Intelligent application development method based on user intention

Abstract

The invention discloses an intelligent application development method based on user intention, and relates to the field of intelligent application development, and the method specifically comprises the following steps: step 1, establishing a data management platform for managing and storing application software data, step 2, analyzing various types of application software data in the data management platform, the method comprises the steps of (1) establishing a visual application software editor, (2) realizing basic development of application software by a developer based on the visual application software editor, (4) calculating a performance evaluation index of an initial application software model and determining a functional component which can cause the performance evaluation index to rise or fall, and (5) perfecting development of the application software based on an existing LLM model technology. 6, a developer confirms whether the application software is published or not by previewing the application software debugging effect, the development process of the application software is greatly simplified through the overall architecture design, the developer can rapidly build an application framework in a low-code mode, and meanwhile deep customization and optimization are conducted through an LLM provided by a platform.

Description

Technical Field

[0001] The present invention belongs to the technical field of application intelligent development, and specifically relates to an application intelligent development method based on user intention. Background Art

[0002] With the acceleration of digital transformation, enterprises have an increasing demand for rapid construction and iteration of application systems. Low-Code Development Platforms (LCDPs) have emerged to reduce the technical threshold of software development and accelerate the application delivery cycle through graphical interfaces and a small amount of code writing. However, although low-code development platforms have shown great potential in improving development efficiency, existing platforms still face many challenges in actual application, which limits their wide application and in-depth optimization in complex business scenarios.

[0003] Due to the limitations of platform architecture and component design, developers often find it difficult to deeply customize or expand components, which makes it difficult for developed applications to fully fit complex and ever-changing business logic and processes, limiting the flexibility and adaptability of applications. As the scale of applications expands and the number of users increases, the requirements for system performance are also increasing. However, the existing low-code development platforms for application software are difficult to improve the application construction of actual business scenarios due to their lack of flexibility, difficulty in performance optimization, and complex module coupling. The components provided by most platforms are difficult to deeply customize and optimize according to the specific application software types, making it difficult for developed applications to meet the needs of complex and ever-changing application scenarios. At the same time, existing platforms generally lack performance evaluation of application software in response to different numbers of users and large-scale request times. When faced with massive users and request data in the application field, performance bottlenecks and system response delays often occur. Summary of the invention

[0004] The purpose of the present invention is to provide an application intelligent development method based on user intention, which is used to solve the technical problems in the prior art that it is difficult to deeply expand components and lacks performance evaluation of application software.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] Step 1. Establish a data management platform for managing and storing application software data; establish a database containing various types of application software data, collect data from the public parts of various types of application software, provide API or Web interface for developers to upload private data related to the application software, verify the collected data to ensure the integrity and accuracy of the data, obtain various types of application software data, based on the standard provisions of application software data, the standard provisions refer to a series of specifications and guidelines for different types of application software formulated by industry authorities, eliminate some application software data that does not meet the standard provisions, classify the remaining application software data by type, and sort the application software data belonging to each type according to the number of users of the corresponding application software. Based on the content of each type of application software data, configure the data table structure of the corresponding application software in the database, upload the data table content to the data management platform, the data management platform parses and stores the data table content, and manages it through a visual page. The application software created by the application software developer supports software users to obtain and view the relevant data authorized by the developer to display.

[0007] Step 2: Analyze the data of various types of application software in the data management platform; analyze the application software itself based on the application software data, extract the front-end and back-end functional components of various types of application software, and divide them into main functional components and sub-functional components, where the sub-functional component refers to the function assigned to the component, which is an extension of the main functional component function. For example, in the e-commerce application software, product search belongs to the main functional component, and product photo search and product name search belong to the sub-functional component of product search. Analyze and compare the data of multiple application software of the same type, compare the main functional component occurrence frequency indexes of multiple application software of the same type, determine the main functional components that are necessary for the development of this type of application software as the main functional components, the main functional components with more occurrence frequency indexes are recorded as regular main functional components, and the main functional components with fewer occurrence frequency indexes are recorded as special main functional components. For n application software belonging to type a, ensure that the n application software complies with the norms, is representative, and keeps up to date in real time, count the number of main functional components of all application software as x, and mark the number corresponding to each main functional component, and obtain the main functional component set as {b1, b2, ..., b x}, the specific formula for comparing the frequency of occurrence index of functional components is as follows:

[0008]

[0009] Where x represents the number of the main functional component is x, F(x) represents the frequency of the functional component, n(x) represents that there are n(x) applications with the main functional component numbered x, i represents the i-th application software, m i represents the number of registered users of the i-th application software, i xAn application software representing a main functional component with number x.

[0010] Determine the functional component frequency thresholds as A and B, calculate the functional component frequency of each main functional component. When F(x) < A, it means the main functional component numbered x belongs to a special main functional component. When A ≤ F(x) < B, it means the main functional component numbered x belongs to a regular main functional component. When B ≤ F(x), it means the main functional component numbered x belongs to a main body functional component, where the functional component frequency thresholds A and B are determined according to the functional component frequency set. By determining the true values of A and B, obtain the number N of main body functional components, the number M of regular functional components, and the number L of special components, ensuring L < N < M and L + N > M.

[0011] Based on the data of the same type of application software, record all the extendable subordinate functional components of each main functional component. By calculating the functional component frequency of the subordinate functional components in each main functional component, divide the subordinate functional components within the extendable range of the main functional component. Use the division method for the frequency index of the main functional component appearance to divide the subordinate functional components into main body subordinate functional components, regular subordinate functional components, and special subordinate functional components in the same way, and record the associated logic configuration methods of all front-end functional components to establish different types of visual application software editors.

[0012] Step 3: Developers implement the basic development of the application software based on the visual application software editor; determine the type of application software that the developer needs to develop, select the corresponding visual editor for the application software type. Based on the main body functional components and the main body subordinate functional components, determine the application template for this type of application software. This application template is preset in the visual editor and includes all the main body functional components, main body subordinate functional components, and the configuration methods of the associated logic between the components in this type. Each type of visual editor provides an application template and a blank template for developers to choose and edit. The template page provides functions for adding, deleting, and layout design of functional components. Each functional component can only exist in one template. Developers drag and drop components for editing, place them in the layout, and configure the data source of the data management platform for the components to correspond to the data tables of the management platform, so as to display or input data. Developers configure the styles of each page according to personalized needs, such as the page theme color, the color matching of each component, the font size and color, etc. Developers configure the logic between pages and the associated logic between the parent page and the child page. Based on the visual application software editor, help developers complete the limitation of the application software functions and the design of the framework layout to obtain an initial application software model.

[0013] Step 4: Calculate the performance evaluation index of the initial application software model and determine the functional components that can cause the performance evaluation index to rise or fall; determine the simulation experiment target based on the application type of the initial application software model, and determine which functional components and configuration logic of the initial application software model will participate in the simulation based on the simulation experiment target. For example, for e-commerce type application software, the simulation experiment target is to evaluate the maximum average user request frequency or number of users that the application software model can withstand without affecting the response time, throughput and number of concurrent users. Based on the simulation experiment target, the product search functional component will participate in the simulation; use relevant simulation tools and platforms to simulate user behavior and system load, for example, use JMeter or LoadRunner simulation tools to simulate user behavior or system load; use H to represent the number of users of the initial application software model, the average request frequency of each user is O, set the average response time, throughput, and error rate as performance evaluation indicators, evaluate the performance of the initial application software model, and set the performance evaluation indicators within the simulation time as follows:

[0014]

[0015] Where T represents the average response time of user requests, represents, R represents the simulation time The throughput within, w represents the error rate. According to the simulation experiment objectives, the relevant variables in the performance evaluation indicators are adjusted to obtain the changes in the performance evaluation indicators for the simulation experiment objectives. For example: by gradually increasing the number of users or the request frequency, the operation of the initial application software under high load is simulated, and the changes in system performance are observed and recorded. The critical point when the performance begins to decline is obtained, and the performance limit of the initial application software model is determined; different slave functional components of this type are added or reduced respectively, and only one functional component is added or reduced each time. The functional component is a slave functional component or a main functional component without a slave functional component, and simulation is performed. Through the simulation experiment, the functional components that cause the performance evaluation indicators to decline in the initial application software model are screened out and recorded as replaceable components. The performance evaluation indicators of the initial application software model are calculated, and the performance evaluation indicators of the application software model after removing the replaceable components are compared. Price index, sort the replaceable components from large to small according to the improvement of performance evaluation index, and obtain the replaceable component sequence. Through simulation experiments, screen the functional components that are not in the initial application software model but have improved performance evaluation index after adding, record them as optimized components, calculate the performance evaluation index of the initial application software model and the performance evaluation index of the application software model after adding the optimized components, sort the optimized components from large to small according to the improvement of performance evaluation index, and obtain the optimized component sequence. Based on the replaceable component sequence and the optimized component sequence, randomly remove the replaceable components and add the optimized components to generate a random optimization scheme, calculate the performance evaluation index of the random optimization scheme, combine the functional consistency of the random optimization scheme with the initial application software model, and screen the best random optimization scheme. The calculation formula for the functional consistency of the random optimization scheme with the initial application software model is as follows:

[0016]

[0017] Where J represents the number of main functional components in the initial application software model, represents the number of components in the random optimization scheme that have the same or similar functions as the main functional components of the initial application software model, which are recorded as retained components. z represents the zth retained component. The main functional components that are the same or similar to z in the initial application software model are recorded as corresponding components. The zth retained component corresponds to the zth corresponding component. j(z) represents the number of subordinate functional components with the zth corresponding component. Represents the number of slave functional components that have the same or similar functions as the zth retained component and the corresponding component.

[0018] The performance evaluation index of the random optimization scheme is calculated using the formula YX(r)=I(r)[Y(r)-Y(0)]. The best random optimization scheme is screened based on the functional consistency between the random optimization scheme and the initial application software model, where r represents the rth random optimization scheme, Y(0) represents the performance evaluation index of the initial application software model, and Y(r) represents the performance evaluation index of the rth random optimization scheme. The random optimization scheme with the largest YX(r) value is selected as the best random optimization scheme.

[0019] Step 5. Develop application software based on the existing LLM model technology. Developers design and modify the application software model data and upload it to the big data management platform. The big data management platform supports software users to obtain and view the relevant data authorized by developers. The big data management platform embeds advanced LLM models, such as GPT and Codex. The API provided by the cloud service provider is used to access the model. The front-end interface is designed for developers, allowing developers to enter the requirement description and view the generated code suggestions. In the back-end, logic is written to process the developer input, call the LLM model API, receive the response, and perform post-processing, such as formatting the code and optimizing the output. By using asynchronous calls to the LLM model, LLM is improved. LM model response speed, collect sample codes and use cases of commonly used functional components and functional component sets of various application software types, and use them as a reference to help developers understand how to use the big data management platform. For the code written by themselves or obtained by developers through other channels, the big data management platform provides real-time syntax checking, error prompts and code running preview after the developer uploads the code, and designs an integrated breakpoint debugging function to allow developers to execute the code step by step, observe the status of variables, locate and solve problems, allow developers to rate and feedback on the code suggestions generated by LLM, collect users' evaluations on various aspects of the application software before it is released, regularly evaluate and optimize the response speed and code generation quality of the LLM model, and ensure the efficient operation of the LLM model.

[0020] Step 6. Developers preview and debug the application software to confirm whether to release the application software; input the code obtained or improved by the LLM model into the free code component area specified in the visual editor. The visual editor parses the input code and identifies the code format, such as HTML structure, CSS style and JavaScript logic. According to the parsing results, the editor automatically generates corresponding visual components on the visual editing interface. These components will display the corresponding appearance and functions according to the definition in the code. Developers preview the display effect of the components in the editor to ensure that each component meets the design requirements. The visual editor provides flexible layout tools, allowing developers to adjust the layout of components by dragging and zooming. Various operations will be reflected in the visual interface and code in real time. Based on the synchronization of code and visual interface, the visual editor will mark the components that are inconsistent with the code and visual interface to remind developers of inconsistencies. When developers are satisfied with the display effect of the application software in the visual editor, they can choose to publish the application software to the corresponding platform. For developers who are not satisfied with the display effect in the visual editor, additional configuration and optimization work needs to be performed on the application software until the developer is satisfied with the display effect of the application software.

[0021] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0022] 1. The present invention proposes an intelligent application development method based on user intention. By introducing a customizable LLM model and deployment framework, developers can flexibly build and optimize related modules according to specific application business needs, and the model generates code blocks and components based on specific business application scenarios, so that developers can quickly iterate and optimize the LLM model for specific business scenarios, and improve the flexibility and pertinence of application development.

[0023] 2. The present invention divides the functional component types of different types of application software based on the frequency of occurrence index, presets different application software templates according to the application type, uses the application software template as a reference template for developers to customize application software, and determines the most basic functions and operations of the application type through the application software template, so as to help developers who have little understanding of the application type to make innovative changes based on the application software template;

[0024] 3. The present invention simulates user behavior and system load by using relevant simulation tools and platforms, and realizes the performance evaluation of application software under different user behaviors and system loads by comprehensively considering average response time, throughput, and error rate. By adding or deleting different functional components on the basis of application software, the influence of each functional component on performance evaluation index is determined, thereby helping developers to adjust the functional component structure of application software. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 A step diagram of an application intelligent development method based on user intent is shown;

[0027] Figure 2 A functional flow chart of the low-code visual editor of the present invention is shown;

[0028] Figure 3 The functional flow chart of the LLM model of the present invention is shown. DETAILED DESCRIPTION

[0029] 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.

[0030] Example 1: Figure 1 , Figure 2 , Figure 3 As shown, this embodiment provides an application intelligent development method based on user intention, and the specific method steps include:

[0031] Step 1. Establish a data management platform for managing and storing application software data; establish a database containing various types of application software data, collect data from the public parts of various types of application software, provide API or Web interface for developers to upload private data related to the application software, verify the collected data to ensure the integrity and accuracy of the data, obtain various types of application software data, based on the standard provisions of application software data, the standard provisions refer to a series of specifications and guidelines for different types of application software formulated by industry authorities, eliminate some application software data that does not meet the standard provisions, classify the remaining application software data by type, and sort the application software data belonging to each type according to the number of users of the corresponding application software. Based on the content of each type of application software data, configure the data table structure of the corresponding application software in the database, upload the data table content to the data management platform, the data management platform parses and stores the data table content, and manages it through a visual page. The application software created by the application software developer supports software users to obtain and view the relevant data authorized by the developer to display.

[0032] Step 2: Analyze the data of various types of application software in the data management platform; analyze the application software itself based on the application software data, extract the front-end and back-end functional components of various types of application software, and divide them into main functional components and sub-functional components, where the sub-functional component refers to the function assigned to the component, which is an extension of the main functional component function. For example, in the e-commerce application software, product search belongs to the main functional component, and product photo search and product name search belong to the sub-functional component of product search. Analyze and compare the data of multiple application software of the same type, compare the main functional component occurrence frequency indexes of multiple application software of the same type, determine the main functional components that are necessary for the development of this type of application software as the main functional components, the main functional components with more occurrence frequency indexes are recorded as regular main functional components, and the main functional components with fewer occurrence frequency indexes are recorded as special main functional components. For n application software belonging to type a, ensure that the n application software complies with the norms, is representative, and keeps up to date in real time, count the number of main functional components of all application software as x, and mark the number corresponding to each main functional component, and obtain the main functional component set as {b1, b2, ..., b x}, the specific formula for comparing the frequency of occurrence index of functional components is as follows:

[0033]

[0034] Where x represents the number of the main functional component is x, F(x) represents the frequency of the functional component, n(x) represents that there are n(x) applications with the main functional component numbered x, i represents the i-th application software, m i represents the number of registered users of the i-th application software, i xAn application software representing a main functional component with number x.

[0035] Determine the functional component frequency thresholds as A and B, calculate the functional component frequency of each main functional component. When F(x) < A, it means the main functional component numbered x belongs to a special main functional component. When A ≤ F(x) < B, it means the main functional component numbered x belongs to a regular main functional component. When B ≤ F(x), it means the main functional component numbered x belongs to a main body functional component, where the functional component frequency thresholds A and B are determined according to the functional component frequency set. By determining the true values of A and B, obtain the number N of main body functional components, the number M of regular functional components, and the number L of special components, ensuring L < N < M and L + N > M.

[0036] Based on the data of the same type of application software, record all the extendable subordinate functional components of each main functional component. By calculating the functional component frequency of the subordinate functional components in each main functional component, divide the subordinate functional components within the extendable range of the main functional component. Use the division method of the appearance frequency index of the main functional component to divide the subordinate functional components into main body subordinate functional components, regular subordinate functional components, and special subordinate functional components in the same way, and record the associated logic configuration methods of all front-end functional components to establish different types of visual application software editors.

[0037] Step 3: Developers implement the basic development of the application software based on the visual application software editor; determine the type of application software that the developer needs to develop, select the corresponding visual editor for the application software type. Based on the main body functional components and the main body subordinate functional components, determine the application template for this type of application software. This application template is preset in the visual editor and includes all the main body functional components, main body subordinate functional components, and the configuration methods of the associated logic between the components in this type. Each type of visual editor provides an application template and a blank template for developers to select and edit. The template page provides functions for adding, deleting, and layout design of functional components. Each functional component can only exist in one template. Developers drag and drop the components for editing, place them in the layout, and configure the data source of the data management platform for the components to correspond to the data tables in the management platform, so as to display or input data. Developers configure the styles of each page according to personalized needs, such as the page theme color, the color matching of each component, the font size and color, etc. Developers configure the logic between pages and the associated logic between the parent page and the child page. Based on the visual application software editor, help developers complete the limitation of the application software function and the design of the framework layout to obtain the initial application software model.

[0038] Step 4: Calculate the performance evaluation index of the initial application software model and determine the functional components that can cause the performance evaluation index to rise or fall; determine the simulation experiment target based on the application type of the initial application software model, and determine which functional components and configuration logic of the initial application software model will participate in the simulation based on the simulation experiment target. For example, for e-commerce type application software, the simulation experiment target is to evaluate the maximum average user request frequency or number of users that the application software model can withstand without affecting the response time, throughput and number of concurrent users. Based on the simulation experiment target, the product search functional component will participate in the simulation; use relevant simulation tools and platforms to simulate user behavior and system load, for example, use JMeter or LoadRunner simulation tools to simulate user behavior or system load; use H to represent the number of users of the initial application software model, the average request frequency of each user is O, set the average response time, throughput, and error rate as performance evaluation indicators, evaluate the performance of the initial application software model, and set the performance evaluation indicators within the simulation time as follows:

[0039]

[0040] Where T represents the average response time of user requests, represents, R represents the simulation time The throughput within, w represents the error rate. According to the simulation experiment objectives, the relevant variables in the performance evaluation indicators are adjusted to obtain the changes in the performance evaluation indicators for the simulation experiment objectives. For example: by gradually increasing the number of users or the request frequency, the operation of the initial application software under high load is simulated, and the changes in system performance are observed and recorded. The critical point when the performance begins to decline is obtained, and the performance limit of the initial application software model is determined; different slave functional components of this type are added or reduced respectively, and only one functional component is added or reduced each time. The functional component is a slave functional component or a main functional component without a slave functional component, and simulation is performed. Through the simulation experiment, the functional components that cause the performance evaluation indicators to decline in the initial application software model are screened out and recorded as replaceable components. The performance evaluation indicators of the initial application software model are calculated, and the performance evaluation indicators of the application software model after removing the replaceable components are compared. Price index, sort the replaceable components from large to small according to the improvement of performance evaluation index, and obtain the replaceable component sequence. Through simulation experiments, screen the functional components that are not in the initial application software model but have improved performance evaluation index after adding, record them as optimized components, calculate the performance evaluation index of the initial application software model and the performance evaluation index of the application software model after adding the optimized components, sort the optimized components from large to small according to the improvement of performance evaluation index, and obtain the optimized component sequence. Based on the replaceable component sequence and the optimized component sequence, randomly remove the replaceable components and add the optimized components to generate a random optimization scheme, calculate the performance evaluation index of the random optimization scheme, combine the functional consistency of the random optimization scheme with the initial application software model, and screen the best random optimization scheme. The calculation formula for the functional consistency of the random optimization scheme with the initial application software model is as follows:

[0041]

[0042] Where J represents the number of main functional components in the initial application software model, represents the number of components in the random optimization scheme that have the same or similar functions as the main functional components of the initial application software model, which are recorded as retained components. z represents the zth retained component. The main functional components that are the same or similar to z in the initial application software model are recorded as corresponding components. The zth retained component corresponds to the zth corresponding component. j(z) represents the number of subordinate functional components with the zth corresponding component. Represents the number of slave functional components that have the same or similar functions as the zth retained component and the corresponding component.

[0043] The performance evaluation index of the random optimization scheme is calculated using the formula YX(r)=I(r)[Y(r)-Y(0)]. The best random optimization scheme is screened based on the functional consistency between the random optimization scheme and the initial application software model, where r represents the rth random optimization scheme, Y(0) represents the performance evaluation index of the initial application software model, and Y(r) represents the performance evaluation index of the rth random optimization scheme. The random optimization scheme with the largest YX(r) value is selected as the best random optimization scheme.

[0044] Step 5. Develop application software based on the existing LLM model technology. Developers design and modify the application software model data and upload it to the big data management platform. The big data management platform supports software users to obtain and view the relevant data authorized by developers. The big data management platform embeds advanced LLM models, such as GPT and Codex. The API provided by the cloud service provider is used to access the model. The front-end interface is designed for developers, allowing developers to enter the requirement description and view the generated code suggestions. In the back-end, logic is written to process the developer input, call the LLM model API, receive the response, and perform post-processing, such as formatting the code and optimizing the output. By using asynchronous calls to the LLM model, LLM is improved. LM model response speed, collect sample codes and use cases of commonly used functional components and functional component sets of various application software types, and use them as a reference to help developers understand how to use the big data management platform. For the code written by themselves or obtained by developers through other channels, the big data management platform provides real-time syntax checking, error prompts and code running preview after the developer uploads the code, and designs an integrated breakpoint debugging function to allow developers to execute the code step by step, observe the status of variables, locate and solve problems, allow developers to rate and feedback on the code suggestions generated by LLM, collect users' evaluations on various aspects of the application software before it is released, regularly evaluate and optimize the response speed and code generation quality of the LLM model, and ensure the efficient operation of the LLM model.

[0045] Step 6. Developers preview and debug the application software to confirm whether to release the application software; input the code obtained or improved by the LLM model into the free code component area specified in the visual editor. The visual editor parses the input code and identifies the code format, such as HTML structure, CSS style and JavaScript logic. According to the parsing results, the editor automatically generates corresponding visual components on the visual editing interface. These components will display the corresponding appearance and functions according to the definition in the code. Developers preview the display effect of the components in the editor to ensure that each component meets the design requirements. The visual editor provides flexible layout tools, allowing developers to adjust the layout of components by dragging and zooming. Various operations will be reflected in the visual interface and code in real time. Based on the synchronization of code and visual interface, the visual editor will mark the components that are inconsistent with the code and visual interface to remind developers of inconsistencies. When developers are satisfied with the display effect of the application software in the visual editor, they can choose to publish the application software to the corresponding platform. For developers who are not satisfied with the display effect in the visual editor, additional configuration and optimization work needs to be performed on the application software until the developer is satisfied with the display effect of the application software.

[0046] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0047] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for intelligent application development based on user intent, characterized in that: include: Step 1: Establish a data management platform for managing and storing application software data; Step 2: Analyze the data of various types of application software in the data management platform; extract the front-end and back-end functional components of various types of application software, divide them into main functional components and sub-functional components, analyze and compare the data of multiple application software of the same type, compare the frequency index of functional components of multiple application software of the same type, and divide the types of functional components according to the frequency index; Step 3: Developers implement basic application software development based on the visual application software editor; Step 4: Calculate the performance evaluation index of the initial application software model and determine the functional components that can cause the performance evaluation index to rise or fall; determine the simulation experiment target based on the application type of the initial application software model, determine the functional components and configuration logic of the initial application software model involved in the simulation based on the simulation experiment target, set the performance evaluation index within the simulation time, adjust the relevant variables in the performance evaluation index according to the simulation experiment target, and obtain the change of the performance evaluation index about the simulation experiment target; Step 5: Development of improved application software based on existing LLM model technology; Step 6: The developer previews and debugs the application to confirm whether to release the application.

2. According to claim 1, a user intention-based application intelligent development method is characterized in that: Establish a data management platform for managing and storing application software data by: The application software data is classified by type, and the application software data belonging to each type is sorted according to the number of users of the corresponding application software.

3. According to the user intention-based application intelligent development method of claim 1, it is characterized in that: Divided into main functional components and slave functional components, the specific method is: Based on the application software data, the functional components are classified according to the main functions and subordinate functions, and the functional components are distinguished by main functional components and subordinate functional components. The subordinate functional component refers to a component whose function is an extension of the function assigned to the main functional component. The importance levels of different categories of functional components are determined based on the frequency indicators of different categories of functional components in various types of application software.

4. According to claim 3, a user intention-based application intelligent development method is characterized in that: Based on the occurrence frequency index of different categories of functional components in various types of application software, the importance level of different categories of functional components is determined. The specific method is as follows: Analyze and compare the data of multiple application software of the same type, and compare the frequency of occurrence indicators of functional components of multiple application software of the same type; For n application software of type a, ensure that the n application software complies with the norms, is representative, and keeps up to date. Count the number of main functional components of all application software or the number of subordinate functional components of a main functional component as x, and mark the corresponding number of each functional component. The functional component set is {b1, b2, ..., b x }, through the formula Determine the frequency index of the functional component, where x represents the number of the functional component x, F(x) represents the frequency index of the functional component in n application software, n(x) represents that there are n(x) application software with the functional component numbered x, i represents the i-th application software, m i represents the number of registered users of the i-th application software, i x Represents application software with a functional component numbered x. The frequency of occurrence of different functional components of the same type is calculated through a formula to determine the importance levels of functional components of different categories.

5. According to claim 4, a method for intelligent application development based on user intention, characterized in that: Determine the importance level of different categories of functional components. The specific method is: Calculate the occurrence frequency index of all functional components in multiple application software of the same type. Compare functional components of the same category with those of the same category, and determine the occurrence frequency index thresholds of the functional components as A and B. Calculate the occurrence frequency index of each functional component. When F(x) < A, it means that the functional component numbered x belongs to a special functional component. When A ≤ F(x) < B, it means that the functional component numbered x belongs to a regular functional component. When B ≤ F(x), it means that the functional component numbered x belongs to a main functional component or a main sub-functional component. Among them, the occurrence frequency index thresholds A and B of the functional components are determined according to the set of occurrence frequency indexes of the functional components. By determining the true values of A and B, obtain the number N of the main functional components or the main sub-functional components, the number M of the regular functional components, and the number L of the special components, ensuring that L < N < M and L + N > M.

6. According to claim 1, a method for intelligent application development based on user intention, characterized in that: Calculate the performance evaluation index of the initial application software model. The specific method is as follows: Based on the application type of the initial application software model, determine the simulation experiment objective. Based on the simulation experiment objective, determine the functional components of the initial application software model participating in the simulation. Simulate user behavior and system load based on relevant simulation tools and platforms. Obtain the performance evaluation index of the initial application software model by synthesizing the number of users, the average request frequency of users, the average response time, the throughput, and the error rate of the initial application software model. According to the simulation experiment objective, adjust the relevant variables in the performance evaluation index to obtain the change situation of the performance evaluation index for the simulation experiment objective.

7. The method for intelligent application development based on user intent according to claim 6, characterized in that: Obtain the performance evaluation index of the initial application software model by synthesizing the number of users, the average request frequency of users, the average response time, the throughput, and the error rate of the initial application software model. The specific method is as follows: By formula Determine the performance evaluation index of the initial application software model, where T represents the average response time of user requests, H represents the number of users of the initial application software model, O represents the average request frequency of each user, and T k represents the response time of the kth user request, N represents the total number of user requests, R represents the throughput within the simulation time T, and w represents the error rate. According to the simulation experiment objectives, the relevant variables in the performance evaluation indicators are adjusted to obtain the changes in the performance evaluation indicators related to the simulation experiment objectives.

8. The method for intelligent application development based on user intent according to claim 1, characterized in that: Determine the functional components that can cause the performance evaluation index to increase or decrease. The specific method is as follows: Add or remove different sub-functional components of this type respectively. Only add or remove one functional component each time. This functional component is a sub-functional component or a main functional component without a sub-functional component, and conduct a simulation. Through the simulation experiment, screen out the functional components in the initial application software model that cause the performance evaluation index to decrease, and record them as replaceable components. Calculate the performance evaluation index of the initial application software model and the performance evaluation index of the application software model after removing the replaceable components. Sort the replaceable components in descending order according to the increase in the performance evaluation index to obtain the replaceable component sequence. Through the simulation experiment, screen out the functional components that are not in the initial application software model but whose performance evaluation index increases after adding, and record them as optimized components. Calculate the performance evaluation index of the initial application software model and the performance evaluation index of the application software model after adding the optimized components. Sort the optimized components in descending order according to the increase in the performance evaluation index to obtain the optimized component sequence. Based on the replaceable component sequence and the optimized component sequence, randomly remove the replaceable components and add the optimized components to generate a random optimization plan. Calculate the performance evaluation index of the random optimization plan, and combine the random optimization plan with the functional consistency of the initial application software model to screen out the best random optimization plan.

9. The method for intelligent application development based on user intent according to claim 8, characterized in that: Calculate the performance evaluation index of the random optimization scheme, combine the functional consistency of the random optimization scheme with the initial application software model, and select the best random optimization scheme. The specific method is as follows: Using the formula Determine functional consistency, where J represents the number of main functional components in the initial application software model, represents the number of components in the random optimization scheme that have the same or similar functions as the main functional components of the initial application software model, which are recorded as retained components. z represents the zth retained component. The main functional components that are the same or similar to z in the initial application software model are recorded as corresponding components. The zth retained component corresponds to the zth corresponding component. j(z) represents the number of subordinate functional components with the zth corresponding component. represents the number of slave functional components with the same or similar functions as the zth retained component and the corresponding component; The performance evaluation index of the random optimization scheme is calculated using the formula YX(r)=I(r)[Y(r)-Y(0)]. The best random optimization scheme is selected by combining the functional consistency of the random optimization scheme with the initial application software model. r represents the rth random optimization scheme, Y(0) represents the performance evaluation index of the initial application software model, Y(r) represents the performance evaluation index of the rth random optimization scheme, and the random optimization scheme with the largest YX(r) value is selected as the best random optimization scheme.

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