Objective modeling method

Abstract

The invention relates to the technical field of information technology, in particular to an objectification modeling method which comprises the following steps: creating an object model; s2, obtaining the object model in the step S1, and configuring a polymorphic behavior template for the object model; recording interaction data and behavior decisions in the object life cycle; dynamically optimizing the attributes and behaviors of the object through an autogenic mechanism of the object model; cross-system sharing is realized by using an object interoperation protocol; carrying out independent evolution and synchronization on the object model in a distributed environment; and automatically deriving attribute configuration and behavior decision of the newly created object instance. According to the method, the polymorphic behavior template is configured for the object model, the objects are allowed to dynamically select behaviors in different environments or service contexts, the flexibility and adaptability of the objects are improved, the behaviors of each object can be autonomously adjusted according to system loads, user requirements or environment changes, and the behavior talking problem during system running is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of information technology, and in particular to an object-oriented modeling method. Background Art

[0002] As the complexity of software systems continues to increase, object-oriented modeling has become one of the core means of system design and development. Traditional object-oriented modeling methods can effectively map entities and behaviors in the real world into models in the system by defining object classes, attributes, behaviors, and relationships between them, thereby simplifying system development and maintenance. However, traditional object-oriented modeling methods have the following shortcomings:

[0003] 1. Object behavior rigidity: Traditional object models are usually statically configured and cannot be dynamically adjusted according to different system environments, business scenarios, and user needs. Object behaviors are fixed and lack flexibility and adaptability, making it difficult to cope with complex or changing business scenarios during system operation, thus affecting the overall flexibility and operating efficiency of the system.

[0004] 2. Object models cannot be automatically optimized: Traditional object modeling methods lack a mechanism to automatically optimize object properties and behaviors based on historical data and real-time feedback. Object optimization relies on manual intervention. As the system runs for a long time, the model may not be able to adapt to new business needs or operating conditions, affecting system performance and scalability.

[0005] 3. Cross-system object models cannot be collaboratively reused: In traditional object-oriented modeling methods, object models between different systems are often isolated and lack effective interoperability mechanisms, making it difficult to share or reuse object models between different systems. This not only increases development costs, but also easily leads to repeated development of objects with similar functions in different systems, affecting development efficiency and system consistency.

[0006] 4. Object evolution problem in distributed systems: In a distributed environment, traditional object modeling methods usually have difficulty in achieving independent evolution of object models of each node and maintaining global consistency. Object models cannot be optimized according to local needs. At the same time, the lack of an effective synchronization mechanism leads to inconsistency in the global object model, limiting the scalability and flexibility of the system.

[0007] 5. Initialization of new object instances is complex and error-prone: In traditional object modeling methods, when creating a new object instance, its properties and behaviors usually need to be manually configured, which is prone to human configuration errors. The configuration process is complex and time-consuming, affecting the system's response speed and the adaptability of new objects.

[0008] 6. Static configuration and rigidity of behavior rules: In traditional object modeling methods, the behavior rules of objects are usually statically configured and cannot be dynamically adjusted and optimized based on feedback from system operation. This causes the behavior of objects to become rigid and unable to adapt to operational requirements in different time periods or scenarios, affecting the long-term flexibility and adaptability of the object model. Summary of the invention

[0009] The technical problem to be solved by the present invention is: in order to solve the technical problem that objects of existing static configuration object-based modeling are inflexible and difficult to adapt, the present invention provides an object-based modeling method, which can improve the flexibility and adaptability of objects by improving the object-based modeling.

[0010] The technical solution adopted by the present invention to solve the technical problem is: an object-oriented modeling method, comprising the following steps:

[0011] S1. Create an object model;

[0012] S2, obtaining the object model in step S1, and configuring a polymorphic behavior template for the object model;

[0013] S3, records the interaction data and behavior decisions during the object life cycle;

[0014] S4, dynamically optimize the properties and behaviors of objects through the self-performance mechanism of the object model;

[0015] S5. Use object interoperability protocols to achieve cross-system sharing;

[0016] S6, Independent evolution and synchronization of object models in a distributed environment;

[0017] S7. Automatically derive the attribute configuration and behavior decisions of newly created object instances.

[0018] Therefore, by configuring polymorphic behavior templates for object models, objects are allowed to dynamically select behaviors in different environments or business contexts, thereby improving the flexibility and adaptability of objects. Each object can autonomously adjust its behavior according to system load, user needs or environmental changes, avoiding behavioral speech problems during system operation; by using object interoperability protocols, object models in multiple systems can share and reuse data and behaviors, breaking the isolation between different systems and realizing cross-system collaboration and reuse of object models. The system can avoid repeated development of objects with similar functions, improving development efficiency and consistency; in a distributed environment, each distributed node is allowed to independently evolve the local object model and update it to the central node through a synchronization mechanism. The global consistency of the object model is achieved, and each distributed node can independently optimize its local object, which improves the scalability and flexibility of the system, while maintaining the synchronization and consistency of the global model; for newly created object instances, the system can automatically derive reasonable attribute configurations and behavioral decisions based on historical data, speeding up the initialization process of new objects, ensuring that new objects can adapt to the business needs of the existing system, and reducing the possibility of human configuration errors; by recording the interaction data during the object life cycle, the system can automatically generate behavioral rules and adjust these rules based on feedback during operation to achieve dynamic optimization of behavior. Objects can continuously adjust their decision rules based on their own behavioral performance at different times to maintain flexibility and adaptability of behavior.

[0019] Further, in step S1, the object model includes: object class, attribute and behavior; wherein: object class is the template of the object, attribute is the static data or dynamic data representing the state of the object, and behavior is the operation that the object can perform in the system. Thus, by creating the object model, a basic framework can be provided for the flexible adjustment and optimization of the subsequent object model.

[0020] Furthermore, in step S2, by configuring polymorphic behavior templates, the object can dynamically select the optimal behavior according to different environments or business contexts; the polymorphic behavior templates include: static attributes, dynamic monitoring attributes, computer attributes, location attributes, associated objects, and events; the system dynamically switches behaviors according to current environmental variables or user needs, giving the object polymorphism at runtime; by continuously monitoring changes in the business environment, the system can automatically trigger behavior selection rules in actual operation. Thus,.

[0021] Furthermore, in step S2, the polymorphic behavior template configuration includes: behavior template creation, behavior selection rule definition, polymorphic mechanism implementation, and continuous monitoring of business context, thereby ensuring that the object can dynamically adjust its behavior according to the environment.

[0022] Furthermore, in step S3, the interaction data includes: the creation, interaction, update and destruction process of the object; by analyzing these historical interaction data, behavior rules are automatically generated to optimize the behavior decisions of future objects to make them more in line with business needs.

[0023] Further, in step S4, the object model dynamically optimizes the properties, behaviors and relationships between the object groups according to historical data and behavioral feedback through a self-evolution mechanism; the system collects the historical data of the object, analyzes the behavioral performance, automatically optimizes the properties and behaviors of the object, and reconstructs the associations between objects, so that the object model can self-adjust and optimize as the system runs. Thus, through the self-evolution mechanism of the object model, the object can be dynamically optimized based on historical data and behavioral feedback, adjust the properties, behaviors and relationships between objects, and achieve self-adjustment and optimization. As the system runs, the object model can continue to learn and adjust, so that the overall performance and efficiency of the system are gradually improved; in the self-evolution mechanism, the system dynamically optimizes the properties of the object, adjusts the behavioral rules, and reconstructs the associations between objects by collecting and analyzing historical data to achieve continuous evolution of the model.

[0024] Furthermore, in step S5, through the object interoperability protocol, the object model in the system can share and reuse data and behaviors across different systems; the interoperability protocol defines standard interfaces and attribute mapping rules, so that objects in different systems can exchange data and call behaviors in a consistent manner, supporting cross-system object collaboration. Therefore, the interoperability protocol can achieve standardized data sharing and behavior reuse of the system object model to ensure that objects in the system can collaborate efficiently.

[0025] Furthermore, in step S6, in the distributed system, the object model on each distributed node is allowed to evolve independently according to local needs and optimize the model; the object model independently optimized by each node is uploaded to the central node through a synchronization mechanism, and the central node is responsible for synchronizing the changes of each node to the global model to maintain global consistency. As a result, the object model on each node can evolve independently according to its own needs, and at the same time, global synchronization optimization can be achieved through the central node, which improves the scalability and flexibility of the system.

[0026] Furthermore, in step S7, the system automatically derives reasonable attribute configuration and behavior decisions for the newly created object based on the object's interaction history and the collected data. As a result, new objects do not need to be manually configured, but instead generate default attributes and behavior rules suitable for the current business scenario based on historical data, ensuring that new objects can quickly adapt to the existing system, reducing human errors and speeding up the system's response speed.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. The present invention configures polymorphic behavior templates for object models, allowing objects to dynamically select behaviors in different environments or business contexts, thereby improving the flexibility and adaptability of objects. Each object can autonomously adjust its behavior according to system load, user needs or environmental changes, avoiding behavioral speech problems during system operation.

[0029] 2. The present invention uses the self-evolution mechanism of the object model to enable objects to be dynamically optimized based on historical data and behavioral feedback, adjust the attributes, behaviors and relationships between objects, and achieve self-adjustment and optimization. As the system runs, the object model can continue to learn and adjust, so that the overall performance and efficiency of the system are gradually improved.

[0030] 3. The present invention utilizes the object interoperability protocol to enable object models in multiple systems to share and reuse data and behaviors, breaking the isolation between different systems and realizing cross-system collaboration and reuse of object models. The system can avoid repeated development of objects with similar functions and improve development efficiency and consistency.

[0031] 4. In a distributed environment, the present invention allows each distributed node to independently evolve the local object model and update it to the central node through a synchronization mechanism, thereby achieving global consistency of the object model. Each distributed node can independently optimize its local object, improving the scalability and flexibility of the system while maintaining the synchronization and consistency of the global model.

[0032] 5. For newly created object instances, the system of the present invention can automatically derive reasonable attribute configurations and behavior decisions based on historical data, which speeds up the initialization process of new objects, ensures that new objects can adapt to the business needs of existing systems, and reduces the possibility of human configuration errors.

[0033] 6. By recording the interaction data during the life cycle of the object, the system can automatically generate behavioral rules and adjust these rules based on the feedback during operation to achieve dynamic optimization of behavior. The object can continuously adjust its decision-making rules according to its own behavioral performance at different times to maintain flexibility and adaptability of behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0035] Figure 1 The flowchart of the object-oriented modeling method of the present invention is shown in FIG. DETAILED DESCRIPTION

[0036] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0037] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0038] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0039] like Figure 1 The figure shows the best embodiment of the present invention. The object-oriented modeling method of this embodiment includes the following steps:

[0040] S1. Create an object model;

[0041] S2, obtaining the object model in step S1, and configuring a polymorphic behavior template for the object model;

[0042] S3, records the interaction data and behavior decisions during the object life cycle;

[0043] S4, dynamically optimize the properties and behaviors of objects through the self-performance mechanism of the object model;

[0044] S5. Use object interoperability protocols to achieve cross-system sharing;

[0045] S6, Independent evolution and synchronization of object models in a distributed environment;

[0046] S7. Automatically derive the attribute configuration and behavior decision of the newly created object instance. Therefore, by configuring polymorphic behavior templates for the object model, the object is allowed to dynamically select behavior in different environments or business contexts, which improves the flexibility and adaptability of the object. Each object can autonomously adjust its behavior according to system load, user needs or environmental changes to avoid behavioral speech problems during system operation; using the object interoperability protocol, object models in multiple systems can share and reuse data and behaviors, breaking the isolation between different systems and realizing cross-system collaboration and reuse of object models. The system can avoid repeated development of objects with similar functions, improving development efficiency and consistency; in a distributed environment, each distributed node is allowed to independently evolve the local object model and update it to the central node through a synchronization mechanism. The global consistency of the object model is achieved, and each distributed node can independently optimize its local object, which improves the scalability and flexibility of the system, while maintaining the synchronization and consistency of the global model; for newly created object instances, the system can automatically derive reasonable attribute configurations and behavioral decisions based on historical data, speeding up the initialization process of new objects, ensuring that new objects can adapt to the business needs of the existing system, and reducing the possibility of human configuration errors; by recording the interaction data during the object life cycle, the system can automatically generate behavioral rules and adjust these rules based on feedback during operation to achieve dynamic optimization of behavior. Objects can continuously adjust their decision rules based on their own behavioral performance at different times to maintain flexibility and adaptability of behavior.

[0047] In this embodiment, in step S1, the object model includes: object class, attribute and behavior; wherein: object class is the template of the object, attribute is the static data or dynamic data representing the state of the object, and behavior is the operation that the object can perform in the system. Therefore, by creating the object model, a basic framework can be provided for the flexible adjustment and optimization of the subsequent object model.

[0048] In this embodiment, in step S2, by configuring a polymorphic behavior template, the object can dynamically select the optimal behavior according to different environments or business contexts; the polymorphic behavior template includes: static attributes, dynamic monitoring attributes, computer attributes, location attributes, associated objects, and events; the system dynamically switches behaviors according to current environmental variables or user needs, giving the object polymorphism at runtime; by continuously monitoring changes in the business environment, the system can automatically trigger behavior selection rules in actual operation; polymorphic behavior template configuration includes: behavior template creation, behavior selection rule definition, polymorphic mechanism implementation, and continuous monitoring of business contexts. In this way, it is ensured that the object can dynamically adjust its behavior according to the environment.

[0049] In this embodiment, in step S3, the interaction data includes: the creation, interaction, update and destruction process of the object; by analyzing these historical interaction data, behavior rules are automatically generated to optimize the behavior decisions of future objects to make them more in line with business needs.

[0050] In this embodiment, in step S4, the object model dynamically optimizes the properties, behaviors and relationships between object groups of objects according to historical data and behavioral feedback through a self-evolution mechanism; the system collects the historical data of the object, analyzes the behavioral performance, automatically optimizes the properties and behaviors of the object, and reconstructs the associations between objects, so that the object model can self-adjust and optimize as the system runs. Thus, through the self-evolution mechanism of the object model, the object can be dynamically optimized based on historical data and behavioral feedback, adjust the properties, behaviors and relationships between objects, and achieve self-adjustment and optimization. As the system runs, the object model can continue to learn and adjust, so that the overall performance and efficiency of the system are gradually improved; in the self-evolution mechanism, the system dynamically optimizes the properties of the object, adjusts the behavioral rules, and reconstructs the associations between objects by collecting and analyzing historical data to achieve continuous evolution of the model.

[0051] In this embodiment, in step S5, through the object interoperability protocol, the object model in the system can share and reuse data and behaviors across different systems; the interoperability protocol defines standard interfaces and attribute mapping rules, so that objects in different systems can exchange data and call behaviors in a consistent manner, supporting cross-system object collaboration. Therefore, the interoperability protocol can achieve standardized data sharing and behavior reuse of the system object model, ensuring that objects in the system can collaborate efficiently.

[0052] In this embodiment, in step S6, in the distributed system, the object model on each distributed node is allowed to evolve independently according to local needs and optimize the model; the object model after independent optimization of each node is uploaded to the central node through a synchronization mechanism, and the central node is responsible for synchronizing the changes of each node to the global model to maintain global consistency. As a result, the object model on each node can evolve independently according to its own needs, and at the same time, global synchronization optimization can be achieved through the central node, which improves the scalability and flexibility of the system.

[0053] In this embodiment, in step S7, the system automatically derives reasonable attribute configuration and behavior decision for the newly created object based on the object's interaction history and the collected data. Therefore, the new object does not need to be manually configured, but generates default attributes and behavior rules suitable for the current business scenario based on historical data, ensuring that the new object can quickly adapt to the existing system, reducing human errors and speeding up the system's response speed.

[0054] In summary, the present invention configures polymorphic behavior templates for object models, allowing objects to dynamically select behaviors in different environments or business contexts, thereby improving the flexibility and adaptability of objects. Each object can autonomously adjust its behavior according to system load, user needs or environmental changes, avoiding behavioral speech problems during system operation; through the self-evolution mechanism of the object model, objects can be dynamically optimized based on historical data and behavioral feedback, and the properties, behaviors and relationships of the objects can be adjusted to achieve self-adjustment and optimization. As the system runs, the object model can continue to learn and adjust, so that the overall performance and efficiency of the system are gradually improved; by utilizing the object interoperability protocol, object models in multiple systems can share and reuse data and behaviors, breaking the isolation between different systems, and realizing cross-system collaboration and reuse of object models. The system can avoid repeated development of objects with similar functions, improving Improve development efficiency and consistency; in a distributed environment, each distributed node is allowed to independently evolve the local object model and update it to the central node through a synchronization mechanism, thus achieving global consistency of the object model. Each distributed node can independently optimize its local object, thus improving the scalability and flexibility of the system while maintaining synchronization and consistency of the global model. For newly created object instances, the system can automatically derive reasonable attribute configurations and behavior decisions based on historical data, thus speeding up the initialization process of new objects, ensuring that new objects can adapt to the business needs of the existing system, and reducing the possibility of human configuration errors. By recording the interaction data during the object life cycle, the system can automatically generate behavior rules and adjust these rules based on feedback during operation to achieve dynamic optimization of behavior. Objects can continuously adjust their decision rules based on their own behavior performance at different times to maintain flexibility and adaptability of behavior.

[0055] The above description is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. An object-oriented modeling method, characterized in that: The following steps are involved: S1. Create an object model; S2, obtaining the object model in step S1, and configuring a polymorphic behavior template for the object model; S3, records the interaction data and behavior decisions during the object life cycle; S4, dynamically optimize the properties and behaviors of objects through the self-performance mechanism of the object model; S5. Use object interoperability protocols to achieve cross-system sharing; S6, Independent evolution and synchronization of object models in a distributed environment; S7. Automatically derive the attribute configuration and behavior decisions of newly created object instances.

2. The object-oriented modeling method according to claim 1, characterized in that: In step S1, the object model includes: Object classes, attributes, and behaviors; Among them: the object class is the template of the object, the attribute is the static data or dynamic data representing the state of the object, and the behavior is the operation that the object can perform in the system.

3. The object-oriented modeling method according to claim 1, characterized in that: In step S2, by configuring a polymorphic behavior template, the object can dynamically select the optimal behavior according to different environments or business contexts; Polymorphic behavior templates include: Static attributes, dynamic monitoring attributes, computer attributes, location attributes, associated objects, and events; The system dynamically switches behaviors based on current environment variables or user needs, giving objects polymorphism at runtime; By continuously monitoring changes in the business environment, the system can automatically trigger behavior selection rules in actual operation.

4. The object-oriented modeling method according to claim 1, characterized in that: In step S2, the polymorphic behavior template configuration includes: Creation of behavior templates, definition of behavior selection rules, implementation of polymorphism mechanisms, and continuous monitoring of business contexts.

5. The object-oriented modeling method according to claim 1, characterized in that: In step S3, the interaction data includes: The process of object creation, interaction, update and destruction; By analyzing these historical interaction data, behavioral rules are automatically generated to optimize future object behavior decisions to make them more in line with business needs.

6. The object-oriented modeling method according to claim 1, characterized in that: In step S4, the object model dynamically optimizes the properties, behaviors, and relationships between object groups based on historical data and behavior feedback through a self-evolution mechanism; The system will collect historical data of objects, analyze behavioral performance, automatically optimize the properties and behaviors of objects, and reconstruct the relationships between objects, so that the object model can self-adjust and optimize as the system runs.

7. The object-oriented modeling method according to claim 1, characterized in that: In step S5, through the object interoperability protocol, the object model in the system can share and reuse data and behaviors across different systems; The interoperability protocol defines standard interfaces and attribute mapping rules, enabling objects in different systems to exchange data and call behaviors in a consistent manner, supporting cross-system object collaboration.

8. The object-oriented modeling method according to claim 1, characterized in that: In step S6, in the distributed system, the object model on each distributed node is allowed to evolve independently according to local needs to optimize the model; The object models independently optimized by each node are uploaded to the central node through a synchronization mechanism. The central node is responsible for synchronizing the changes of each node to the global model to maintain global consistency.

9. The object-oriented modeling method according to claim 1, characterized in that: In step S7, the system automatically derives reasonable attribute configurations and behavior decisions for the newly created object based on the object's interaction history and the collected data.

Images