7 results about "Architectural pattern" patented technology

Systems and methods for generating system architecture representation by implementing machine learning (ML) techniques are disclosed. The system receives a request for generating system architecture representation from at least one user and generates an architecture summary for the received request. Further, the system determines an architecture pattern relevant to the received request based on a context of the generated architecture summary using the large language models and machine learning (ML) models. The system further generates an architecture code corresponding to the received request. The system validates the generated architecture code for determining errors in the generated architecture code based on compliance-based rules, legal-based rules, and security-based rules specific to an organization using the machine learning (ML) models. The system further generates the at least one system architecture representation based on successful validation and outputs the generated architecture code and the at least one system architecture representation on a user interface.

The present invention belongs to the technical field of combat systems and discloses a method for modeling a combat system architecture based on a hypernetwork model, including preprocessing the task nodes for constructing the hypernetwork model to obtain the corresponding relationship between the task nodes and the system nodes; constructing a task network according to the corresponding relationship between the task nodes and the system nodes; generalizing and representing the task nodes and the system nodes of the architecture pattern according to the design scheme of the architecture pattern to construct a hybrid structure of the hypernetwork; using the hypernetwork to construct a system network with the generalized and represented task nodes and system nodes; and combining the task network and the system network to construct a combat system architecture model. The present invention can construct a combat system architecture model with multiple architecture scheme selections, which is convenient for decision-makers to make the best choice; this method is of polynomial time, and its return value is significantly better than other benchmark algorithms, and it is optimal under the assumption of the independence of the combat system architecture scheme space.

The present application discloses a method for recognizing architectural patterns, which is based on multiple spatial proximity graph distances and architectural attribute features, and is used to identify architectural complexes with complex nonlinear spatial distribution patterns. The present application constructs three graph sequences to capture the spatial adjacent structures and non-spatial features of different feature views, and then obtains three improved graphs through a graph diffusion process, and fuses them into a joint graph shared by all views, which can depict the mutual relationships between them and produce the final clustering results. The recognition method of the present application uses two distance metrics, contour distance and centroid distance, to make full use of the complementary information of spatial structure and non-spatial attributes, and to determine architectural patterns by combining spatial proximity relationships and non-spatial similarities, providing technical support for aspects such as map making synthesis and urban scene semantic segmentation, and representing geographical reality as realistically as possible within the limitations of map scale.

This invention relates to the fields of software engineering and artificial intelligence, and particularly to an automated management system for the entire software development lifecycle, including a requirements analysis and architecture design module, a development and testing integration module, a deployment and operation monitoring module, and a visual management module. In the requirements phase, the invention performs semantic parsing of natural language requirements to generate structured documents, intelligently matches historical architecture patterns, and establishes a two-way traceability relationship. In the development and testing phase, it automatically generates code frameworks and test cases, performs incremental code review based on a defect prediction model, and automatically completes log cleaning, fault location, root cause analysis, and defect ticket closure when tests fail. In the deployment and operation phase, it intelligently generates canary release strategies, constructs a digital twin operation model, and enables multi-dimensional tracing and rapid handling of operational anomalies. This invention breaks down data barriers throughout the entire process with a unified digital mainline data layer, significantly improving software development and delivery efficiency and system operational stability.

A method is provided for developing a software product in a no-code development platform (NCDP) to address a problem related to a business domain. The method includes designing the software product in the NCDP. This includes receiving design instructions composed in a semi-structured grammar of a domain-driven design (DDD) natural language for the business domain, and generating a metamodel from the design instructions and according to the DDD natural language. The metamodel incorporates logic and data to implement software features, and the software product has an event sourcing architectural pattern in which the logic in the form of aggregate services are invoked by commands, and the data as events that describe changes in state of the software product are generated. The method includes automatically implementing the aggregate services, commands, and events to build the software product from the metamodel, using an event sourcing framework as a programming model.

The invention provides a specification driving code generation method and system based on intention understanding, and relates to the field of artificial intelligence, and the method comprises the steps: carrying out semantic analysis on a specification document by adopting a natural language processing technology to obtain a user intention, a system intention and a constraint intention, and constructing an intention hierarchy tree; traversing each node of the intention hierarchy tree, and extracting a standard fragment corresponding to the node from the standard document to establish a standard constraint set; establishing a mapping table between the standard constraint set and each node in the intention hierarchy tree; extracting an architecture feature vector from the intention hierarchy tree and the mapping table, and mapping the architecture feature vector to the recommendation of the architecture mode according to a predefined rule to generate a recommended architecture; and calling the large language model, generating a plurality of code implementation candidate schemes according to the recommendation architecture, the to-be-implemented nodes in the mapping table and the standard constraint set corresponding to the nodes, and selecting an optimal scheme from the candidate schemes. And the accuracy, the quality and the maintainability of the generated code are improved.

The application provides a specification-driven code generation method and system based on intention understanding, and relates to the field of artificial intelligence, which comprises the following steps: using natural language processing technology to perform semantic analysis on a specification document to obtain user intention, system intention and constraint intention and to construct an intention hierarchical tree; traversing each node of the intention hierarchical tree, extracting a specification fragment corresponding to the node from the specification document to establish a specification constraint set; establishing a mapping table between the specification constraint set and each node in the intention hierarchical tree; extracting an architecture feature vector from the intention hierarchical tree and the mapping table, and mapping the architecture feature vector to a recommended architecture mode according to a predefined rule to generate a recommended architecture; calling a large language model, and generating multiple candidate schemes of code implementation according to the recommended architecture, the nodes to be implemented in the mapping table and the specification constraint set corresponding to the nodes to select an optimal scheme from the multiple candidate schemes. The accuracy, quality and maintainability of the generated code are improved.