20 results about "SOLID" patented technology

The invention relates to a software testing method and device, computer equipment, a readable storage medium and a program product. The method comprises the steps of obtaining a deep learning model based on a multi-stage training strategy, wherein the deep learning model is used for performing mapping test on a source code file and a demand design document; obtaining a multi-task model based on the deep learning model, wherein the multi-task model is used for performing a mapping test on the demand design document and the test document; based on a relation extraction model, optimizing the test document; the optimization at least comprises enhancement of semantic association between entities. By adopting the method, the software testing quality can be improved.

The invention discloses an application software architecture for encapsulating a task management and synchronization mechanism of an operating system, and belongs to the technical field of industrial real-time control. According to the architecture, an operating system task management and synchronization mechanism is modularly packaged into three types of objects: an employee type for packaging specific business execution logic; the pipeline class is used for packaging inter-task communication and synchronization functions; and the behavior class is used for packaging an operating system task entity and is responsible for scheduling employee objects contained in the behavior class to be executed orderly. The three types of objects are created, assembled and started through a factory mode according to configuration information to form a complete real-time task system. According to the method, through object-oriented packaging and configuration assembly, the problems of tight task coupling and difficult code maintenance in traditional process-oriented programming are solved, loose coupling and high cohesion among task modules are realized, the configurability, maintainability and expandability of industrial real-time software are remarkably improved, and the method is suitable for various real-time operating system environments.

This invention discloses a rapid interactive and verification method for mold structures based on wireframe preview, applied to a computer-aided design system. The method includes: receiving and loading a parametric 3D structural model of the target mold; parsing the 3D structural model, extracting and registering the driving design parameters, and generating a parameter registry; constructing and displaying a lightweight wireframe preview model representing the structural outline based on the parameter values ​​in the parameter registry; adjusting the design parameters, updating the parameter values ​​in the parameter registry in real time, and driving the wireframe preview model to update synchronously; after confirming that the updated wireframe preview model meets the design intent, driving the computer-aided design system to generate the final 3D solid structure based on the final parameter registry. This invention significantly improves the efficiency of mold structure design by providing real-time preview and rapid adjustment interaction during the design process.

The invention relates to a Python-based reflector design optimization method and system and a medium. The method comprises the following steps: determining the shape and the material of the reflector; a reinforcing rib, a supporting hole and an outer edge frame of the reflector are drawn through UG software to complete design of a sketch parameterization template of the reflector; according to the sketch parameterization template of the reflector, performing parameterization characteristic curve stretching, entity merging and entity trimming operation to obtain a reflector back structure parameterization model; performing mirror parametric modeling to obtain a mirror parametric model; obtaining settable parameters of the reflector to form a settable parameter set; the reflector structure is updated by modifying parameters in the parameter set, and design optimization of the reflector structure is carried out. According to the invention, the design iteration period is shortened, the design efficiency is improved, the research and development cost of the reflector is reduced, the probability of model errors or update failures is greatly reduced, the design space is easy to fully explore, and the design effect of the reflector is improved.

The application relates to an artificial intelligence-based software design scheme automatic evaluation method and system, which automatically extracts function entities and architecture topologies in a design document through a multi-modal analysis technology to generate a structured design scheme atlas; performs standardized compliance checking based on an enterprise architecture benchmark library to identify technical specification deviation and component reuse defects; fuses a defect prediction model and a risk quantification mechanism to analyze component coupling degree and historical defect data to generate a risk atlas; combines constraint rules and a similar case library to deduce an executable architecture optimization path; finally, constructs a closed-loop decision chain of technical compliance, risk control and asset reuse to generate a quantitative evaluation report. The application solves the problems of traditional evaluation methods, such as dependence on manual work, low efficiency, non-uniform standards and decision disconnection, realizes full-process automatic evaluation from design analysis to improvement guidance, significantly improves evaluation efficiency and decision accuracy, and guides software architecture optimization decision.

The invention discloses a traceable graph construction method based on human-multi-agent collaborative software development, and relates to the technical field of software engineering, and the method specifically comprises the steps: defining a traceable graph framework used for representing the full life cycle of software development; collecting events generated by multiple agents and manual developers in the full life cycle of software development, and normalizing the events into a preset event model; analyzing the preset event model, and creating and updating a corresponding node in the traceable atlas; identifying an evolution relationship of a code entity of software development through static analysis on the basis of a scene, and adjusting the consistency of a tracing relationship between nodes and edges in the traceable atlas on the basis of an identification result; a structured graph query interface and a natural language query interface are provided through the traceable atlas, the problem that event semantics between heterogeneous systems are inconsistent can be solved, an enhanced updating mechanism is provided to guarantee real-time performance and accuracy of the atlas, and the risk of information lag is reduced.

A first instance is caused to execute software code to perform a first portion of a workflow in response to receipt of a workflow request, and performance of the first portion results in submission of an operation request to an entity. A resume workflow request is received from the entity, where the resume workflow request includes a handle to a snapshot that corresponds to a state of execution of the software code and a response to the operation request to the entity. Using the handle to the snapshot and the response to the operation request, a second instance is caused to execute the software code from the first state to perform a second portion of the workflow. A workflow result is received from an instance that executes a last portion of the workflow, and the workflow is provided result in response to the workflow request.

This invention discloses a deep learning-based intelligent text proofreading method and system, belonging to the field of intelligent proofreading technology. The method includes acquiring a preprocessed text sequence and spatial distribution coordinates, extracting semantic vectors and knowledge vectors, constructing a spatial topology graph to extract spatial vectors, generating a feature matrix, using a supervised contrastive learning strategy to obtain optimized error detection and correction parameters, loading the error detection and correction parameters into the sequence error detection model and semantic correction model respectively, outputting the error detection distribution and correction distribution, comparing entity features with a global memory database to output a consistency score, and weightedly fusing the error detection distribution, correction distribution, and consistency score to determine the proofreading result. This invention integrates spatial layout awareness, domain knowledge graph enhancement, and cross-paragraph global consistency verification into a dual-path architecture, solving problems such as typesetting interference, lack of professional background, and logical conflicts, achieving accurate differentiation of confusing characters, and ensuring the logical rigor of document content.

The invention discloses an intelligent inverse software programming method based on a large model. The method comprises the steps that standardized analysis is conducted on input multi-language project codes, code entities, static relations and metadata are extracted, a standardized intermediate representation (IR) is generated, semantic analysis is conducted on the code entities through a large model to recognize service function attributes, a function calling graph and semantic indexes are constructed, and a function-code mapping table is generated; performing code extraction according to a hierarchical extraction strategy in combination with large model aided decision making; and calling a target language compiler to execute static grammar check and reference relationship verification, performing dependency missing tracing and correction in combination with the large model until the code passes verification, generating a differentiated code package, and outputting a reverse engineering processing result. According to the method, in a development scene, the code review and reconstruction period can be shortened; in a teaching scene, removal of functional modules on demand is supported to design programming exercises, and the logic complementation ability and the system understanding depth of a learner are improved.

This invention discloses a method and system for controlling the visibility of programming language scopes. The method includes: during the execution of program code, when an execution operation on a program entity is detected, determining the target scope chain corresponding to the program entity based on the entity type; searching for the program entity level by level from the current scope of the program code to the last-level scope of the target scope chain until the program entity is found, thus determining the target scope where the program entity resides; and calling the program entity from the namespace corresponding to the target scope. This solves the problems of low code maintainability and poor code security. By setting more refined and hierarchical scopes and binding scopes, namespaces, and display modifiers, the lookup rules and access boundaries of variables and functions are fundamentally reconstructed, thereby improving code maintainability and security.

The invention provides a semantic modeling-based software demand automatic identification and conversion method and system, and relates to the technical field of software development, and the method comprises the following steps: obtaining a multi-version demand document, and constructing a time sequence semantic representation; deducing a dependency relationship between demand entities and resolving conflicts, and constructing a dependency relationship graph; software components are generated for the demand entities, semantic verification is executed, and root causes are positioned and repaired; establishing a component interaction relationship to form a software architecture; the timing consistency is verified and the dependency inference rule is optimized. According to the method, demand evolution can be automatically tracked, dependency conflicts can be identified, accurate conversion from demands to software architecture is realized, and the software development efficiency and quality are improved.

The invention relates to the technical field of software and artificial intelligence, in particular to a software development method based on natural language orchestration, which comprises the following steps of: S1, in response to a natural language demand, identifying a business entity and an action, mapping the entity into a library of a colored Pearl network, defining a color set, mapping the action into transition, and establishing a color set; constructing an incidence matrix according to the input consumption and the output of the Tokenn; and S2, iteratively constructing a branch process based on the incidence matrix, calculating a state identifier of a local configuration of a new event, and marking a cut-off event when the state identifier is repeated with a historical event so as to generate an acyclic finite complete prefix structure. According to the method, verification and supervision control synthesis are carried out through the Pearl network, and then a mathematical-level anti-deadlock section is automatically woven into a business code, so that the problems that traditional generative development mostly depends on direct generation and concurrency control of a large model, the model lacks global logical reasoning ability, and the development efficiency is low are solved. And therefore, the problem of frequent random deadlock of software in a high-concurrency environment is solved.

The invention discloses a RESTful API intelligent application method based on a large language model, and the method comprises the following steps: automatically extracting API endpoints, parameter entities and response code information from an OpenAPI standard document, a source code annotation, HAR flow data, a WITSML standard data stream of a petroleum drilling geological design system, and an SDK document of Landmark and Schlumberger platforms through employing a BERT series model in combination with a rule template; the method comprises the following steps of: vectorizing a natural language instruction input by a user through a Sension-BERT model; calculating a comprehensive score based on three dimensions of cosine similarity of a query vector and an API description vector, a Jaccard similarity coefficient of a parameter set and a historical calling frequency; an API calling request is constructed and executed, a dynamic timeout threshold value based on a historical response time P95 quantile is set, and a backspacing strategy related to the field is configured for a key API. According to the method, end-to-end intelligent API calling is realized, multidisciplinary data islands such as geology and engineering are effectively broken through, and the automation level and service continuity of complex system integration are remarkably improved.

The invention relates to the technical field of die design, and discloses a stamping die three-dimensional entity part feature rapid editing design method, which comprises the following steps: S1) selecting an entity target surface as a selection surface through an interactive interface, and querying attributes of the selection surface; s2) judging the feature type of the selection surface in the step S1); the rapid editing and designing method for the three-dimensional entity part features of the stamping die has the advantages that the time for designing and modifying the entity features of the die is shortened, repeated labor is reduced, and the design efficiency of the die is improved.

The invention discloses a cross-normal-form automatic conversion method and system for parameterized geometric modeling scripts and a medium, and provides a conversion architecture based on double-layer abstract syntax tree (AST) mapping and state stack management for a semantic gap between an implicit structure entity geometry (CSG) description language (such as OpenSCAD) and an explicit boundary representation (B-rep) programming language (such as CadQuery / Python). Deducing logic from an implicit functional list in the source script by adopting a recursive structure mapping mechanism, decoupling and reconstructing into an explicit implicit circulating control flow in a target language; a statement container stack is used for solving the isolation and recombination problems of hierarchical action domains; and identifying a specific geometric combination (such as Minkowski and cubes and spheres in operation) through semantic analysis, and reconstructing the specific geometric combination into efficient function call based on feature modeling (such as chamfer). According to the method, the parameterization design intention of the original script is reserved, and the calculation efficiency of the generative model in the B-rep kernel is remarkably improved.

The application provides a software requirement automatic recognition and conversion method and system based on semantic modeling, relates to the technical field of software development, and comprises the following steps: obtaining multiple versions of requirement documents and constructing a time sequence semantic representation; inferring a dependency relationship between requirement entities and resolving conflicts to construct a dependency relationship graph; generating software components for the requirement entities and performing semantic verification, locating a root cause and repairing; establishing a component interaction relationship to form a software architecture; and verifying time sequence consistency and optimizing dependency inference rules. The application can automatically track requirement evolution, recognize dependency conflicts, realize accurate conversion from requirements to a software architecture, and improve software development efficiency and quality.

This invention discloses a method and system for modeling discrete manufacturing workshops based on a hierarchical fusion of Petri nets and static knowledge graphs. By constructing a hierarchical structure that integrates time-varying and logical Petri nets, the upper layer models workshop-level resource flow, while the lower layer characterizes equipment-level state transitions, achieving a dynamic formal description of the concurrency, asynchronicity, and dependencies of the manufacturing system. Simultaneously, a specialized workshop knowledge graph is constructed, and a joint extraction model combining a RoBERTa-BiLSTM-CRF model and a focus loss function is employed to automatically extract entities and relationships from unstructured text, effectively improving knowledge construction efficiency and robustness. By defining a dual fusion mechanism of modeling and knowledge, deep coupling and collaborative reasoning between dynamic Petri nets and static knowledge graphs are achieved. This method supports multi-level modeling from system to equipment, simultaneously describing production logic, resource states, and process knowledge. Through continuous learning, the model can continuously accumulate and solidify production knowledge, ensuring long-term collaborative reliability.

The application belongs to the technical field of software development, and particularly relates to a software development system and a software development method. The BERT-base-based semantic understanding model can accurately extract function parameters, performance indexes and constraint conditions in natural language requirements, a three-layer verification mechanism of a technical entity design rule set is combined to ensure requirement compliance and integrity, priority calculation of the analytic hierarchy process makes development resources focus on core requirements, greatly reduces requirement deviation rate, through requirement hierarchical decomposition and intelligent matching of a component template library, combined with deep optimization of a technical entity design model, including design pattern adaptation, interface standardization and performance strategy customization, the generated core function components, auxiliary function components and interface components not only meet individualized requirements, but also meet performance requirements, and component reuse rate and development efficiency are significantly improved.