143 results about "Quality assurance" patented technology

The invention discloses a product full-life-cycle traceability after-sales service system based on multi-source heterogeneous data, and relates to the technical field of product traceability after-sales management. Manufacturing resumes, work orders, spare part warehouse-in and warehouse-out and equipment logs are accessed, mapping of product instances, parts and software primary keys is established, and the product traceability after-sales service system is established. And normalizing the configuration change event into a configuration change event containing double time axes of effective time and warehousing time, and writing the configuration change event carrying differential operation, an evidence packet and an idempotent event identifier into an immutable event library. And constructing a conflict set for the same configuration target, executing uniqueness, causality and compatibility constraint verification, determining an effective event based on evidence packet arbitration, and outputting an arbitration record and confidence. And deriving a configuration version chain according to the effective event and generating a snapshot, performing incremental playback on the late or error correction event and generating an influence propagation list. And when any time point configuration is queried, playback restoration is performed, an evidence chain and confidence are output, an active verification backflow error correction event is triggered if the confidence is insufficient, and the accuracy of quality guarantee judgment and spare part matching is improved.

The invention relates to the technical field of computers, and discloses a chip mounter material tracing management method and system based on a knowledge graph. The method comprises the following steps: constructing a dynamic knowledge graph covering the whole process of a patch; injecting multi-source data in real time to drive dynamic updating of the atlas; when the materials are abnormal, reverse tracing and forward influence double-path reasoning are started; isolation, rework and reset instructions are automatically generated and pushed to a manufacturing execution system; and synchronously updating the atlas state to form an auditable record. The system comprises a dynamic knowledge graph construction module, a real-time data injection module, a bidirectional inference engine module, an automatic processing instruction generation module and a graph state synchronization module. According to the scheme, millisecond-level error positioning and closed-loop processing are realized, and the tracing efficiency and the quality guarantee capability are improved.

The invention relates to the technical field of information, and particularly discloses an online mall platform intelligent management method and system, and the method comprises the following steps: S1, constructing a data collection system, and obtaining platform operation data, user behavior data and external market data in real time; s2, acquiring historical sales data, analyzing the historical sales data by adopting a Prophet time sequence model, predicting a future sales trend and inventory requirements, and generating a dynamic replenishment suggestion; s3, optimizing inventory management through a dynamic programming algorithm, calculating an optimal inventory threshold value in combination with external market data, and performing automatic replenishment triggering; s4, establishing a user portrait according to the user behavior data, and generating a personalized coupon strategy based on a collaborative filtering algorithm; s5, dynamically matching the work order and the customer service according to a multi-attribute decision algorithm; and S6, storing quality assurance information, and ensuring non-tampering and traceability of construction time, material batches and technician ID data. Therefore, the operation efficiency and the user experience of the shopping mall platform are improved.

An assessment system can generate a software quality value based on testing results and analysis of a multitude of factors that impact a readiness evaluation. For example, the system generates a software quality score (e.g., an Applause Quality Score “AQS”) that enables development teams to understand the level of quality they are achieving for a given release and build-over-build. In various examples, the system generates a data-driven score to enable development teams or quality assurance teams to make decisions for when a build is ready for release. In further embodiments, the system can integrate user interfaces that present a software quality score in a user dashboard that is linked to version control systems. On review and acceptance of the score, a user can trigger the release of their new code or product.

The invention discloses an intelligent report generation system, method and device and a storage medium, and relates to the technical field of data processing, and the system comprises a main research agent which is used for multi-source data information collection and preliminary analysis; the report writing agent is used for converting the research result into a professional report; and the review agent is used for reviewing the professional report. A multi-agent collaborative architecture and a domain knowledge enhancement technology are deeply fused, a full-link quality assurance system including data credibility evaluation, multi-source cross validation and dynamic knowledge updating is established, and collaborative optimization of professional report generation in three dimensions of timeliness, economy and specialty is realized.

The invention relates to the technical field of software engineering management, and discloses a computer software development information management system and method. According to the method, real-time multi-dimensional association among four entities, namely a demand entity, a code entity, a test entity and a deployment entity is realized by constructing a dynamic knowledge graph center, and an end-to-end closed-loop control system is formed; a full-link traceable network is dynamically established through explicit binding, implicit capturing and cross-layer traceability mechanisms, demand omission marks are automatically repaired, and accurate attribution of environmental problems is achieved; manual operation blind areas are eliminated through automatic means such as developing and submitting forced association, automatically freezing branches when test fails and deploying environment consistency verification; based on a risk thermodynamic diagram of full-link topology penetration and fusion defect density and change frequency, active early warning of a high-risk module is realized, and controllability and quality assurance capability of a software development process are remarkably improved.

Systems and methods are provided for implementing quality assurance for digital technologies using language model (“LM”)-based artificial intelligence (“AI”) and / or machine learning (“ML”) systems. In various embodiments, a first prompt is provided to an LM actor or attacker to cause the LM actor or attacker to generate interaction content for interacting with test software. Responses from the test software are then evaluated by an LM evaluator to produce evaluation results. In some examples, a second prompt is generated that includes the responses from the test software along with the evaluation criteria for the test software. When the second prompt is provided to the LM evaluator, the LM evaluator generates the evaluation results.

Systems and methods for providing an automated quality assurance framework for infrastructure as code (“IaC”) implementations are provided. Pull requests with proposed change to existing IaC source code (“changed code”) are received from user devices, each associated with either a service enablement team member or an applications development team member. Team specific versions of the quality assurance framework are automatically triggered for the changed code which require successful passage through multiple modules, such as in a successive manner, before automatically being merged into the existing IaC source code.

The invention provides a data processing method and device, computing equipment, a storage medium and a program product, and the method comprises the steps: determining a target task, and distributing the target task to a target client; in response to a code submission request sent by the target client, processing submission information carried in the code submission request by using a task association model, and determining an association task corresponding to the code submission request; under the condition that the associated task is the target task, performing construction and test inspection on the target task; under the condition that the inspection is passed, a target version program corresponding to the target task is released, and a version report corresponding to the target version program is generated and sent to an associated client; the standardization and traceability of version release are improved, and the information transparency of cross-team cooperation is enhanced; the automation level, the quality guarantee capability and the cooperation efficiency of the software research and development process are optimized, and efficient and reliable version management can be achieved.

The invention discloses an intelligent code writing and quality assurance system for multi-language code analysis, which relates to the technical field of intelligent code development and quality control and comprises a multi-language code analysis engine, an intelligent engineering management module, a self-adaptive compiler, an interactive console, a multi-dimensional instance library and a personalized configuration center, each module realizes real-time data interaction through a distributed data bus; the system supports more than 15 mainstream programming languages, new language support can be expanded through plug-ins, and the multi-language code analysis engine integrates static analysis, dynamic tracking and cross-language call detection functions. Static analysis identifies grammar errors and undefined variables through abstract syntax tree analysis. According to the intelligent code writing and quality assurance system for multi-language code analysis, the single-language limitation of a traditional system is broken through, conjoint analysis of programming languages is achieved, cross-language defect recognition accuracy is improved, and potential risks of multi-language projects are remarkably reduced.

The invention relates to a computing fusion data application method based on full life cycle quality assurance. The method comprises the steps of performing regularization integration on computerization original data of a computing power network to obtain a computerization fusion initial data set; performing standard system processing on a space-time three-dimensional field in the computerized fusion initial data set to obtain a standardized data set; carrying out coupling representation learning on the computerization related data in the standardized data set to obtain a computerization coupling portrait set; performing collaborative optimization arrangement on the computing power network according to the standardized data set and the computing coupling portrait set to obtain regulation and control and transaction integrated plan information; and performing instruction conversion on the strategy elements of the regulation and transaction integrated plan information to obtain a multi-scale execution instruction set. The method can ensure that the utilization degree of the computerization fusion data is difficult to load the current power grid requirement.

The invention, which belongs to the technical field of product appearance inspection, discloses an all-dimensional inspection system for the appearance of an automobile pipeline finished product, and the system comprises four core modules, namely a full-view image acquisition work station, an image processing and interpretation engine, a result feedback and execution mechanism and a data management and tracing interface. Wherein the image acquisition work station realizes multi-angle dead-corner-free image acquisition of a pipeline through cooperative work of a multi-axis positioning clamp and a fixed camera array; the image processing engine adopts a white-box algorithm library based on physical imaging characteristics and combines a graphical configuration interface to realize efficient and reliable defect detection; and the data management interface is used for binding and tracing the whole process of the inspection data, and reversely guiding the quality information to the previous process through the closed-loop feedback module. According to the invention, manual inspection is converted into automatic and intelligent inspection, the detection efficiency and accuracy are obviously improved, the labor cost is reduced, and reliable quality guarantee is provided for automobile pipeline manufacturing.

Techniques for monitoring a pharmaceutical manufacturing process and making determinations regarding the release of radiopharmaceuticals to health care providers. A data processing system collects data across multiple batches of radiopharmaceuticals, across multiple entities, and / or across multiple stages of the manufacturing process, processes the data, and provides feedback to entities involved in the manufacturing process. In scenarios where quality assurance tests are conducted, data is collected from radiopharmaceutical products before they are shipped, and the data is analyzed to provide the recipients with an indication of whether the radiopharmaceutical products satisfy quality assurance standards. Techniques for analyzing information about a batch manufacturing process and, when a problem occurred during a manufacture of a batch, determining whether to continue to manufacture a next batch in time for delivering and administering to a patient. The detected problem may be investigated and remedied before or during the synthesis of the next batch.

Devices, systems, machine-readable media, and methods for quality assurance of an additively manufactured part are provided. A method includes receiving by a manufacturer, a proprietary additive manufacturing process parameter, a non-proprietary additive manufacturing process parameter, and sensor data indicative of a build condition of an additively manufactured part, the build condition indicative of an attribute of the additively manufactured part during the additive manufacturing process; identifying, based on the proprietary additive manufacturing process parameter, the non-proprietary additive manufacturing process parameter, and the sensor data, a defect of the additively manufactured part; filtering out the proprietary additive manufacturing process parameter, resulting in filtered information; generating, based on the filtered information, a quality assurance report of the additively manufactured part; providing the quality assurance report to a customer, the quality assurance report includes a description of the defect and location of the defect; and delivering, based on the defect passing a part acceptance criterion, the additively manufactured part.

This invention provides a semi-automatic method for constructing and iterating an ontology in the financial and tax domain, comprising the following steps: S1, system initialization and configuration; S2, data acquisition and preprocessing; S3, based on a few-shot learning model and an expert rule base, automatically extracting core concepts from structured financial and tax data and inferring relationships between concepts, performing hierarchical modeling according to financial and tax business logic, and generating a draft ontology model; S4, multi-dimensional automatic verification and manual optimization of the draft; S5, ontology output and version management; S6, dynamic iterative update of the ontology; S7, iterative automatic verification of the ontology in multiple dimensions. This invention achieves four core advantages: improved efficiency, quality assurance, scenario adaptation, and dynamic updates, solving key technical challenges in the construction and application of ontology in the financial and tax domain, providing core support for the efficient operation of financial and tax intelligent agents, and possessing broad application prospects and commercial value.

The invention discloses an AI-based code quality intelligent review and automatic distribution system and method, and relates to the technical field of software development and quality assurance, the AI-based code quality intelligent review and automatic distribution system comprises an event triggering and capturing unit, a code change extraction and analysis unit, an intelligent review engine starting unit, an AI analysis and decision unit and a feedback and closed loop unit; the event triggering and capturing unit is used for monitoring a code pushing event for submitting a code to a remote GitLab code library after a developer completes function development locally through a GitLab platform, generating an HTTP request and sending the HTTP request to the code change extraction and analysis unit; through the Webhook mechanism provided by the Gitlab, 'triggering upon code submission 'is realized, manual intervention is not needed, the feedback period is greatly shortened, and the development efficiency is improved.

Methods, systems, and apparatuses for improved quality assurance (QA) are described herein. A computing device may provide a user interface having multiple user interface elements that allow a user of the computing device to interact with a QA system. Each of the user interface elements may be associated with one or more QA tasks for a type(s) of medical equipment. The computing device may receive input from the user via at least one of the user interface elements. The computing device may determine a completion value for at least one of the QA tasks. The computing device may send an update message indicative of the completion value for the at least one QA task.

An example quality assurance (QA) system for a radiosurgery system is described herein. The system includes an appliance comprising: a housing, an indicator; and an actuator configured to move the indicator; a controller in operable communication with the appliance, where the controller comprises a processor and a memory, the memory having computer-executable instructions stored thereon that, when executed by the processor, cause the processor to: transmit one or more control signals to the appliance in accordance with a QA test protocol, where the QA test protocol comprises moving the actuator from a first position to a second position, the first and second positions being separated by at least a first predetermined distance.

The invention discloses a timely software quality assurance method based on automatic defect detection and software testing, and belongs to the technical field of software quality assurance. The method comprises the following steps: pre-training a timely defect prediction model, predicting a prediction probability that a current code change has defects, and judging whether the current code change needs to be tested or not; searching a test suite related to the current code change; selecting or generating a test case related to the current code change; and executing the test case to judge whether the current code change introduces defects or not, and updating the timely defect detection model by using the current code change. According to the method, a collaborative guarantee mechanism of automatic defect detection and software testing is constructed, the advantages of real-time prediction and determinacy verification are fused, test resources are dynamically optimized, the problems of verification delay and test case missing are solved, efficient quality guarantee without manual intervention is achieved, and the software development iteration rate and reliability are remarkably improved.

The invention particularly relates to a database quality monitoring and diagnosing method based on a model context protocol. According to the database quality monitoring and diagnosing method based on the model context protocol, initialization configuration is completed through an MCP Server, and a probe unit collects operation indexes and original operation logs of a database in real time and transmits the operation indexes and the original operation logs to the MCP Server; early warning and automatic identification and root accurate positioning of anomalies are realized through the MCP Server, a solution is automatically executed, and closed-loop management of database states is realized; and the large model monitoring module performs abnormal attribution analysis, triggers an alarm notification, and archives historical downtime and error information to a knowledge base. According to the database quality monitoring and diagnosis method based on the model context protocol, real-time monitoring, intelligent abnormity diagnosis and rapid problem positioning of multi-dimensional quality indexes of the database are realized, the manual intervention cost is reduced, the efficiency and reliability of database quality assurance are improved, and the method is suitable for popularization and application. And the full-life-cycle quality management requirements of different types of databases can be met.

This invention discloses a machining process for precision screws, belonging to the field of mechanical manufacturing technology. It includes the following steps: S1, rough machining and forming: treating the surface of the bar stock and machining functional slot structures, followed by pre-deburring; S2, structural strengthening: heat-treating the workpiece for strengthening; S3, precision finishing: correcting the form and position tolerances of the heat-treated workpiece and precision grinding each surface; S4, quality assurance delivery: completing inspection, cleaning, and packaging. This process flow is clear, employing a logical arrangement of "forming first, then strengthening, and then fine-tuning," resulting in a workpiece with not only a high-hardness surface but also improved coaxiality of its stepped axis and thread trajectory accuracy. This significantly enhances the screw's operational stability at high speeds. Furthermore, through staged quality control and precision correction, it improves the first-pass yield of the workpiece and reduces the risk of scrap due to heat treatment deformation, possessing extremely high industrial application value.

To provide a determination method capable of checking whether or not a target molecule is hydrogen generated by water electrolysis or a molecule generated by using the hydrogen as a raw material, a quality assurance method, and a determination device.SOLUTION: In a determination method, when a deuterium presence ratio relative to light hydrogen of a target molecule is equal to or less than a predetermined threshold value that is smaller than the deuterium presence ratio relative to light hydrogen in nature, the target molecule is determined to be an electrolytic hydrogen-containing molecule.SELECTED DRAWING: None

The invention relates to the technical field of software engineering management, in particular to a software development control method. The method comprises the following steps of: decomposing a software application into a plurality of independent software modules according to software development requirements, and acquiring characteristic measurement of each software module; based on the feature measurement of each software module, determining a reconstruction probability score of the software module; determining the risk level of the software module according to the reconstruction probability score; selecting a matched control strategy for the software module from a plurality of predefined control strategies based on the risk level; and applying the control strategy corresponding to the selected software module to the subsequent development process of the software module. Through the data-driven and differentiated control method, the quality assurance resources can be accurately projected to the most required links, so that the software delivery speed is increased, and the stability and maintainability of the system are remarkably enhanced.

The invention relates to a method (1) for quality assurance in the production of assemblies, in particular in vehicle manufacturing, - where individual parts are manufactured and associated individual part data relating to the manufacture of the respective individual part are recorded, - in which the manufactured individual parts are each placed in a compartment of a load carrier and associated compartment data, which individually identify the respective load carrier and the respective compartment of the respective load carrier in which the respective individual part has been placed, are recorded, - in which the individual part data and the associated technical data for each manufactured part are linked together and transmitted to a database, - in which an assembly is built using several individual parts, for which the individual parts are taken from the respective compartment and the associated compartment data is recorded, - where the database queries the individual part data for the technical data of the individual parts used in assembling the respective assembly, and - where assembly data that is individually assigned to the respective assembly is generated by linking the individual part data of the individual parts used in assembling the respective assembly.

To improve quality assurance and durability of coated components, a multifaceted inspection coupon is provided that includes opposing flat surfaces, separated by sides which include one or more curves or fillets representing surfaces of the coated components to be inspected. The inspection coupon is coated on all sides in the same manner as the components to be inspected, whereby later analysis of the coupon provides quality assurance of all coated surfaces of the components at once.

The subject matter herein provides for AI-based prediction of production defects in association with a production system, such as a semiconductor manufacturing machine. In one embodiment, a method begins by receiving production data from the production system. The production data typically comprises non-homogeneous machine parameters and maintenance data, quality test data, and product and process data. Using the production data, a neural network is trained to model an operation of a given machine in the production system. Preferably, the training involves multi-task learning, transfer learning (e.g., using knowledge obtained with respect to a machine of the same type as the given machine), and a combination of multi-task learning and transfer learning. Once the model is trained, it is associated with the given machine operating environment, wherein it is used to provide quality assurance predictions.

The invention provides a control software joint simulation hardware-in-the-loop test system and method. The system comprises a hardware-in-the-loop test platform, a test project management platform and an automatic test platform. The hardware-in-the-loop test platform comprises an IO interface board card and a real-time simulation machine which are respectively used for connecting a physical controller and operating a controlled object model containing a virtual controller model; the system supports the hybrid deployment of a real object and a virtual controller: the controller of a selected type can be accessed in the form of the real object, and meanwhile, a corresponding virtual model in a real-time simulation machine replaces a non-accessed controller of the same type, so that the controller and the real-time simulation machine interact in real time to form a closed-loop test. According to the method, flexible configuration and reuse of a test environment are realized, a whole-process closed loop from test management, automatic execution to result tracing is completed, the method has software quality quantitative measurement and continuous improvement capabilities, and the test efficiency, coverage depth and quality assurance level of the new energy automobile control software are remarkably improved.

The invention discloses a regression test case generation method based on a code large language model, and belongs to the technical field of computer programs. The method comprises the following steps: a step of automatically generating and evaluating a test case oriented to a C language program, a step of generating a test expectation by dialogue with a code large model and using a voting tool, a step of constructing a customized prompt (prompt) template oriented to a C language program type, and a step of generating a test case oriented to a natural language description test requirement. According to the method and the device, the problems of searching in a huge test case space to obtain a high-quality test case and obtaining a reliable test expectation (Oracle) are solved. By combining human intelligence with the generation capability of the code large model, the accuracy, coverage and effectiveness of the test case can be effectively improved, and the problem that a traditional test case generation tool cannot generate test expectation (Oracle) can be solved, so that the software development process is accelerated, and the quality assurance level of software is improved.

The invention provides a submission information generation method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring a code change block; performing fine-grained extraction on the pre-change code and the post-change code of the code change block to obtain code fine-grained representation; performing feature retrieval on the code fine-grained representation based on an existing submission information base to obtain a corresponding first candidate submission message; performing context interaction and sub-word multiplexing processing on the code fine-grained representation to obtain a second candidate submission message; and calling a pre-constructed quality assurance model to process the first candidate submission information, the second candidate submission information and the change code of the code change block to generate target submission information, the pre-constructed quality assurance model being constructed based on a sample set. Therefore, the generation accuracy of the submitted message is improved.

A semantic similarity-based configurable system for automatic scenario detection in customer-agent conversations is disclosed. The system understands intent from semantic similarities in vector space between speaker sentences, does not rely on the use of synonyms, and tolerates a large amount of paraphrasing. This approach is easily scalable to a large number of customers and can be fed more data to increase accuracy and precision. Furthermore, the system is configurable in real time, allowing clients to control which intents are detected and how. In some embodiments, the semantic similarity-based configurable system includes a scenario detection system, a conversation tagging system, a bi-encoder, and a cross-encoder. The scenario detection system receives inputs of sample phrases and customer and agent utterances and generates results. The sample phrases may be phrases and keywords that describe scenarios representing customer or call agent behavior.