Demand modeling and management method and system supporting multi-level demand tracing and baseline management

Abstract

The invention discloses a demand modeling and management method and system supporting multi-level demand tracing and baseline management. The method comprises the following steps: constructing a demand information architecture comprising a tree hierarchical structure, a demand type definition and an association relationship definition; generating and storing demand entries in a unified format by integrating a demand import interface based on an attention mechanism deep learning model; dynamically updating a state mark of the associated entry based on the association relationship, wherein a user can instruct to create a demand baseline; serializing the demand set and calculating a hash value, and generating a non-tampering baseline snapshot; a demand consistency report is finally generated by constructing a demand traceability graph, utilizing a graph traversal algorithm and adopting an innovative mathematical model combining time distribution and associated weight to quantitatively calculate a change influence index. According to the invention, automation, intelligentization and quantitative analysis of the whole life cycle of demand management are realized, and the consistency maintenance, change control and tracing analysis efficiency of demands are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of computer systems engineering, and in particular relates to a requirement modeling and management method and system that supports multi-level requirement traceability and baseline management. Background Technology

[0002] With the increasing complexity of modern software and systems engineering, requirements management has become a critical element in ensuring project success. Requirements are not only numerous and diverse in origin, but also constantly changing. Effectively tracking the sources of requirements, managing requirement changes, and maintaining consistency between requirements and design, testing, and other work products has long been a serious challenge for the industry. Traditional requirements management often relies on documents or simple tools (such as Excel and Word), lacking a systematic and structured management framework. This leads to prominent problems such as isolated requirement information, difficulty in assessing the impact of changes, and low traceability efficiency.

[0003] Requirements traceability is widely regarded as a crucial indicator of system quality, its core being the establishment and maintenance of logical connections between requirements and between requirements and downstream work products. Research shows that the quality and effectiveness of traceability practices vary significantly, and its successful implementation is intricately influenced by environmental, organizational, and technological factors. Despite its universally acknowledged importance, traceability, especially before requirements specification (pre-RS), is often neglected in practice, which is the root cause of most traceability problems. Many organizations attempt to implement traceability but struggle with the lack of efficient modeling frameworks and tools to handle the complex networks of relationships in large-scale projects.

[0004] Establishing a requirements baseline is a widely accepted best practice for managing requirement changes and controlling project scope. A baseline represents a set of agreed-upon requirements within a specific version, providing a stable reference point for development work. However, traditional baseline management often faces several pain points: the baseline creation process is cumbersome and error-prone; baseline content lacks tamper-proofing, casting doubt on its authority; and more importantly, when baseline requirements change, it is difficult to quickly and accurately analyze the scope of the change's impact, thus failing to provide a quantitative basis for change decisions. This often leads to project scope creep, schedule delays, and cost overruns.

[0005] Existing methods and tools (such as IBM DOORS) attempt to address these issues, but they often have limitations. They are either too heavyweight and expensive, or they are insufficient in automating traceability (such as intelligently parsing requirement text), quantifying the impact of changes, and migrating data across platforms. Many empirical studies indicate that a significant gap remains between current support methods and users' actual needs.

[0006] Therefore, there is an urgent need in this field for an integrated solution that can support multi-level, structured modeling of requirements from the underlying architecture, realize automated processing and intelligent parsing of requirements data, and provide powerful baseline management and quantitative traceability analysis capabilities, thereby systematically improving the efficiency, accuracy and consistency of requirements management. Summary of the Invention

[0007] To address the shortcomings of the existing technology, this invention provides a requirement modeling and management method that supports multi-level requirement traceability and baseline management, comprising the following steps: Step S101: Based on the preset engineering specifications, construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions; Step S103: Receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture to generate requirement entries with a unified format and unique identifier. Step S105: Based on the aforementioned relationships, construct a requirement traceability graph with requirement items as nodes and relationships as edges; Step S107: Using a graph traversal algorithm, generate a demand traceability chain in both forward and backward dimensions; Step S109: Based on the traceability chain, a preset mathematical model of the impact of demand change is used to quantify the scope and degree of the impact of the change, and a demand consistency report is automatically generated.

[0008] The requirement information architecture in step S101 includes requirement hierarchy definitions for defining requirement levels, requirement type definitions for classifying requirement properties, and requirement relationship definitions for describing logical dependencies between requirements.

[0009] Wherein, after step S103, the method includes: providing a requirement editing interface to respond to the user's editing operation on the requirement item; The method further includes: when any requirement item changes, automatically triggering the status flag update logic of the associated requirement item based on the association relationship, wherein the status flag includes the status of pending review, baselined, and changing.

[0010] The method further includes: in response to the user's baseline creation instruction, extracting the target requirement item set and all its associated items from the requirement database, and performing version consistency verification.

[0011] After the verification is passed, the set of requirement items and their associations are serialized, and their cryptographic hash values ​​are calculated to generate an unmodifiable requirement baseline snapshot and store it.

[0012] The method further includes: real-time monitoring of change requests for baselined requirement items.

[0013] The calculation formula for the demand change impact index mathematical model in step S109 is as follows: Where I represents the demand change impact index, a dimensionless quantitative value; t represents the time variable, with t0 to t1 being the time window for assessing the change impact; n represents the total number of affected related demand items identified through the traceability chain; C represents the demand change propagation function, whose input is the change content and output is the change intensity; R i The weight coefficient of the i-th associated requirement item is determined by the requirement type (function, performance, interface) and its depth in the hierarchical structure. The parameters σ and μ are obtained through statistical analysis of historical change data. Specifically, the method is as follows: collect complete impact time series data of N historical requirement changes, perform Gaussian fitting on the impact diffusion curve of each change, and take the mean of all fitting results as μ and the standard deviation as σ. π represents pi and e represents the natural constant.

[0014] This formula utilizes the output (n, R) of the traceability chain. i As the core input, it enables quantitative simulation of the impact of changes in both the time and logical dimensions.

[0015] The method further includes: using a data migration interface, converting and encapsulating the requirement entries, baseline snapshots, and change history in the requirement database according to the standardized ReqIF format to generate a migrateable data package, thereby achieving lossless data exchange with a heterogeneous requirement management platform.

[0016] This invention also proposes a requirement modeling and management system that supports multi-level requirement traceability and baseline management, including: The requirement information architecture management module is used to construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions based on preset engineering specifications. The intelligent requirement import module is used to receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture, generating requirement entries with a unified format and unique identifier. The traceability graph construction module is used to construct a demand traceability graph with demand items as nodes and relationship as edges based on the association. The graph traversal module is used to generate a demand traceability chain in both forward and backward dimensions using graph traversal algorithms. The report generation module is used to quantify the scope and extent of the impact of changes based on the traceability chain using a preset mathematical model of the impact index of demand changes, and automatically generate a demand consistency report.

[0017] Compared with the prior art, the present invention has the following advantages: This invention enhances the automation and intelligence of requirement management. By introducing a deep learning model based on an attention mechanism to automatically segment and extract key information from requirement text, it overcomes the inefficiencies and errors of traditional manual requirement input and parsing. It achieves automated and high-precision conversion of requirement items from raw data to structured data, significantly reducing manual intervention and improving the efficiency and accuracy of requirement import and initial modeling.

[0018] This enhances the authority and reliability of the requirements baseline. By using serialization combined with cryptographic hash verification techniques to generate an immutable baseline snapshot, the integrity and immutability of the requirements baseline content are ensured. Any tampering with the baseline can be easily detected, making it a truly reliable and stable reference during project development and providing a solid foundation for project management.

[0019] This invention achieves precise and quantitative assessment of the impact of changes. Its most outstanding feature lies in its powerful requirements tracing and quantitative analysis capabilities. By constructing a requirements tracing graph and applying a graph traversal algorithm, the complete propagation path of requirements changes can be clearly and intuitively displayed. Furthermore, it innovatively introduces a mathematical model for the impact index of requirements changes, elevating the degree of change impact from traditional qualitative description to precise quantitative calculation. This enables project managers and architects to quantitatively assess the potential costs and risks of each change, thereby making more scientific and rational decisions and effectively controlling project scope creep.

[0020] This ensured consistency of requirements and project quality. A dynamic status marker update mechanism and a complete lifecycle change history ensured consistent linkage between different workpieces such as requirements, design, and testing. The systematic traceability framework ensured the integrity and consistency of the "requirements-design-implementation-verification" chain, greatly reducing the defect rate caused by misunderstandings, omissions, or inconsistencies in requirements, fundamentally improving the quality of the final product.

[0021] It improved team collaboration and communication efficiency. The structured requirements information architecture and clear status views (such as pending review, baselined, and under change) enabled all project stakeholders to have a unified and transparent understanding of the current status and historical evolution of the requirements. This greatly improved communication efficiency between different roles (such as business analysts, developers, and testers) and reduced duplication of work and rework caused by information asymmetry.

[0022] The system's interoperability and adaptability have been enhanced. By supporting data migration in the standard ReqIF format, the problem of data silos between different requirement management platforms has been solved, enabling lossless exchange and long-term reuse of requirement assets. Furthermore, the requirement information architecture and weighting coefficients (such as Ri) can be customized according to specific project characteristics, giving the methodology and system good adaptability and scalability, capable of meeting the needs of projects of different sizes and application domains. Attached Figure Description

[0023] The above and other objects, features, and advantages of exemplary embodiments of the present disclosure will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the present disclosure are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein: Figure 1 This is a flowchart illustrating a requirement modeling and management method that supports multi-level requirement traceability and baseline management according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0025] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0026] It should be understood that although the terms first, second, third, etc., may be used to describe... in the embodiments of the present invention, these... should not be limited to these terms. These terms are only used to distinguish... For example, first... may also be referred to as second... without departing from the scope of the embodiments of the present invention, and similarly, second... may also be referred to as first...

[0027] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0028] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0029] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0030] The optional embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] Example 1 like Figure 1 As shown, this invention discloses a requirement modeling and management method that supports multi-level requirement traceability and baseline management, including the following steps: Step S101: Based on the preset engineering specifications, construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions; Step S103: Receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture to generate requirement entries with a unified format and unique identifier. Step S105: Based on the aforementioned relationships, construct a requirement traceability graph with requirement items as nodes and relationships as edges; Step S107: Using a graph traversal algorithm, generate a demand traceability chain in both forward and backward dimensions; Step S109: Based on the traceability chain, a preset mathematical model of the impact of demand change is used to quantify the scope and degree of the impact of the change, and a demand consistency report is automatically generated.

[0032] In this invention, the demand information architecture includes the following three core elements: Requirement hierarchy definition: Define the tree-like hierarchical structure of requirements from top-level business requirements to bottom-level technical requirements; Requirement type definition: Classify requirements into types such as functional requirements, performance requirements, and interface requirements; Definition of demand relationships: Define the logical relationships between demands, including relationships such as inclusion, derivation, satisfaction, and tracing.

[0033] In step S105, the Requirements Traceability Diagram is a tool used to visualize requirements and their relationships with other model elements. It uses nodes and edges to represent requirement items and their relationships. Nodes represent requirement items, while edges represent the relationships between these requirement items, such as "satisfy," "refine," "verify," and "trace."

[0034] In requirements management, there may be various relationships between requirements, such as: Containment: One requirement is contained within another requirement.

[0035] Derivation: A requirement is derived from another requirement.

[0036] Satisfy: A requirement is satisfied by another requirement through other elements or designs.

[0037] Trace: A relationship exists between a requirement and another model element (such as a design, test case, etc.), used to trace the implementation and verification of the requirement.

[0038] Based on the requirement relationships defined in S1, the steps to construct a requirement traceability diagram are as follows: Identify requirement items: Treat each requirement item as a node, representing an independent unit of requirement.

[0039] Define relationships: Define edges between nodes based on the relationships between requirements (such as "satisfy", "trace", "refine" etc.).

[0040] Drawing diagrams: Use graphics tools (such as requirements diagrams, matrices, or software tools) to draw nodes and edges to form a requirements traceability diagram.

[0041] Requirements traceability diagrams play an important role in requirements management.

[0042] Requirements tracking and verification: Traceability diagrams can be used to track the progress of requirements from definition to implementation and testing, ensuring the integrity and consistency of requirements.

[0043] Change management: When requirements change, the impact of the change can be analyzed through traceability diagrams to ensure the rationality and controllability of the change.

[0044] Visualization and Communication: Graphical methods help team members understand and communicate the relationships between needs, improving collaboration efficiency.

[0045] In this invention, various tools and methods can be used to support the construction and management of demand traceability graphs: Requirement Diagram: Requirement diagrams are drawn using modeling languages ​​such as SysML, supporting the representation of relationships between requirements and model elements.

[0046] Requirements management tools, such as PingCode and Worktile, provide requirements management functions and support requirements tracking, change management, and traceability analysis.

[0047] Automation tools, such as MATLAB and Modelook, support the automatic generation and visualization of demand traceability diagrams.

[0048] Constructing a requirement traceability graph based on the requirement relationships defined in S1, with requirement items as nodes and relationships as edges, is an effective requirement management method. This graphical representation clearly shows the relationships between requirements, supporting requirement tracking, verification, and change management. In practical applications, combining it with appropriate tools and methods can improve the efficiency and effectiveness of requirement management.

[0049] In step S107, graph traversal algorithms are algorithms used in computer science to access all nodes in a graph, mainly including depth-first search (DFS) and breadth-first search (BFS). These algorithms can access and process all elements in the graph by traversing the nodes and edges. In graph traversal, the order of node access and the choice of path determine the traversal order and result.

[0050] In a requirements traceability chain, requirements are typically represented as a graph, where nodes represent requirements, components, or work products, and edges represent the relationships between them. Requirements traceability chains generally operate in two directions: forward traceability and backward traceability. Forward traceability starts with the requirement and traces it to a specific component or implementation, answering the question "Which component?"; backward traceability starts with the requirement and traces it to its source or origin, answering the question "Which source?". These two directions of traceability help ensure the integrity and consistency of requirements throughout the development process.

[0051] Graph traversal algorithms can be used to generate demand traceability chains. For example, Depth-First Search (DFS) visits nodes in a graph in a specific order, generating a traceability chain from high to low levels; while Breadth-First Search (BFS) visits nodes in a hierarchical order, generating a traceability chain from low to high levels. Graph traversal algorithms can systematically traverse all nodes and edges in a graph, thus generating a complete traceability chain.

[0052] Graph traversal algorithms provide theoretical and technical support for generating demand traceability chains. Through graph traversal algorithms, nodes and edges in a graph can be systematically traversed, thereby generating demand traceability chains in both forward (higher levels to lower levels) and backward (lower levels to higher levels) dimensions.

[0053] In step S109, requirements traceability is fundamental to understanding the impact of changes. It connects models, tests, and code to requirements by creating a digital chain to help understand the impact of changes and reduce waste throughout the design lifecycle. Requirements traceability supports industry standards not only in automotive, aerospace, railroad, and healthcare, but also common software development standards such as CMMI and ASPICE. Furthermore, the development of requirements traceability tools and methods, such as reference model-based traceability methods, helps organizations achieve requirements management across software development projects of varying scales and complexities.

[0054] In this invention, assessing the impact of requirement changes typically involves multiple steps, including identifying affected requirements, options, and design decisions, as well as determining affected system model elements. Furthermore, based on the relationships and semantics of SysML (System Modeling Language), change impact rules can be defined to guide the change process and ensure model-domain synchronization.

[0055] Based on the above method, a pre-defined mathematical model of the impact index of demand changes can be used to quantify the scope and extent of the impact of changes and automatically generate a demand consistency report.

[0056] Example 2 This invention proposes a requirement modeling and management method that supports multi-level requirement traceability and baseline management, comprising the following steps: Step S101: Based on the preset engineering specifications, construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions; Step S103: Receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture to generate requirement entries with a unified format and unique identifier. Step S105: Based on the aforementioned relationships, construct a requirement traceability graph with requirement items as nodes and relationships as edges; Step S107: Using a graph traversal algorithm, generate a demand traceability chain in both forward and backward dimensions; Step S109: Based on the traceability chain, a preset mathematical model of the impact of demand change is used to quantify the scope and degree of the impact of the change, and a demand consistency report is automatically generated.

[0057] The requirement information architecture in step S101 includes requirement hierarchy definitions for defining requirement levels, requirement type definitions for classifying requirement properties, and requirement relationship definitions for describing logical dependencies between requirements.

[0058] A requirement hierarchy definition describes the hierarchical structure of requirements, that is, how requirements are refined from high to low levels. For example, requirements can be divided into top-level requirements, business requirements, system requirements, etc. This hierarchical structure helps to understand how requirements are organized and the relationships between different levels of requirements. For example, top-level requirements may involve the company's strategic goals, while system requirements focus on specific technical implementations. Furthermore, requirement hierarchies can also be organized and represented using requirement models and requirement hierarchies.

[0059] Requirements type definitions are used to categorize requirements to distinguish between different types of requirements. For example, requirements can be divided into functional requirements, non-functional requirements, availability requirements, performance requirements, etc. This categorization helps to better understand and manage the nature and priority of requirements. For instance, functional requirements describe the functions that the system should perform, while non-functional requirements focus on the system's performance, reliability, maintainability, etc.

[0060] Requirement relationship definitions describe the logical dependencies between requirements, such as their dependence, influence, and interaction. For example, the implementation of one functional requirement may depend on the completion of another functional requirement. These relationships can be represented using tools such as requirement matrices, requirement diagrams, or requirement relationship diagrams. Furthermore, relationships between requirements can also be modeled using concepts such as requirement definition, requirement usage, and constraint definition.

[0061] The requirement hierarchy definition provides a description of the classification and organization of requirement levels.

[0062] The definition of requirement types provides a discussion of requirement classification and classification methods.

[0063] The requirement relationship definition provides a description of requirement relationships and requirement models.

[0064] The aforementioned requirements information architecture provides a systematic framework for the organization, classification, and management of requirements through the definition of requirements hierarchy, requirements type, and requirements relationships. This architecture helps improve the efficiency and accuracy of requirements management and supports requirements analysis, prioritization, and change management.

[0065] After step S103, the method includes: providing a requirement editing interface to respond to user editing operations on requirement items.

[0066] Multiple pieces of evidence demonstrate the interfaces used for editing requirements in different systems or tools, which typically allow users to create, modify, view, and manage requirement entries.

[0067] Users can edit requirement items through the interface, including: The edit button and operation process allow users to enter the editing page by clicking the "Edit" button and modify the content (such as basic information, description, status, etc.).

[0068] Editing methods: Some interfaces support editing via tables, text boxes, buttons, etc., such as editing by clicking on a cell.

[0069] After editing, users can usually save their changes using buttons such as "Save", "Update", and "OK".

[0070] Version control and history: Some systems support required version management, record editing history, and support rolling back or viewing historical versions.

[0071] Document editors and plugins: Some systems support online editing and export of required documents by integrating document editors (such as Word and PageOffice).

[0072] Database and file management: Required entries are typically stored in a database, supporting fast retrieval and retrieval.

[0073] Collaborative editing and integration: Some tools support collaborative editing by multiple users and integration with other systems (such as Jira and Git).

[0074] Interface layout: The interface typically includes a navigation bar, operation buttons, input boxes, tables, etc., which support users to perform editing operations intuitively.

[0075] Responsive design, with some interfaces supporting responsive layouts to adapt to different devices and screen sizes.

[0076] The method further includes: when any requirement item changes, automatically triggering the status flag update logic of the associated requirement item based on the association relationship, wherein the status flag includes the status of pending review, baselined, and changing.

[0077] When a requirement item changes, the system automatically triggers a status update for related requirement items based on predefined relationships (such as those defined in S1). These status updates include status markers such as "Pending Review," "Based On," and "Under Change." These status markers help track the lifecycle of requirement changes, ensuring transparency and traceability in the change process.

[0078] In software engineering, requirement change management is a crucial management activity, encompassing lifecycle management of requirement changes, access control, change classification, and analysis. Requirement tracing is a key component of requirement management; it helps manage the state of requirements and the impact of changes by establishing dependencies and logical connections between requirements and other system elements.

[0079] In terms of technical implementation, state change triggering mechanisms are widely used in event-driven architectures and microservice architectures to achieve real-time response and automated processing. For example, when the state of an object or entity changes, the system automatically triggers a series of operations or events to ensure the system's reliability and flexibility.

[0080] In this application, the system handles state changes through asynchronous updates and event triggering to ensure data consistency and user experience. For example, in the order update status, the system may asynchronously update the query data to ensure the timeliness and consistency of the status update.

[0081] When any requirement item changes, the system automatically triggers a status update for related requirement items based on predefined relationships, ensuring efficient management and traceability of requirement changes. This mechanism demonstrates the system's automation and intelligence capabilities in requirement change management.

[0082] The method further includes: in response to the user's baseline creation instruction, extracting the target requirement item set and all its associated items from the requirement database, and performing version consistency verification.

[0083] A baseline is a core concept in requirements management. It refers to a specification or product that has been formally reviewed and approved, serving as the basis for further development, and subject to change only through a formal change control system. A baseline is a set of marked, frozen requirements. Creating a baseline from a collection of documents ensures that object versions and the shared links between them remain unchanged. Baselines are typically used for a specific development iteration or planned release.

[0084] Requirements management includes version and change control. The requirements baseline needs to be versioned, and the version number needs to be updated after each requirement changes to avoid confusion. Requirements change control is to handle changes to requirements in the requirements baseline in a controlled and consistent manner, including the assessment, coordination, approval or rejection, implementation, and verification of changes.

[0085] In requirements management, consistency is a crucial aspect. Consistency means that user requirements must align with business requirements, and functional requirements must align with user requirements. Methods for requirements verification include requirements review, prototyping and simulation, developing test cases, creating user manuals, utilizing traceability relationships, and automated analysis. Requirements tracing is the ability to describe requirements and track changes to them, and it is divided into forward tracing and backward tracing.

[0086] In requirements management, consistency verification ensures the consistency of the requirements set, guaranteeing consistency between business requirements, user requirements, and functional requirements. In requirements change management, change requests must submit reasons and solutions, and be approved by the CCB (Change Control Committee). Upon approval, the requirements document is updated, the baseline is adjusted, relevant teams (development, testing) are notified to make corresponding modifications, and the change history is recorded.

[0087] In practice, version consistency verification may involve checking requirement items and their associated items to ensure the consistency of all related items. For example, during a requirement change process, a consistency checker verifies whether the request and its items are consistent, ensuring that no request is missed.

[0088] In response to the user's baseline creation command, the target requirement item set and all its associated items are extracted from the requirements database, and version consistency verification is performed. This means: Extract requirement entries: Extract the target requirement entry and all its associated entries from the requirement database.

[0089] Version consistency verification ensures the consistency of requirement items and their related items through version control, change management, and consistency checks, thereby ensuring the integrity and consistency of requirements.

[0090] After the verification is passed, the set of requirement items and their associations are serialized, and their cryptographic hash values ​​are calculated to generate an unmodifiable requirement baseline snapshot and store it.

[0091] First, the set of requirement items and their relationships are serialized, that is, converted into a storable or transmittable format. The serialized data can be in binary or text format, which facilitates subsequent processing and storage.

[0092] Calculate the cryptographic hash value of the serialized data. A cryptographic hash function is a deterministic algorithm that converts data of arbitrary length into a fixed-length hash value (such as SHA-256, MD5, etc.). This hash value has the following characteristics: Uniqueness: Different input data usually generate different hash values ​​(although there is a possibility of collision attacks, it is difficult to achieve in practice).

[0093] Irreversible; the original data cannot be deduced from the hash value.

[0094] Integrity verification works by checking the hash value of any small change made to the original data, which can detect whether the data has been tampered with.

[0095] By storing the hash value of the serialized data along with the original data, an immutable "snapshot" can be created. Due to the uniqueness and irreversibility of hash values, any modification to the data will cause a change in the hash value, thus allowing verification of data integrity.

[0096] This snapshot (i.e., the serialized data and its hash value) is stored for later verification. When data integrity needs to be verified, the hash value of the serialized data can be recalculated and compared with the stored hash value to confirm that the data has not been tampered with.

[0097] The method further includes: real-time monitoring of change requests for baselined requirement items.

[0098] The calculation formula for the demand change impact index mathematical model in step S109 is as follows: Where I represents the demand change impact index, a dimensionless quantitative value; t represents the time variable, with t0 to t1 being the time window for assessing the change impact; n represents the total number of affected related demand items identified through the traceability chain; C represents the demand change propagation function, whose input is the change content and output is the change intensity; R i The weight coefficient of the i-th associated requirement item is determined by the requirement type (function, performance, interface) and its depth in the hierarchical structure. The parameters σ and μ are obtained through statistical analysis of historical change data. Specifically, the method involves collecting complete time-series data of the impact of N historical requirement changes, performing Gaussian fitting on the impact diffusion curve of each change, and taking the mean of all fitting results as μ and the standard deviation as σ. π represents pi, and e represents the natural constant. The weight coefficient R... i The calculation formula is: R i = α × β, where α is the requirement type weight (functional requirement = 1.0, performance requirement = 1.2, interface requirement = 1.5), β is the hierarchy depth decay factor, calculated as β = 0.8^(d-1), where d represents the depth of the requirement in the tree hierarchy (root node d=1); the change propagation function C(Δ) is a quantization function, whose input Δ is the feature vector of the change content description text after being transformed by the word embedding model, and the output is the normalized change intensity value in the interval [0,1], which is specifically implemented through a pre-trained neural network classifier.

[0099] This formula utilizes the output (n, R) of the traceability chain. i As the core input, it enables quantitative simulation of the impact of changes in both the time and logical dimensions.

[0100] The method further includes: using a data migration interface, converting and encapsulating the requirement entries, baseline snapshots, and change history in the requirement database according to the standardized ReqIF format to generate a migrateable data package, thereby achieving lossless data exchange with a heterogeneous requirement management platform.

[0101] Data migration refers to the process of moving data from one storage system (such as a database) to another. In requirements management, data migration may involve transferring data between different databases, tools, or platforms. Data migration typically includes steps such as data extraction, transformation, and loading (ETL). In requirements management, data migration may also involve migrating information such as requirement entries, baseline snapshots, and change history.

[0102] The ReqIF (Requirements Interchange Format) is an open, non-proprietary, standardized format used for exchanging requirements information between different systems, tools, or platforms. Based on XML documents, it supports the exchange of requirements, metadata, attributes, relationships, and other information. ReqIF is managed by the Object Management Group (OMG) and is widely used in requirements management tools. ReqIF supports requirements import / export, change management, and data integrity maintenance.

[0103] During data migration, information such as requirement items, baseline snapshots, and change history needs to be converted and encapsulated according to the ReqIF format. The ReqIF format supports a structured representation of requirements, including requirement items, relationships, attributes, baselines, and change sets. For example, ReqIF supports migrating entire projects, users, attributes, types, groups, links, baselines, and data schemas. ReqIF also supports change management mechanisms to ensure data consistency and integrity during the migration process.

[0104] Through standardized conversion and encapsulation of the ReqIF format, lossless data exchange with heterogeneous requirements management platforms can be achieved. This means that data will not be lost or corrupted during migration, and data exchange between different systems is more reliable and consistent. The standardized nature of ReqIF ensures that requirements information from different tools or platforms can be interpreted and processed consistently.

[0105] Data migration interfaces may involve steps such as data extraction, transformation, and loading. In requirements management, data migration interfaces may be implemented through APIs, tools, or middleware to convert requirement data into ReqIF format data packets and generate migrateable data packets. These data packets can be used for data exchange between different platforms or tools.

[0106] Example 3 This invention also proposes a requirement modeling and management system that supports multi-level requirement traceability and baseline management, including: The requirement information architecture management module is used to construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions based on preset engineering specifications. The intelligent requirement import module is used to receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture, generating requirement entries with a unified format and unique identifier. The traceability graph construction module is used to construct a demand traceability graph with demand items as nodes and relationship as edges based on the association. The graph traversal module is used to generate a demand traceability chain in both forward and backward dimensions using graph traversal algorithms. The report generation module is used to quantify the scope and extent of the impact of changes based on the traceability chain using a preset mathematical model of the impact index of demand changes, and automatically generate a demand consistency report.

[0107] Example 4 In one embodiment, the present invention proposes a requirement modeling and management method that supports multi-level requirement traceability and baseline management, characterized by comprising the following steps: S1. Construct a requirement information architecture: Based on the preset engineering specifications, construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions, and store it in the requirement database; wherein, the requirement information architecture includes requirement hierarchy definitions for defining requirement levels, requirement type definitions for classifying requirement properties, and requirement relationship definitions for describing logical dependencies between requirements; S2. Structured import and parsing of requirement data: Receive unstructured or semi-structured requirement data from external sources through the requirement import interface, use a word segmentation processing unit based on an attention mechanism deep learning model to perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture constructed in S1, generate requirement entries with a unified format and unique identifier, and persist them to the requirement database. S3. Dynamic Requirement Editing and Status Collaborative Update: Provides a requirement editing interface to respond to user editing operations on requirement items; when any requirement item changes, based on the association defined in S1, the status flag update logic of the associated requirement item is automatically triggered, and the status flag includes pending review, baselined, and changing status. S4. Requirements Baseline Snapshot Generation and Solidification: In response to the user's baseline creation command, the target requirement item set and all its associated items are extracted from the requirements database and version consistency is verified. After the verification is passed, the requirement item set and its associated relationships are serialized and their cryptographic hash values ​​are calculated to generate an unmodifiable requirements baseline snapshot and store it. S5. Change Impact Propagation and Historical Tracking: Real-time monitoring of change requests for baselined requirement items; once a change request is approved, the scope of affected requirement items is automatically determined based on the relationships defined in S1, and the status update logic in S3 is driven; at the same time, the change content, change reason, and scope of impact are stored as change history records in the requirement database. S6. Construction and Quantitative Impact Analysis of Demand Traceability Chain: Based on the demand relationships defined in S1, construct a demand traceability graph with demand items as nodes and relationships as edges; use a graph traversal algorithm to generate demand traceability chains in two dimensions: forward (high-level to low-level) and backward (low-level to high-level); based on the traceability chains, use a preset demand change impact index mathematical model to quantify the propagation range and degree of change impact, and automatically generate a demand consistency report; S7. Cross-platform requirement data migration: Through the data migration interface, the requirement entries, baseline snapshots and change history in the requirement database are converted and encapsulated according to the standardized ReqIF format to generate a migrateable data package, realizing lossless data exchange with heterogeneous requirement management platforms.

[0108] In S4, the step of generating a demand baseline snapshot includes: S4.1. Determine the baseline range, i.e. the set of target requirement items, based on user interaction selections; S4.2 Query the version number and latest update timestamp of all items in the target requirement item set in the requirement database, and perform version consistency verification to ensure that all items are in the latest and consistent version state; S4.3 After the verification is passed, the target requirement item set and all downstream items associated with it through the association relationship are serialized and encapsulated. S4.4 Calculate the hash value of the serialized data using the SHA-256 algorithm, and store the serialized data and hash value together to form an immutable baseline snapshot.

[0109] In S6, the calculation formula for the mathematical model of the demand change impact index is as follows: Where I represents the demand change impact index, a dimensionless quantitative value; t represents the time variable, with t0 to t1 being the time window for assessing the change impact; n represents the total number of affected related demand items identified through the traceability chain; C represents the demand change propagation function, whose input is the change content and output is the change intensity; R i The weight coefficient of the i-th associated requirement item is determined by the requirement type (function, performance, interface) and its depth in the hierarchical structure. The parameters σ and μ are obtained through statistical analysis of historical change data. Specifically, the method is as follows: collect complete impact time series data of N historical requirement changes, perform Gaussian fitting on the impact diffusion curve of each change, and take the mean of all fitting results as μ and the standard deviation as σ. π represents pi and e represents the natural constant.

[0110] This formula utilizes the output (n, R) of the traceability chain. iAs the core input, it enables quantitative simulation of the impact of changes in both the time and logical dimensions.

[0111] In S4.2, when the version consistency check fails, a consistency check report is submitted to the user, and the baseline creation process is blocked until the user completes the version conflict resolution.

[0112] In S2, the word segmentation processing unit based on the attention mechanism deep learning model is trained through the following steps: S2.1 Collect historical requirement documents as a training corpus; S2.2 Manually annotate the corpus, including the required entities, entity types, and relationships between entities; S2.3. Train a neural network model with a Transformer architecture using the labeled corpus, so that the model can learn the professional vocabulary, grammatical structure and semantic features of the target domain. S2.4 Deploy the trained model as a word segmentation processing unit to perform automated, high-precision word segmentation and keyword extraction on newly added demand texts.

[0113] The “derivation relationship” in the definition of the demand association relationship (S1) is explicitly defined as follows: if the realization of demand A depends entirely on the prerequisites defined by demand B, then demand A is said to be derived from demand B, and this relationship is unidirectional and non-cyclic.

[0114] Example 5 In one embodiment, the present invention also proposes a requirement modeling and management system that supports multi-level requirement traceability and baseline management to implement the above method, characterized in that it includes: The requirement information architecture management module is used to execute S1, build and maintain the requirement information architecture; The intelligent demand import module is used to execute S2 and integrates the aforementioned deep learning model. The requirements database is used to store requirement entries, baseline snapshots, and change history; The requirements editing and status management module is used to execute S3; The baseline management module is used to execute S4; The change management module is used to execute S5; The demand traceability and impact analysis module is used to execute S6, and it integrates the demand change impact index calculation unit. The data migration module is used to execute S7.

[0115] The demand tracing and impact analysis module includes: The traceability graph construction submodule is used to dynamically construct a requirement traceability graph based on the relationships in the current requirement database; The graph traversal submodule is used to perform a breadth-first search (BFS) algorithm to generate a demand traceability chain; The impact index calculation submodule is used to load and run the mathematical model of the demand change impact index; The report generation submodule is used to visualize the results of the impact index calculation and generate a structured, consistent report.

[0116] The demand database is a time-series database. In addition to storing the current state of demand data, it also records all state changes of each demand item throughout its entire lifecycle, forming a demand change time sequence diagram.

[0117] The system also includes a permission management module, which is based on the RBAC (role-based access control) model to assign different granular operation permissions to different users for requirement items, baselines and change operations, and the permissions are associated with the status flag of the requirement item and the baseline to which it belongs.

[0118] Example 6 This disclosure provides a non-volatile computer storage medium storing computer-executable instructions that can perform the steps described in the above embodiments.

[0119] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0120] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0121] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (AN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0123] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0124] The preferred embodiments of the present invention have been described above to make the spirit of the present invention clearer and easier to understand, and are not intended to limit the present invention. All modifications, substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope summarized by the appended claims.

Claims

1. A requirement modeling and management method that supports multi-level requirement traceability and baseline management, characterized in that, Includes the following steps: Step S101: Based on the preset engineering specifications, construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions; Step S103: Receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture to generate requirement entries with a unified format and unique identifier. Step S105: Based on the aforementioned relationships, construct a requirement traceability graph with requirement items as nodes and relationships as edges; Step S107: Using a graph traversal algorithm, generate a demand traceability chain in both forward and backward dimensions; Step S109: Based on the traceability chain, a preset mathematical model of the impact of demand change is used to quantify the scope and degree of the impact of the change, and a demand consistency report is automatically generated.

2. The method as described in claim 1, characterized in that, The requirement information architecture in step S101 includes requirement hierarchy definitions for defining requirement levels, requirement type definitions for classifying requirement properties, and requirement relationship definitions for describing logical dependencies between requirements.

3. The method as described in claim 1, characterized in that, After step S103, the method includes: providing a requirement editing interface to respond to user editing operations on requirement items.

4. The method as described in claim 3, characterized in that, The method further includes: when any requirement item changes, automatically triggering the status flag update logic of the associated requirement item based on the association relationship, wherein the status flag includes the status of pending review, baselined, and changing.

5. The method as described in claim 1, characterized in that, The method further includes: in response to the user's baseline creation instruction, extracting the target requirement item set and all its associated items from the requirement database, and performing version consistency verification.

6. The method as described in claim 5, characterized in that, After the verification is passed, the set of requirement items and their associations are serialized, and their cryptographic hash values ​​are calculated to generate an unmodifiable requirement baseline snapshot and store it.

7. The method as described in claim 1, characterized in that, The method also includes: real-time monitoring of change requests for baselined requirement items.

8. The method as described in claim 1, characterized in that, The calculation formula for the demand change impact index mathematical model in step S109 is as follows: Where I represents the demand change impact index, a dimensionless quantitative value; t represents the time variable, with t0 to t1 being the time window for assessing the change impact; n represents the total number of affected related demand items identified through the traceability chain; C represents the demand change propagation function, whose input is the change content and output is the change intensity; R i The weight coefficient of the i-th associated requirement item is determined by the requirement type (function, performance, interface) and its depth in the hierarchical structure. The parameters σ and μ are obtained through statistical analysis of historical change data. Specifically, the complete impact time series data of N historical requirement changes are collected, and the impact diffusion curve of each change is Gaussian fitted. The mean of all fitted results is taken as μ, and the standard deviation as σ. π represents pi, and e represents the natural constant. This formula uses the output (n, Ri) of the traceability chain as the core input to achieve a quantitative simulation of the impact of changes in both the time and logical dimensions.

9. The method as described in claim 1, characterized in that, The method further includes: using a data migration interface, converting and encapsulating the requirement entries, baseline snapshots, and change history in the requirement database according to the standardized ReqIF format to generate a migrateable data package, thereby achieving lossless data exchange with a heterogeneous requirement management platform.

10. A requirement modeling and management system that supports multi-level requirement traceability and baseline management, comprising: The requirement information architecture management module is used to construct a requirement information architecture with a tree-like hierarchical structure, attribute definitions, and relationship definitions based on preset engineering specifications. The intelligent requirement import module is used to receive unstructured or semi-structured requirement data from external sources through the requirement import interface, perform syntactic and semantic parsing on the requirement text, extract key attributes, and map the parsed data to the corresponding level and type according to the requirement information architecture, generating requirement entries with a unified format and unique identifier. The traceability graph construction module is used to construct a demand traceability graph with demand items as nodes and relationship as edges based on the association. The graph traversal module is used to generate a demand traceability chain in both forward and backward dimensions using graph traversal algorithms. The report generation module is used to quantify the scope and extent of the impact of changes based on the traceability chain using a preset mathematical model of the impact index of demand changes, and automatically generate a demand consistency report.

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