Visual software modeling method for computer software view
By subdividing the software model into multiple functional modules and optimizing using complexity and dependency evaluation algorithms, the problems of high coupling and complexity in traditional software modeling methods are solved, and more efficient modular design and maintainability are achieved.
Patent Information
- Application Number
- CN202510239588.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-03
- Publication Date
- 2025-06-06
AI Technical Summary
Traditional software modeling methods are difficult to effectively divide modules, resulting in high coupling and increasing the maintenance cost and complexity of the system.
By subdividing the software model into multiple functional modules, each functional module is responsible for specific functions, using complexity evaluation algorithms and dependency algorithms for evaluation and optimization, dynamically adjusting the dependence between functional modules to achieve a more efficient modular design.
It realizes a more efficient modular design, reduces system complexity and maintenance costs, and improves system maintainability and modeling efficiency.
Smart Images
Figure CN120104119A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of computer software, and in particular to a visual software modeling method of a computer software view. Background Art
[0002] Computer software is the computer programs, procedures, rules, and possible files, documents, and data related to the operation of computer systems. Software is the interface between users and hardware. Users mainly communicate with computers through software. Software is an important basis for computer system design. As software systems become more and more complex, traditional text and tabular design documents often cannot meet the needs of understanding and maintaining complex software systems.
[0003] In traditional modeling methods, the entire software system is often modeled directly, which makes it difficult to effectively divide modules and lacks flexible modular design, increasing the complexity of software modeling. When faced with changing requirements, multiple functional components in the software system are often tightly coupled, resulting in the modification of one component may require the gradual and large-scale reconstruction or adjustment of other functions. This high coupling increases the maintenance cost of the system and reduces modeling efficiency. Summary of the invention
[0004] The purpose of the present invention is to provide a visual software modeling method for computer software views, which solves the problems raised in the above background technology.
[0005] To achieve the above object, the present invention provides the following technical solution: a visual software modeling method of a computer software view, comprising the following steps: Pre-modeling preparation: select visual modeling tools according to software requirements, and introduce code generation modeling tools to automatically generate software models based on existing code bases and automatically update software models when codes are changed to ensure consistency between software models and codes; Modular modeling, subdividing the software model into multiple functional modules. Each functional module is responsible for a specific function. Each functional module is modeled and maintained separately, and the subdivided functional modules are visualized through UML diagrams; Complexity evaluation: Use the complexity evaluation algorithm to evaluate the complexity of each functional module, and determine whether the functional module needs to be optimized based on the results; Module dependency: After the software model is subdivided into multiple functional modules, the dependency algorithm is used to evaluate the dependency between the functional modules, and based on the results, it is determined whether the functional modules need to be optimized to avoid excessive coupling between the functional modules. Dynamic adjustment: evaluate the overall dependency of functional modules through the overall evaluation algorithm, and quantify the results to obtain the overall software dependency S, so as to understand the overall software coupling situation, and set the adjustment threshold Y3 for the overall software coupling S to determine whether to adjust the data in the dependency algorithm to improve the accuracy of the dependency algorithm; Model verification: After the modeling of the software functional modules is completed, the reviewer will review each functional module to ensure that the design meets the requirements and there are no omissions. After passing the review, all modeling data and other related data will be organized into system documents and stored in encrypted form.
[0006] Optionally, the complexity evaluation algorithm process is as follows: ;
[0007] Among them, CM i is the complexity of functional module i; E k is the symbolic complexity of the kth subfunction in the functional module, which is obtained by the number of symbols, operands and expressions required by the subfunction; W k is the influence coefficient of the kth sub-function in the functional module, ranging from 0 to 1; h is the number of sub-functions; U k is the change frequency of the kth sub-function in the functional module; V k is the dynamic change frequency of the kth sub-function in the functional module; The complexity CM of functional module i i The larger the size, the more functions it includes, the higher the complexity, and the more resources need to be managed and maintained. Set the complexity CM of functional module i i The complexity threshold is Y1, when the complexity of functional module i is CM i >complexity threshold Y1, it means that functional module i is too complex and needs to be optimized. At this time, the management personnel are notified to handle it.
[0008] Optionally, the dependency algorithm process is as follows: ;
[0009] Where D(M i ,M j ) is the dependency between functional module i and functional module j; CM j is the complexity of functional module j; β i,j is the interaction weight between functional module i and functional module j; F(Mi ,M j ) is the historical change frequency correlation between functional module i and functional module j; α is the historical change frequency influence coefficient, ranging from 0 to 1; F(M i ,M j ) The process is as follows: ;
[0010] Where ΔUM i is the change frequency of functional module i; ΔUM j is the change frequency of functional module j; The historical change frequency correlation F(M) between function module i and function module j i ,M j ) is larger, indicating that the mutual influence between the two modules is smaller. i ,M j ) is smaller, indicating that the mutual influence between the two modules is greater. The dependency D(M i ,M j ) is lower, indicating that the coupling between functional module i and functional module j is weaker, the independence and cohesion of the modules are better, and the dependency D(M) between functional module i and functional module j is i ,M j ) is higher, indicating that the coupling between functional module i and functional module j is stronger, and the degree of mutual dependence is higher. The modification of the module may cause a chain reaction and affect the stability of the system. The dependency D(M) between functional module i and functional module j is set. i ,M j ) has a dependency threshold of Y2. When D(M i ,M j )>Y2, it indicates that the dependency between function module i and function module j is too high, and the administrator is notified to handle it.
[0011] Optionally, the overall evaluation algorithm process in the dynamic adjustment step is as follows: ;
[0012] Where S is the overall software dependency; N is the number of functional modules; Software overall dependency R(M i ,M j ) is the interactive resource consumption between functional module i and functional module j; R max is the total amount of resources; θ is the resource consumption impact coefficient, ranging from 0 to 1; The double summation symbol ensures that the dependency between each pair of functional modules can be calculated. The higher the overall software dependency S, the stronger the dependency between the software functional modules and the higher the potential coupling risk. The adjustment threshold of the overall software dependency S is set to Y3. When the overall software dependency S is greater than the adjustment threshold Y3, it means that the overall software dependency is too high. At this time, the interaction weight β between functional module i and functional module j is increased. i,j In order to avoid excessive coupling between modules in the system, the adjustment process is as follows: ;
[0013] where Xβ i,j is the interaction weight between the new functional module i and the functional module j; γ is the adjustment influence coefficient, ranging from 0 to 1; When the overall software dependency S is too high, adjust the interaction weight β between function module i and function module j according to the amount of risk excess i,j , so that it can be dynamically adjusted according to the actual situation of the software, improving the flexibility of the software.
[0014] Optionally, in the pre-modeling preparation step, the visual modeling tool is VisualParadigm, and the code generation modeling tool is JHipster.
[0015] Optionally, in the modular modeling step, the visual display includes class diagrams, component diagrams, deployment diagrams, use case diagrams, activity diagrams, timing diagrams, state diagrams and communication diagrams.
[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention divides the software model into multiple functional modules according to the needs. Each functional module is responsible for a certain type of specific function in the software system, and the complexity of each functional module is evaluated by a complexity evaluation algorithm. Influence coefficients are added to different sub-functions of the functional module to improve the accuracy of complexity evaluation. At the same time, a threshold is set for the result to determine whether further subdivision is needed, thereby achieving a more efficient modular design and effectively reducing the complexity of the system, so that developers only need to focus on the design and implementation of specific functional modules, thereby improving the maintainability of the system.
[0017] 2. The present invention uses a dependency algorithm to quantitatively evaluate the dependency between different functional modules. If the dependency is too high, the interaction weights of the relevant functional modules can be reduced to reduce the coupling between the functional modules, thereby ensuring the collaborative work efficiency during software modeling. The overall dependency of the software functional modules is then quantitatively evaluated through an overall evaluation algorithm to obtain the overall software dependency S. Resource consumption factors are introduced into the overall evaluation algorithm to avoid system performance bottlenecks caused by excessive interactive operations, so that computers can use resources more efficiently and optimize the overall efficiency of the computer system. The dependency algorithm can be adjusted in real time according to the actual situation of the overall software dependency S to improve the accuracy of the dependency algorithm, further avoid excessive coupling, reduce system maintenance costs, and improve modeling efficiency.
[0018] Optionally, in the model verification step, after obtaining the system documentation, the system documentation is managed through a version control tool to ensure that historical versions can be traced back at different stages.
[0019] Optionally, the version control tool is Git. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION
[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1
[0022] See also Figure 1 , this implementation provides a visual software modeling method for a computer software view, comprising the following steps: Pre-modeling preparation: select visual modeling tools according to software requirements, and introduce code generation modeling tools to automatically generate software models based on existing code bases and automatically update software models when codes are changed to ensure consistency between software models and codes; Modular modeling, subdividing the software model into multiple functional modules. Each functional module is responsible for a specific function. Each functional module is modeled and maintained separately, and the subdivided functional modules are visualized through UML diagrams; Specifically, the visual display includes class diagrams, component diagrams, deployment diagrams, use case diagrams, activity diagrams, sequence diagrams, state diagrams, and communication diagrams; Specifically, when dividing the functional modules, they can be divided according to the following contents: Functional independence: Each module should focus on completing a specific function in the system to avoid modules taking on too many responsibilities. Functional division can ensure that each module has high cohesion and the tasks completed by each module can be clearly defined; Separation of business logic: modularize different business logic functions so that each module can independently process business, such as user management, order processing, payment system, etc. This division helps reduce the dependency between modules and improve the flexibility of the system; Reusability: Common functions or functions that can be shared by multiple modules can be extracted as a separate module for multiple use, such as log modules, authentication modules, etc.
[0023] Complexity evaluation: Use the complexity evaluation algorithm to evaluate the complexity of each functional module, and determine whether the functional module needs to be optimized based on the results; Module dependency: After the software model is subdivided into multiple functional modules, the dependency algorithm is used to evaluate the dependencies between modules, and based on the results, it is determined whether the functional modules need to be optimized to avoid excessive coupling between functional modules. Dynamic adjustment, evaluate the overall dependency of software functional modules, and quantify the results to obtain the overall software dependency S, so as to understand the overall software coupling situation, and set the adjustment threshold Y3 for the overall software coupling S to determine whether to adjust the data in the dependency algorithm to improve the accuracy of the dependency algorithm; Model verification: After the modeling of the software functional modules is completed, the reviewer will review each functional module to ensure that the design meets the requirements and there are no omissions. After passing the review, all modeling data and other related data will be organized into system documents and stored in encrypted form.
[0024] Specifically, after obtaining the system documentation, the system documentation is managed through the version control tool Git to ensure that historical versions can be traced back at different stages.
[0025] More specifically, in this embodiment: by subdividing the software model into multiple functional modules according to the needs, each functional module is responsible for a certain type of specific function in the software system, so that developers only need to focus on the design and implementation of specific functional modules, improve modeling efficiency, and evaluate the complexity of each functional module through the complexity evaluation algorithm, and then determine whether further subdivision is needed based on the specific complexity, which can help designers identify which modules need to be optimized or split, thereby achieving more efficient modular design to improve the maintainability of the system and effectively reduce the complexity of the system. When the dependency between functional modules is too high, it means that when one of the functional modules is modified, it will lead to large-scale changes in other functional modules, making it difficult to effectively expand and modify the system, increasing the workload. At this time, the dependency between different functional modules is quantitatively evaluated through the dependency algorithm, which is convenient for staff to understand the dependency between functional modules and decide whether to optimize based on the specific situation. If the dependency is too high, the dependency between functional modules can be reduced by reducing the interaction weights of related functional modules.
[0026] Finally, the overall dependency of the software functional modules is quantitatively evaluated through the overall evaluation algorithm to obtain the overall software dependency S, so as to understand the overall coupling of the software. Resource consumption factors are introduced into the overall evaluation algorithm to avoid system performance bottlenecks caused by excessive interactive operations, so that computers can use resources more efficiently, improve performance, reduce redundant interactions and unnecessary calculations, thereby optimizing the overall efficiency of the computer system, and set the adjustment threshold Y3 for the overall software coupling S to determine whether to adjust the data in the dependency algorithm, so that the dependency algorithm can be adjusted in real time according to the overall situation of software modeling, so as to improve the accuracy of the dependency algorithm, further reduce coupling, and improve modeling efficiency.
[0027] Furthermore, the complexity evaluation algorithm process is as follows: ;
[0028] Among them, CM i is the complexity of functional module i; E k is the symbolic complexity of the kth subfunction in the functional module, which is obtained by the number of symbols, operands and expressions required by the subfunction; W k is the influence coefficient of the kth sub-function in the functional module, ranging from 0 to 1; h is the number of sub-functions; U k is the change frequency of the kth sub-function in the functional module; V k is the dynamic change frequency of the kth sub-function in the functional module; Specifically, the complexity CM of functional module i i The larger the size, the more functions it includes, the higher the complexity, and the more resources need to be managed and maintained. Set the complexity CM of functional module i i The complexity threshold is Y1, when the complexity of functional module i is CM i >complexity threshold Y1, it means that function module i is too complex and needs to be optimized. At this time, the management personnel are notified to handle it. The management personnel can further split the function modules with high complexity, or delete and modify the sub-functions of the function modules to achieve the effect of optimization and adjustment. Finally, the complexity evaluation algorithm is used to evaluate it to ensure that overly complex function modules do not appear, thereby effectively reducing the complexity of the system and achieving efficient modular design effects to improve the maintainability of the system.
[0029] Furthermore, the dependency algorithm process is as follows: ;
[0030] Where D(M i ,M j ) is the dependency between functional module i and functional module j; CM j is the complexity of functional module j; β i,j is the interaction weight between functional module i and functional module j; F(M i ,M j ) is the historical change frequency correlation between functional module i and functional module j; α is the historical change frequency influence coefficient, ranging from 0 to 1; F(M i ,M j ) The process is as follows: ;
[0031] Where ΔUM i is the change frequency of functional module i; ΔUM j is the change frequency of functional module j; The complexity CM of functional module j j and the complexity CM of functional module i i Multiplication indicates the mutual influence between the complexity of the two modules. The higher the complexity of functional module j and functional module i, the greater the dependency between them. j With CM i Addition is used to normalize the comparison between complexities.
[0032] Furthermore, the historical change frequency correlation F(M i ,M j ) is larger, indicating that the mutual influence between the two modules is smaller. i ,M j ) is smaller, indicating that the mutual influence between the two modules is greater. The dependency D(M i ,M j ) is lower, indicating that the coupling between functional module i and functional module j is weaker, the independence and cohesion of the modules are better, and the dependency D(M) between functional module i and functional module j is i ,M j ) is higher, indicating that the coupling between functional module i and functional module j is stronger, and the degree of mutual dependence is higher. The modification of the module may cause a chain reaction and affect the stability of the system. The dependency D(M) between functional module i and functional module j is set. i ,M j ) has a dependency threshold of Y2. When D(M i ,M j )>Y2, it means that the dependency between functional module i and functional module j is too high, and the administrator is notified to handle it. When the dependency is too high, the direct dependency between modules can be reduced by introducing interfaces or abstract classes. The use of interfaces or abstract layers can make the interaction between modules looser and reduce direct dependency. Introducing intermediary layers between highly coupled modules, such as message queues and event buses, for communication and data exchange between modules can reduce direct interaction between modules and ultimately achieve the effect of reducing the dependency between modules.
[0033] Furthermore, the overall evaluation algorithm process in the dynamic adjustment step is as follows: ;
[0034] Where S is the overall software dependency; N is the number of functional modules; Software overall dependency R(M i ,M j ) is the interactive resource consumption between functional module i and functional module j; R max is the total amount of resources; θ is the resource consumption impact coefficient, ranging from 0 to 1; Specifically, the double summation symbol ensures that the dependency between each pair of functional modules can be calculated. The higher the overall software dependency S, the stronger the dependency between the software functional modules and the higher the potential coupling risk, so that the staff can intuitively understand the current overall software coupling situation. The adjustment threshold of the overall software dependency S is set to Y3. When the overall software dependency S is greater than the adjustment threshold Y3, it means that the overall software dependency is too high. At this time, the interaction weight β between functional module i and functional module j is increased. i,j , to avoid excessive coupling between modules in the system, the adjustment process is as follows: ;
[0035] where Xβ i,j is the interaction weight between the new functional module i and the functional module j; γ is the adjustment influence coefficient, ranging from 0 to 1; Specifically, when the overall software dependency S is too high, the interaction weight β between function module i and function module j is adjusted according to the amount of risk excess i,j , so that it can be dynamically adjusted according to the actual situation of the software, by increasing the interaction weight β between function module i and function module j i,j , which can eventually increase the results of the dependency algorithm, thereby improving the sensitivity of coupling detection between functional modules, further avoiding excessive coupling, reducing maintenance costs, and improving software flexibility and the accuracy of the dependency algorithm.
[0036] Furthermore, in the pre-modeling preparation step, the visual modeling tool is VisualParadigm, and the code generation modeling tool is JHipster.
[0037] The visual modeling tool VisualParadigm is suitable for supporting multiple views of software design, supports UML modeling, and can create various types of diagrams to help software modelers intuitively understand the software system structure during the design phase. It can display the contents of different views in a graphical way, especially computer software view models, which are suitable for this method.
[0038] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. A visual software modeling method for computer software views, characterized in that: The following steps are involved: Step S1: Pre-modeling preparation: select a visual modeling tool according to software requirements, and introduce a code generation modeling tool to automatically generate a software model based on the existing code base, and automatically update the software model when the code changes to ensure the consistency between the software model and the code; Step S2: modular modeling, subdividing the software model into multiple functional modules, each functional module is responsible for a specific function, each functional module is modeled and maintained separately, and the subdivided functional modules are visualized through UML diagrams; Step S3: Complexity evaluation: use the complexity evaluation algorithm to evaluate the complexity of each functional module, and determine whether the functional module needs to be optimized based on the result; Step S4: module dependency. After the software model is subdivided into multiple functional modules, the dependency between the functional modules is evaluated using a dependency algorithm, and based on the result, it is determined whether the functional modules need to be optimized to avoid excessive coupling between the functional modules. Step S5: Dynamic adjustment: evaluate the overall dependency of the functional modules through the overall evaluation algorithm, and quantify the results to obtain the overall software dependency S, so as to understand the overall software coupling situation, and set the adjustment threshold Y3 for the overall software coupling S, so as to determine whether to adjust the data in the dependency algorithm to improve the accuracy of the dependency algorithm; Step S6: Model verification. After the modeling of the software functional modules is completed, the reviewer reviews each functional module to ensure that the design meets the requirements and there are no omissions. After the review is passed, all modeling data and other relevant data are organized into system documents.
2. The visual software modeling method of computer software view according to claim 1, characterized in that: The complexity evaluation algorithm process is as follows: ； Among them, CM i is the complexity of functional module i; E k is the symbolic complexity of the kth subfunction in the functional module, which is obtained by the number of symbols, operands and expressions required by the subfunction; W k is the influence coefficient of the kth sub-function in the functional module, ranging from 0 to 1; h is the number of sub-functions; U k is the change frequency of the kth sub-function in the functional module; V k is the dynamic change frequency of the kth sub-function in the functional module; The complexity CM of functional module i i The larger the size, the more functions it includes, the higher the complexity, and the more resources need to be managed and maintained. Set the complexity CM of functional module i i The complexity threshold is Y1, when the complexity of functional module i is CM i >complexity threshold Y1, it means that functional module i is too complex and needs to be optimized. At this time, the management personnel are notified to handle it.
3. The visual software modeling method of computer software view according to claim 2, characterized in that: The dependency algorithm process is as follows: ； Where D(M i ,M j ) is the dependency between functional module i and functional module j; CM j is the complexity of functional module j; β i,j is the interaction weight between functional module i and functional module j; F(M i ,M j ) is the historical change frequency correlation between functional module i and functional module j; α is the historical change frequency influence coefficient, ranging from 0 to 1; F(M i ,M j ) The process is as follows: ； Where ΔUM i is the change frequency of functional module i; ΔUM j is the change frequency of functional module j; The historical change frequency correlation F(M) between function module i and function module j i ,M j ) is larger, indicating that the mutual influence between the two modules is smaller. i ,M j ) is smaller, indicating that the mutual influence between the two modules is greater. The dependency D(M i ,M j ) is lower, indicating that the coupling between functional module i and functional module j is weaker, the independence and cohesion of the modules are better, and the dependency D(M) between functional module i and functional module j is i ,M j ) is higher, indicating that the coupling between functional module i and functional module j is stronger, and the degree of mutual dependence is higher. The modification of the module may cause a chain reaction and affect the stability of the system. The dependency D(M) between functional module i and functional module j is set. i ,M j ) has a dependency threshold of Y2. When D(M i ,M j )>Y2, it indicates that the dependency between function module i and function module j is too high, and the administrator is notified to handle it.
4. The visual software modeling method of computer software view according to claim 3, characterized in that: The overall evaluation algorithm process in the dynamic adjustment step is as follows: ； Where S is the overall software dependency; N is the number of functional modules; Software overall dependency R(M i ,M j ) is the interactive resource consumption between functional module i and functional module j; R max is the total amount of resources; θ is the resource consumption impact coefficient, ranging from 0 to 1; The double summation symbol ensures that the dependency between each pair of functional modules can be calculated. The higher the overall software dependency S, the stronger the dependency between the software functional modules and the higher the potential coupling risk. The adjustment threshold of the overall software dependency S is set to Y3. When the overall software dependency S is greater than the adjustment threshold Y3, it means that the overall software dependency is too high. At this time, the interaction weight β between functional module i and functional module j is increased. i,j In order to avoid excessive coupling between modules in the system, the adjustment process is as follows: ； where Xβ i,j is the interaction weight between the new functional module i and the functional module j; γ is the adjustment influence coefficient, ranging from 0 to 1; When the overall software dependency S is too high, adjust the interaction weight β between function module i and function module j according to the amount of risk excess i,j , so that it can be dynamically adjusted according to the actual situation of the software, improving the flexibility of the software.
5. The visual software modeling method of computer software view according to claim 4, characterized in that: In the pre-modeling preparation step, the visual modeling tool is VisualParadigm, and the code generation modeling tool is JHipster.
6. The visual software modeling method of computer software view according to claim 1, characterized in that: In the modular modeling step, the visual display includes class diagrams, component diagrams, deployment diagrams, use case diagrams, activity diagrams, sequence diagrams, state diagrams and communication diagrams.
7. The visual software modeling method of computer software view according to claim 1, characterized in that: In the model verification step, after obtaining the system documentation, the system documentation is managed through a version control tool to ensure that historical versions can be traced back at different stages.
8. The visual software modeling method of computer software view according to claim 7, characterized in that: The version control tool is Git.