254 results about "Software feature" patented technology

The invention provides an automatic software testing method and system based on artificial intelligence. The method comprises the following steps: analyzing a software demand document by using an NLP technology, converting the software demand document into structured data, extracting a key function point, and identifying a software function point; generating a test case covering all function points through a deep learning model in combination with historical test data training; automatically executing a test operation, analyzing a test result, analyzing a test log by using a machine learning algorithm, identifying and classifying potential defects by using a data mining and pattern recognition technology, and generating a repair suggestion report; and analyzing feedback data in the test process, dynamically adjusting a strategy according to a test result by using a reinforcement learning algorithm, and optimizing a test case and the strategy. According to the invention, intelligent analysis of test data, automatic generation of test cases and automatic execution of a test process are realized; flexible configuration and expansion can be carried out according to the actual condition of software; the test efficiency and quality are improved, and the test cost and manpower consumption are reduced.

The embodiment of the invention provides a multi-configuration relay-oriented aircraft electrical box parameter measurement system and method, and belongs to the field of aircraft electrical box test and diagnosis. According to the hardware level, flexible access of a multi-configuration relay electrical box is achieved based on a universal adapter interface, core parameter measurement is completed in combination with an integrated measurement and control circuit, and synchronous acquisition and processing are conducted on multiple paths of signals through a signal acquisition and processing unit; according to the software level, the pull-in / release time, the rebound time and the voltage parameters are accurately calculated through a parameter calculation module on the basis of waveform feature point recognition and dynamic excitation-response theories, and the functions of fault diagnosis, safety protection and data storage are integrated. According to the method, the crossing from on-off judgment to parameterized precise evaluation is realized, the detection efficiency, the measurement precision and the equipment reliability evaluation capability are remarkably improved, and an integrated solution is provided for external field maintenance and state prediction of the aircraft relay.

The invention discloses an automatic software function testing and evaluating method based on a multi-modal large model, and particularly relates to the field of non-embedded software function testing and evaluating, which comprises the following steps: collecting software texts, images and structured data, generating corresponding feature vectors, aligning through a cross-modal comparison algorithm, and constructing a multi-modal testing and evaluating data set; deep features of all modes are extracted through a mode exclusive encoder, and a unified multi-mode function vector is output based on information entropy dynamic weighted fusion; constructing triple training data, and optimizing the multi-modal large model by combining a joint loss function with an enhanced training strategy; and finally, deploying the model at a cloud end and an edge node, carrying out real-time triggering test by docking a CI / CD process, and realizing functional integrity verification, interactive compliance detection and accurate defect positioning through semantic vector comparison, graph isomorphism rate calculation and cross-modal attention backtracking. According to the scheme, the test comprehensiveness and precision are improved, and the rapid iteration requirement of software is met.

Systems / techniques that facilitate automatic product support systems and methods via generative artificial intelligence (GAI) and customer interactions are provided. In various embodiments, a system can access an electronic interaction record pertaining to a software product. In various aspects, the system can synthesize, via execution of GAI on the electronic interaction record, first text that describes a problem afflicting the software product. In various instances, the system can determine, based on executing the GAI on the first text, whether there is an available software feature in an available software feature repository that addresses or solves the problem. In various cases, the system can, in response to a determination that there is no available software feature that addresses or solves the problem, synthesize, via execution of the GAI on the first text, a recommended design alteration to the software product that would address or solve the problem.

The invention relates to a software function point extraction and element identification method and system, equipment and a medium. According to the method, the natural language processing capability of the large language model and the precise classification capability of the text classification model are combined, so that precise extraction and element recognition of function points in the software requirement document can be realized. And by introducing structured text segmentation, an object attribute cleaning strategy, a cue word optimization extraction scheme, a mechanism of secondary supplemental extraction of ILF function points and a correction optimization strategy based on a heuristic rule, the integrity and accuracy of function point extraction and recognition can be remarkably improved, the situation of mistaken extraction or omission is reduced, and the recognition efficiency is improved. And a solid data basis is provided for software scale automatic estimation.

An implementation may involve: receiving audio input that contains utterances; determining, by a speech-to-text engine that receives the audio input, a textual representation of the utterances; providing, to a natural language model, a request to determine an intent of the textual representation of the utterances, wherein the request indicates that the intent is to be selected from a plurality of predefined intents; receiving, from the natural language model, the intent; determining, based on the intent, an action; and based on the action, modifying operation of a software application.

The invention relates to the technical field of engineering cost, and discloses a data entry method for engineering cost software, which comprises the following steps of: S1, importing an engineering quantity list file in an Excel format through an interface of the engineering cost software, and automatically analyzing a data structure of the engineering quantity list file; s2, based on a preset intelligent matching algorithm, performing dynamic mapping on the Excel data field and a data field of a project cost software function module; s3, adopting a data type self-adaptive rule to automatically classify and convert numerical values, texts and compound data in the Excel; s4, based on a data association generation algorithm, automatically establishing a hierarchical relationship and a dependency relationship between the engineering quantity list items; s5, executing one-button data import, and writing the processed structured data into a project cost software database in batches; according to the method, high-precision automatic mapping of the Excel field and the software module is realized through an intelligent matching algorithm and a dynamic weight adjustment mechanism based on the feature vector similarity, the matching accuracy is greatly improved, and the manual correction frequency is greatly reduced.

The invention discloses an industrial software intelligent building system and method based on a plug-in mechanism, and relates to the technical field of industrial Internet of Things, and the method comprises the following steps: defining a standardized format and an interface of a plug-in, and ensuring the compatibility and the expandability of the plug-in; establishing a plug-in library, and analyzing and recording a dependency relationship between plug-ins; performing semantic similarity matching on the user demand and the plug-in function, and screening plug-ins in combination with a plug-in historical success rate to form a plug-in combination; conflict analysis is carried out on the plug-in combinations, CPU occupancy rate detection is carried out on feasible plug-in combinations based on the conflict analysis, and plug-in combinations with unqualified CPU occupancy rates are removed; and activating the plug-ins according to the plug-in combination selected by the user to complete software function implementation, and executing dynamic updating of the plug-ins.

Various systems and methods are presented regarding a threat analysis and risk assessment (TARA) system for implementation during design of a device, such as a software-defined vehicle. The system can be implemented across a manufacturing organization and combines knowledge from a range of entities, e.g., software programmers, hardware designers, network designers, and suchlike. Items and assets can be utilized to define respective features of components, e.g., defining software functionality, electronic control unit (ECU) configuration, a communication network connecting one or more ECUs and various signal inputs / outputs, etc. By representing components / features as items and assets, knowledge regarding potential / actual threats (e.g., cybersecurity attack(s)) can be respectively applied, damage scenarios and mitigation identified, threat risks assessed and reduced, with the whole system iteratively updated in response to newly derived configurations and knowledge regarding component of interest. Respective entities can apply their knowledge to supplement knowledge across the system, enabling interaction from multiple sources.

Various systems and methods are presented regarding a threat analysis and risk assessment (TARA) system for implementation during design of a device, such as a software-defined vehicle. The system can be implemented across a manufacturing organization and combines knowledge from a range of entities, e.g., software programmers, hardware designers, network designers, and suchlike. Items and assets can be utilized to define respective features of components, e.g., defining software functionality, electronic control unit (ECU) configuration, a communication network connecting one or more ECUs and various signal inputs / outputs, etc. By representing components / features as items and assets, knowledge regarding potential / actual threats (e.g., cybersecurity attack(s)) can be respectively applied, damage scenarios and mitigation identified, threat risks assessed and reduced, with the whole system iteratively updated in response to newly derived configurations and knowledge regarding component of interest. Respective entities can apply their knowledge to supplement knowledge across the system, enabling interaction from multiple sources.

Examples of the present disclosure describe systems and methods for providing a protection level-based mechanism for securing an AI model. In examples, a request to distribute an AI model to a client device is received. A license specifying at least one protection level for one or more portions of the AI model is identified at a licensing server. The hardware and / or software capabilities of the client device are evaluated to determine whether the client device is configured to support the protection level specified by the license for the AI model. If the client device is configured to support the protection level, the AI model is retrieved from an AI model distribution server and provided to the client device.

Various systems and methods are presented regarding a threat analysis and risk assessment (TARA) system for implementation during design of a device, such as a software-defined vehicle. The system can be implemented across a manufacturing organization and combines knowledge from a range of entities, e.g., software programmers, hardware designers, network designers, and suchlike. Items and assets can be utilized to define respective features of components, e.g., defining software functionality, electronic control unit (ECU) configuration, a communication network connecting one or more ECUs and various signal inputs / outputs, etc. By representing components / features as items and assets, knowledge regarding potential / actual threats (e.g., cybersecurity attack(s)) can be respectively applied, damage scenarios and mitigation identified, threat risks assessed and reduced, with the whole system iteratively updated in response to newly derived configurations and knowledge regarding component of interest. Respective entities can apply their knowledge to supplement knowledge across the system, enabling interaction from multiple sources.

The invention provides a software and hardware integrated intelligent terminal power transaction system and method, relates to the technical field of power market transaction, and solves the technical problems of data potential safety hazards and insufficient real-time performance caused by dependence on an external platform in a power transaction process in the prior art. The system specifically comprises a hardware architecture and a software function module, the hardware architecture comprises a processor, a redundant power supply, a storage device, a network interface, a security encryption chip and a display interface; the software function module comprises a core function layer, an interface layer and a security layer; wherein the core function layer is used for being responsible for processing and controlling the whole flow of power transaction; the interface layer is used for carrying out standardized and ordered external data interaction; and the security layer is used for guaranteeing the security of the terminal from multiple dimensions of communication, transaction, data and operation and maintenance. The method is used for electricity market transaction.

The invention provides a model-oriented health detection method, device and equipment and a storage medium, and the method comprises the steps: collecting a plurality of pieces of hardware index data representing hardware features and a plurality of pieces of software index data representing software features of a server; detecting whether an abnormal index exists or not based on the hardware index data and the software index data; if the abnormal index exists, calculating a health degree score according to the hardware index data and the software index data; and determining the health state of the server according to the health degree score. According to the technical scheme provided by the invention, the hardware index data and the software index data are quantified through the health degree score component, so that health detection can be accurately carried out, and a decision basis is provided for fault early warning and automatic repair.

Methods and systems for artificial intelligence (AI) assisted automation of testing of a software functionality related to a user intent on a software platform is provided. In one embodiment, the method includes receiving user action data indicating the user intent related to a software platform and generating a human-readable test scenario. The test scenario, which includes a sequence of human-readable testing steps and an expected outcome, is generated using a scenario machine learning (ML) model. The method includes generating an interpretable test script based on the test scenario using a script ML model. The test script is interpreted to implement testing steps on the software platform, generating a test outcome. A human-readable test report is also generated to evaluate the test scenario on the software platform, based on the test outcome and the expected outcome.

Methods are described for determining user operations at a data processing system. In one example, an agent is established at the data processing system that has access to data indicating, for each of multiple user space applications, an association between (i) a set of multiple calls by the user space application to one or more software functions and (ii) a specific operation of the user space application. A set of calls by a given user space application to one or more software functions is received by the agent. It is determined that the set of calls are characteristic of a specific operation of the given user space application by processing the set of calls based on the data. One or both of generating a report regarding the specific operation and influencing functioning of the given user space application are then performed.

The invention relates to a method for the automated specification of at least one test case (490) for testing software functions of a control unit, comprising the following steps - Creating (S10) a training data set (230), wherein the training data set (230) comprises software documentation, specifications, requirement documents, networking architectures and / or sensor measured values ​​and / or further data of at least one software function of a control unit to be tested; - Training (S20) an AI model (450) with the training data set (230); - entering (S30) first input data (250) for a test case specification and forwarding the first input data (250) to the trained AI model (450); - generating (S40) at least one test case (490) by the AI ​​model (450); - entering (S50) requirements in the form of second input data (270) for optimizing and improving the test case (490); - repeating (S60) the method steps (S40) and (S50) in one iteration until a target test case (495) is reached; - Outputting (S70) the target test case (495) and / or storing the target test case (495) in a database (300).

The embodiment of the invention provides a software function iteration method and device, and the method comprises the steps: building a hybrid model through a preset isolated forest model and a preset time sequence model, carrying out the anomaly detection of initial user behavior features, removing abnormal values, building a generator and discriminator frame, and carrying out the recognition of the abnormal values. Carrying out missing value filling on the user behavior characteristics according to the generative adversarial network, complementing missing values, cleaning the processed user behavior characteristics based on a preset clustering algorithm, constructing a multi-model pool, carrying out multi-modal fusion on the preprocessed user behavior characteristics, and carrying out multi-modal fusion on the preprocessed user behavior characteristics; combining the multi-modal fusion feature with a preset service label to determine a corresponding user behavior data set, performing frequent item mining on the user behavior data set based on a frequent item set mining algorithm, determining a corresponding software function use association rule, and performing software function iteration according to the software function use association rule to obtain a software function set; the efficiency and accuracy of software functions can be improved.

The invention relates to a test verification system and method for a reactor core neutron fluence rate measurement system. The test verification system comprises an upper computer software test verification unit, a lower computer software and hardware test verification unit and a communication verification unit, the upper computer software testing and verifying unit is used for testing and verifying functions of upper computer software; the lower computer software and hardware test verification unit is used for testing software functions, hardware functions and local functions of the lower computer; and the communication verification unit is used for testing a communication interface, a communication protocol and communication stability. According to the invention, a standard test scheme can be formed, complete evaluation of functions of the reactor core neutron fluence rate measurement system is realized, independent tests are carried out for communication, logic and software and hardware, and the requirement of rapid replacement of subsystems is met. And meanwhile, the fault point can be quickly positioned by disassembling and testing specific functions.

Various embodiments of the present disclosure include systems, methods, and / or apparatuses for executing an artificial intelligence (AI) framework. The system may be configured to: receive an initial software functionality definition data set; retrieve at least one configuration data set comprising predefined context data; generate, at least by at least one agent executing at least one generative AI model, one or more requirement data objects for a computer-generated executable software program product based on the initial software functionality definition data set; generate one or more code generation work prompt sets defining a list of computer-executable tasks configured to generate code for the computer-generated executable software program product; and / or build the code for the computer-generated executable software program product.

The invention discloses a vehicle body domain controller hardware-in-the-loop simulation method under an AUTOSAR architecture, and the main conception of the method is that based on the standardized interface definition of an AUTOSAR basic software layer, an HIL cabinet hardware channel standardized mapping relation library is established, and thus a hardware corresponding relation configuration file template is constructed; establishing a subsystem simulation model for each functional module and constructing a three-layer decoupling architecture in combination with different functional specifications to realize dynamic binding of test software and a hardware channel; then, based on an actual hardware interface and software function definition, a simulation test bench is built, and verification is completed; and finally, generating an automatic test case based on the function specification, and carrying out the function test of each subsystem of the vehicle body domain controller in the current test environment. According to the invention, the rack development period is obviously shortened, the flexibility and expandability of the test environment are improved, and the full-life-cycle test verification capability optimization is realized.

The invention discloses a computer software development data processing system based on big data, relates to the field of software development, and solves the problem that the computer software development data processing system is poor in application effect. Comprising a development data module used for obtaining the function resource occupancy rate and the function static complexity corresponding to each software function to obtain software development function data, and a resource investment module used for obtaining the fund investment degree corresponding to each software function to obtain fund investment data, the function concurrence module is used for obtaining function concurrence complexity corresponding to each software function to obtain function concurrence data, and the software deployment module is used for performing server selection and deployment on the computer software according to the software development function data, the fund investment data and the function concurrence data. According to the method, the scientificity and applicability of a computer software deployment result can be improved.

The invention relates to the field of big data, and discloses a data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of determining metadata information of target software in response to a personalized deployment requirement of a target object for the target software; the metadata information comprises multiple pieces of metadata sub-information; determining each piece of modifiable sub-information meeting modifiable conditions from each piece of metadata sub-information based on respective information characteristics of each piece of metadata sub-information; performing semantic analysis on the personalized deployment demand to determine personalized information expected by the target object and a personalized demand for the personalized information; target sub-information matched with the personalized information is determined from the modifiable sub-information; and modifying the target sub-information based on a personalized demand to obtain updated metadata information of the target software corresponding to the target object. By adopting the method, the software function stability can be improved.

The invention provides a multi-satellite cooperative task planning subsystem software componentization method based on a soft bus. The method comprises the following steps: setting a multi-task framework of task planning subsystem software componentization; setting a function module of task planning subsystem software; and setting an information flow between task planning subsystem software components. According to the method, the problems of complex star group task planning setting and excessive scheme iteration times are solved, functional data coupling is effectively reduced, and the stability of software and the high efficiency of troubleshooting are improved; the reliability and safety of normal operation of multi-satellite task planning software functions are improved, and the in-orbit service life of satellites is prolonged to a great extent; the task planning function is standardized and modularized, the requirements of iteration, on-orbit fault repair and the like of multi-satellite task planning software can be better met, and the reusability of the task planning software is greatly improved.

The application provides an intelligent parameterized UI generation system and method suitable for professional analysis software, receives UI requirements in the form of natural language or pictures through a user interaction layer, analyzes the requirements by an AI intelligent processing layer, and automatically generates an initial configuration file containing components, styles and logic in combination with a domain knowledge base and a reference style. A user can adjust and analyze the configuration file through a configuration editing and analyzing layer. A parameterized UI generation layer dynamically constructs UI components with tree hierarchical relationships based on the analyzed structured data, automatically configures interaction logic, data binding and professional field processing, realizes two-way synchronization of GUI and backend data, and finally outputs an interactive interface by a UI rendering layer. The application changes highly customized and fragmented UI development into an automated and standardized generation process, greatly improves development efficiency, guarantees the consistency of interface style and operation logic, significantly reduces maintenance cost, and enhances the flexibility of software function expansion.

Industrial machines can include internal or associated sensors, which can output one or more operational parameters of the industrial machine. Sensors can use a variety of communication protocols to output the machine data. A configurable, multi-protocol (CMP) device can include hardware and software functionality to interface with and communicate with a variety of sensors and their communication protocols. The CMP device can include a microcontroller, an interface selector, a connector with pinout, having connections. The microcontroller can include a variety of interfaces each dedicated to a communication protocol. The connections of the pinout can include channels. The interface selector can use a combination of relay positions to establish an electrical pathway between an interface of the microcontroller and one or more channels in the pinout.

The invention relates to the technical field of vehicles, in particular to a vehicle software function arrangement method and device, a vehicle and a storage medium, and the method comprises the steps: obtaining a script code of target vehicle software; analyzing the script code to obtain related data of an atomic component in the target vehicle software; and rearranging the atomic components of the target vehicle software based on the relevant data. Therefore, the problems that a software function changing method in an existing controller is complex, the updating speed is low, and the personalized requirement of a user cannot be met are solved.

The invention discloses a method and a system for upgrading software generated based on a low-code development tool and a medium. The method comprises the following steps of: adding an update content field and an update time field to a plurality of data tables for storing software function configuration metadata; based on the update time field, exporting configuration records changed after the first time point from a plurality of data tables; obtaining an upgrade configuration record file set which is provided by a software supplier and is related to version upgrade; comparing and combining the exported configuration record file with the upgrade configuration record file set to generate a combined target configuration record file set; and importing the target configuration record file set into a database of the target system in batches to complete software upgrading. According to the method, a new version released by a software developer and personalized modification of an old version by a user can be efficiently and accurately combined, smooth upgrading is realized, and high cost and error risks caused by manual comparison are avoided.

The invention relates to a software function point identification method fusing a large model and multiple clustering analysis, and solves the problems of subjective deviation, inconsistent naming and low auditing efficiency caused by function disassembly depending on artificial experience in traditional function point measurement and calculation. The method comprises the following steps: inputting a design scheme, and constructing a document level semantic tree; obtaining feature information described by corresponding function points in the semantic tree, and analyzing the feature information to determine candidate function points; fusing the candidate function points according to semantic tree hierarchy alignment; and carrying out differentiation processing on the candidate function points, and carrying out duplicate removal on the similarity frequency according to the candidate function points to obtain the function points. According to the method, based on construction and analysis of a document hierarchy semantic tree, feature positions and large model reasoning ability are combined, and accurate extraction and auditing of function points are achieved. And differentiation is formed by adopting multiple clustering, and a co-cooperation relation matrix is constructed through clustering cross validation, so that the function point de-duplication accuracy is greatly improved.

The application belongs to the technical field of networking communication, and proposes a component-based networking system and method based on scene arrangement, which is used for networking devices. The networking system comprises a plurality of components and a component management platform. The component is a software functional component running in the networking system, and is designed based on a subscription and publication mode and serves as a client in the subscription and publication mode. The component management platform comprises a message bus, a component management center and an arrangement management module. The message bus serves as a server in the subscription and publication mode. The component management center is used for processing the registration and discovery of the components. The arrangement management module is used for arranging the components based on a preset scene. The component initiates registration to the component management platform through an interface provided by the component management platform, and subscribes and publishes messages through the message bus. The application loosely couples software functions of special devices, facilitates the change or expansion of software functions, and provides scene-based device management and operation modes.