent synchronization points (755); and an output module (900) configured to output the selected test cases (950) for a synchronization point (750) to increase the efficiency of verification tests and reduce resource requirements.

The invention discloses a method for playback of a production acquisition message to a test environment for verification and comparison, and relates to the technical field of software testing, the method comprises the following steps: capturing an original request and a return message of an online transaction in real time through a non-intrusive acquisition mechanism in the production environment, and storing the original request and the return message in a physically isolated special database node in a structured manner; importing the message data set and the backup mirror image of the production database into a test environment; deploying an application version to be put into production in a test environment, and starting a message driving module and a virtual service module for playback; after playback is completed, field-level consistency comparison is carried out on the messages of the second type and the messages of the fourth type, difference identification and consistency comparison based on a table structure, a primary key and a change field triple are carried out on database change records, and the method avoids real-time network connection of production and test environments, reduces safety risks and system modification cost, and improves system performance. And the message playback verification test precision and the system automation test level are improved.

The application relates to a cross-level processor verification method, system, electronic equipment, storage medium and computer program product, and the method comprises the following steps: constructing a script, the script is used for converting standard assembly into assembly-like text and converting the assembly-like text into a hexadecimal file, or is used for converting the assembly-like text into standard assembly; in the case that system-level verification needs to reuse module-level verification test cases, the script is used to convert the assembly-like text corresponding to the module-level verification into standard assembly, and system-level verification is performed based on the standard assembly; in the case that system-level verification needs to reproduce module-level verification, the script is used to process the standard assembly corresponding to the system-level verification to obtain a hexadecimal file, and the hexadecimal file is used for module-level verification. The script is used to convert standard assembly into assembly-like assembly to realize the downward reproduction of system-level cases, and the assembly-like assembly is converted into standard assembly to realize the upward reuse of module-level cases, so that cross-level processor verification is finally realized.

Apparatuses, methods, and systems pertaining to the verification of portable consumer devices for 3-D Secure Systems are disclosed. In one implementation, a verification token is coupled to a computer by a USB connection so as to use the computer's networking facilities. The verification token reads identification information from a user's portable consumer device (e.g., credit card) and sends the information to a validation entry over a communications network using the computer's networking facilities. The validation entity applies one or more validation tests to the information that it receives from the verification token. If a selected number of tests are passed, the validation entity sends a 3-D Secure datum to the verification token. The verification token may enter the 3-D Secure datum into a hidden field of a Purchase Authentication Page appearing on the computer's display.

Systems and methods for bias testing and remediation are disclosed. Decentralized Web Application Testing Systems use a Holochain framework to distribute testing workloads across Full Nodes and Lightning Nodes. A Holochain Node Management Application for configuring nodes, a UI Application creates test cases, and a Version Management System tracks changes. Test results are stored and analyzed in a Test Result Store, with a Bias Intelligence module detecting biases and generating additional test cases. A Consensus Algorithm validates test cases through decentralized nomination. An AI-Driven Defect Remediation System automates defect detection, root cause analysis, and remediation using AI modules. Machine learning algorithms identify patterns and anomalies, while NLP techniques generate code fixes. Predictive maintenance monitors application performance to preemptively address issues. A feedback loop mechanism continuously improves AI models through reinforcement learning. Together, these systems provide a holistic approach to web application testing and maintenance.

The invention discloses a method and a system for quickly verifying binary messages in an automobile test, and belongs to the technical field of automobile electronic tests. The method comprises the following steps: constructing a structured verification rule set, executing a test and capturing a message flow, carrying out real-time matching verification and generating and outputting an accurate positioning report based on a rule engine, and pre-defining the structured verification rule set corresponding to an expected behavior of a tested piece through a configuration interface of upper computer software. The set of structured validation rules is independent of the test execution logic. According to the method, the verification test period is greatly accelerated, not only can static signal values be verified, but also complex logic, dynamic field behaviors and message time sequences among signals can be deeply verified, a structured test report obtained through the method can directly locate violated specific rules and signals, and the problem debugging and root cause analysis time is greatly shortened.

The present application relates to the technical field of micro-grid simulation, and particularly relates to a micro-grid closed-loop cross-validation simulation system, method, device and medium, the system comprising a bottom data generation module, a topology automatic mapping module, a communication protocol module, a master station control module, an index evaluation module, a man-machine interface module and a historical section playback module; the system can simulate the steady-state operation characteristics of different types of micro-grid elements, can interact with an external micro-grid energy management system based on the system, and can realize closed-loop cross-validation testing through the master station simulation function; the system can simulate different characteristic resources, verify different investment subjects and different user operation targets, verify micro-grid dynamic aggregation capability, verify micro-grid coordination, and the like; and based on the system, micro-grid group verification can be realized to provide a test environment for master station micro-grid group coordinated control.

The application relates to the field of automatic testing, and discloses a user interface automatic testing method and device, computer equipment and a storage medium. The method comprises the following steps: configuring a test environment through an environment configuration tool, and determining whether the test environment meets a condition; when it is verified that the test environment meets the condition, positioning the target equipment through a test service tool, acquiring page control information corresponding to the target equipment; writing the page control information into a target text according to a preset instruction; and converting the target text into a target script through an implementation module in the preset test environment to realize automatic testing of the target equipment. In the above manner, when it is determined that the test environment meets the current target equipment, the page control information of the target equipment is acquired, the page control information is written into the target text and converted into the target script which can be executed by the target equipment, so that the UI automatic testing of the target equipment is realized, and the UI automatic testing efficiency is improved.

A system and method for automated software testing that uses machine learning algorithms to automatically generate and implement software testing based on an automated analysis of the software. In an embodiment, a mobile software application comprising one or more screens is processed through a trained machine learning algorithm to identify screens and objects, understand the operational flow of the application, define priorities and dependencies within the application, define validation tests, and automatically generate one or more testing scenarios for the application. The testing scenarios may then be fed to an automated execution module which installs the application on one or more physical or virtual devices and performs testing on the application installed on those devices according to the testing scenario.

The application discloses a code testing system and method of a screen menu type adjustment mode, relates to the technical field of OSD testing, and mainly aims to realize verification testing on the screen menu type adjustment mode in the development stage of the screen menu type adjustment mode. The main technical scheme comprises the following steps: a testing platform is used for deploying to-be-tested codes of to-be-tested OSD, generating OSD data in response to an OSD request, wherein the OSD request corresponds to a function point of the to-be-tested codes, and the OSD is the screen menu type adjustment mode; a format conversion device is used for converting the data format of the OSD data into a target format required by a display device; and the display device is used for performing display corresponding to the OSD data.

The invention relates to a method, a device, equipment and a medium for automatically converting an automobile CAPL language into a C language, and the method comprises the steps: processing a collected CAPL code text of an automobile electronic project to obtain a data set, dividing the data set into a training set, a verification set and a test set, and carrying out the marking to obtain a real C language code corresponding to the CAPL code; the method comprises the following steps: constructing an AI model based on a Transform architecture; inputting the training set into an AI model for training to obtain a predicted C language code; adjusting the AI model according to the difference between the predicted C language code and the real C language code, and verifying the AI model by adopting the verification set; the test set tests and evaluates the verified AI model; and inputting the to-be-converted CAPL code into the AI model passing the test evaluation for conversion to obtain a converted C language code. The AI model constructed by the method can understand semantics and bus communication logic of CAPL codes, the CAPL codes are converted into C languages with equivalent functions and good structures, and the need of manual intervention is greatly reduced.

The invention discloses a verification test method for an M-PHY layer of a UFS. The verification test method comprises the following steps: step 1) setting up a test environment; configuring a multi-rate adaptive test engine; configuring an inter-channel interference simulation system; configuring a protocol perception type state machine verifier; the verification test method for testing the M-PHY layer of the UFS comprises the steps of (1) carrying out an M-PHY layer, (2) carrying out a multi-rate adaptive test, (3) carrying out an inter-channel interference simulation test, and (4) carrying out protocol perception type state machine verifier.The verification test method for testing the M-PHY layer of the UFS can verify the data integrity and reliability of UFS equipment on the M-PHY layer.

The present invention relates to a method and a system for generating one or more compliance documents for vehicle development. The method involves receiving a user query specifying parameters such as use cases, weight class, performance targets, energy type, propulsion type, software features, and environmental conditions. A processor determines system, subsystem, and component requirements, as well as compliance requirements, using data stored in a memory. The data includes information on systems, subsystems, components, risk levels, compliance standards, and validation tests. The method further categorizes systems and components into risky and non-risky groups, validates compliance with functional safety, cybersecurity, emissions, and connectivity standards, and performs validation tests to ensure alignment. The generated compliance documents incorporate system requirements, compliance strategies, validation results, and industry-standard alignment, providing a system to a component-level guide for vehicle development.

The invention discloses a configuration release method, device and equipment with multi-layer environment isolation and a storage medium, and relates to the technical field of software configuration and release, and the method comprises the following steps: obtaining a to-be-released version configuration file and a multi-branch environment isolation strategy; performing stage division on a simulation environment according to the multi-branch environment isolation strategy to obtain a development test environment, a verification test environment, a gray release environment and a production environment; sequentially performing corresponding configuration verification on the version configuration file in the development test environment, the verification test environment and the gray release environment to obtain a verification result; and releasing the version configuration file to the production environment according to the verification result. According to the invention, by introducing a multi-branch environment isolated staged configuration release mechanism, gradual verification of configuration change is realized, the problem of coarse version management granularity in traditional configuration release is solved, and the stability and security in the configuration release process are improved.