Software simulation method and device
The software simulation method breaks down complex manufacturing tasks into manageable steps using a pre-trained model, enhancing simulation clarity, precision, and reliability by visually tracking and correcting errors.
Patent Information
- Application Number
- CN202510389226.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-28
- Publication Date
- 2025-07-15
AI Technical Summary
Existing software automation solutions are difficult to effectively implement complex software simulation tasks in the manufacturing industry, especially in complex operation interfaces and multi-step operation processes. It is difficult for UI understanding modules to accurately capture UI elements, and there is a lack of a clear mechanism for task disassembly and execution results.
By obtaining the simulation task information of the target software, using pre-trained large models to disassemble the simulation task, identifying the simulation target and dependencies, generating user interface elements, and monitoring the simulation process, providing historical data reference and real-time optimization.
It improves the accuracy and efficiency of simulation, reduces the difficulty and complexity of simulation, enhances the controllability and reliability of simulation, and supports real-time optimization and problem discovery.
Smart Images
Figure CN120316004A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of software testing technologies, and in particular, to a software simulation method and apparatus. Background Art
[0002] In the manufacturing industry, operators use various industrial software for analysis, simulation, design, and testing, which includes a large number of computer control tasks with clear process specifications and goals. These computer control tasks are implemented through software automation operations. Due to the large-scale system engineering involving multiple complex links, existing software automation is difficult to implement.
[0003] It should be noted that the above introduction to the technical background is only for the convenience of clearly and completely explaining the technical solutions of this application and facilitating the understanding of those skilled in the art. It cannot be considered that the above technical solutions are well-known to those skilled in the art just because these solutions are described in the background art section of this application. Summary of the Invention
[0004] An object of this application is to solve at least one of the technical problems in the related technologies to a certain extent.
[0005] To this end, a first object of this application is to propose a software simulation method.
[0006] A second object of this application is to propose a software simulation apparatus.
[0007] A third object of this application is to propose an electronic device.
[0008] A fourth object of this application is to propose a computer-readable storage medium.
[0009] A fifth object of this application is to propose a computer program product.
[0010] To achieve the above object, an embodiment of the first aspect of this application proposes a software simulation method, including:
[0011] In response to an input operation, obtaining simulation task information of a target software; wherein, the simulation task information is used to indicate a simulation target and simulation tasks to be executed for the simulation target;
[0012] Displaying a simulation process of the target software, wherein the simulation process includes at least one simulation step obtained by disassembling the simulation tasks based on historical data related to the simulation target and the simulation tasks.
[0013] To achieve the above object, an embodiment of the second aspect of this application proposes a software simulation apparatus, including:
[0014] An acquisition module, which is configured to acquire simulation task information of a target software in response to an input operation; wherein, the simulation task information is used to indicate a simulation target and simulation tasks to be executed for the simulation target.
[0015] A display module, which is configured to display the simulation process of the target software, wherein the simulation process includes at least one simulation step obtained by disassembling the simulation tasks based on the simulation target and historical data related to the simulation tasks.
[0016] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: a processor; a memory for storing executable instructions of the processor; wherein, the processor is configured to execute the instructions to implement the software simulation method provided in the embodiment of the first aspect of the present application.
[0017] To achieve the above object, an embodiment of the fourth aspect of the present application provides a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the method provided in the embodiment of the first aspect of the present application.
[0018] To achieve the above object, an embodiment of the fifth aspect of the present application provides a computer program product, including a computer program, which implements the method provided in the embodiment of the first aspect of the present application when executed by a processor in a communication device.
[0019] The software simulation method and device provided by the present application.
[0020] In the embodiments of the present application, by acquiring simulation task information through an input operation, it can ensure that users or systems have a clear understanding of the simulation target, which helps to concentrate resources in subsequent steps and perform efficient simulations for specific targets; based on the simulation task information, it helps to refine the simulation process and ensure that each step meets the preset simulation target and requirements; based on the historical data related to the simulation target and simulation tasks, it can provide valuable reference and reference for the current simulation, thereby improving the accuracy and efficiency of the simulation; disassembling complex simulation tasks into smaller tasks that are easier to manage and execute reduces the difficulty and complexity of the simulation; the display of the simulation process enables users or systems to intuitively understand the progress and status of the simulation, which helps to promptly discover and solve problems that may occur during the simulation process, improving the controllability and reliability of the simulation; by displaying the simulation process, users or systems can make more accurate optimization strategies based on real-time data, and at the same time help to indicate sharing and deep learning.
[0021] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. Description of the Drawings
[0022] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of embodiments in conjunction with the accompanying drawings, where:
[0023] Figure 1 It is a schematic flowchart of a software simulation method provided by an embodiment of the present application;
[0024] Figure 2 It is a schematic flowchart of another software simulation method provided by an embodiment of the present application;
[0025] Figure 3 It is a schematic flowchart of another software simulation method provided by an embodiment of the present application;
[0026] Figure 4 It is a schematic structural diagram of a software simulation device provided by an embodiment of the present application;
[0027] Figure 5 It is a schematic structural diagram of an electronic device provided according to an embodiment of the present application;
[0028] Figure 6 It is a schematic structural diagram of another electronic device provided according to an embodiment of the present application. Detailed implementation manners
[0029] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the embodiments of the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.
[0030] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms "a" and "the" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0031] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "when" as used herein may be interpreted as "when...", "when...", or "in response to a determination".
[0032] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.
[0033] In the manufacturing industry, such as automotive manufacturing, engineers use various industrial software for computer control tasks mainly in two directions: an automation script solution based on manually written scripts, which often writes a large amount of script code for specific tasks and scenarios and executes the tasks by compiling the script code; an automation script generation solution based on large models to execute tasks.
[0034] In some embodiments, the automation script generation solution based on large models is divided into three major modules: a user interface (UI) understanding module, whose function is to identify and extract user interaction elements and their position coordinates in an image. Among them, user interaction elements include text, icons, and colors. After these elements are input to the large model and filtered, a part most relevant to the current task is left, simplifying the subsequent model input; a prompt generation module, which includes five major parts: responsibilities, function templates, examples, UI elements, and tasks. Among them, according to the current task, corresponding responsibilities, function templates, and examples are written, and the result output in the previous step is filled into the UI element part; a script generation module, which uses the prompt as the input to the large model and requests it to generate script code capable of completing the target task.
[0035] Although the automated script generation solution based on large models is more user-friendly than scripts written by users themselves and reduces the reliance on software interfaces, for complex manufacturing environments, such as the complex software control interfaces required in automotive manufacturing, the single-step generation method formed by the automated script generation solution of large models is difficult to complete tasks that require long-term planning. As an example, during the process of conducting a door strength simulation experiment, it often requires multiple delicate operations to successfully complete a comprehensive simulation analysis. Specifically, this complex process includes carefully selecting 100 key anti-denting points within the anti-denting area as the objects of investigation; subsequently, based on these selected points, an anti-denting head file needs to be generated and imported into the large model one by one to thoroughly check for any possible interference and penetration situations; in order to ensure that the state of each indenter is accurately recorded and analyzed, separate files also need to be generated for them and these files are submitted to the computing system for in-depth computational analysis. Only in this way can a door strength simulation experiment be successfully completed.
[0036] In summary, the main limitations of the automated script generation solution based on large models are as follows: for complex operation interfaces such as industrial software, the UI understanding module may not be able to accurately capture the UI elements required for the current task; for processes that require multiple steps of operation, it is difficult for large models to understand the task objectives and break down tasks according to the task objectives; for the execution results of each step, large models lack a mechanism for judging the correctness of script execution, and there is no clear correction path for execution errors.
[0037] Next, the software simulation method and its device according to the embodiments of the present application will be described with reference to the accompanying drawings.
[0038] Figure 1 It is a flowchart showing the process of a software simulation method provided by an embodiment of the present application.
[0039] As shown in Figure 1 the method includes but is not limited to the following steps:
[0040] S101, in response to an input operation, obtain simulation task information of the target software; wherein, the simulation task information is used to indicate the simulation target and the simulation tasks to be executed for the simulation target.
[0041] In a feasible implementation manner, the target software is a software that needs to be simulated currently.
[0042] In a feasible implementation manner, the input operation can be generated based on the real-time operation behavior of the user on the operation interface of the target software, and the input operation can be some recorded user operation behaviors.
[0043] In a feasible implementation manner, the input operations may include, but are not limited to: operations on UIs (such as buttons, text boxes, drop-down menus, etc.) on the operation interface of the target software, input requests for the command-line interface of the target software, and the like.
[0044] In a feasible implementation manner, the information included in the input operations can be used to identify the simulation target and the type of simulation task required. Among them, the simulation target can be to verify or optimize the performance indicators of the target software, such as response time, throughput, resource utilization, etc.; the simulation target can also be the behavioral performance indicators of the target software. For the ANSA software, its behavioral performance indicators can be: the accuracy rate of importing geometric figures, the success rate of performing the mesh generation task, and whether the results after the mesh generation task meet the expectations.
[0045] S102. Display the simulation process of the target software, where the simulation process includes at least one simulation step obtained by disassembling the simulation task based on the historical data related to the simulation target and the simulation task.
[0046] In a feasible implementation manner, after obtaining the simulation task information, the simulation task can be executed on the target software based on the simulation task information, and the progress and status of the task can be monitored during the execution of the simulation task. First, identify that for complex simulation tasks, there may be multiple operation processes. It can be understood that multiple operation processes often involve multiple subtasks and simulation targets, and there may be complex dependencies between these subtasks and simulation targets. By identifying this dependency, the simulation task is disassembled. Among them, according to the simulation target, the simulation requirements can be analyzed. The simulation requirements include: the required physical or mathematical models, computational resource consumption, etc.; then based on the simulation requirements, determine the data, behavioral performance indicators, result verification mechanism, etc. required for each simulation step, and then disassemble the simulation task to obtain multiple simulation steps.
[0047] In summary, the software simulation method provided by the embodiments of the present application can ensure that users or systems have a clear understanding of the simulation target by obtaining simulation task information through input operations, which helps to concentrate resources in subsequent steps and perform efficient simulation for specific targets; based on the simulation task information, it helps to refine the simulation process and ensure that each step meets the preset simulation objectives and requirements; based on the historical data related to the simulation target and simulation tasks, it can provide valuable references and lessons for the current simulation, thereby improving the accuracy and efficiency of the simulation; decomposing complex simulation tasks into smaller tasks that are easier to manage and execute reduces the difficulty and complexity of the simulation; the display of the simulation process enables users or systems to intuitively understand the progress and status of the simulation, which helps to promptly discover and solve possible problems in the simulation process and improve the controllability and reliability of the simulation; by displaying the simulation process, users or systems can make more accurate optimization strategies based on real-time data, and at the same time, it helps to indicate sharing and deep learning.
[0048] Figure 2 FIG. is a schematic flowchart of another software simulation method provided by the embodiments of the present application.
[0049] As Figure 2 shown, the method includes but is not limited to the following steps:
[0050] S201, in response to an input operation, obtain simulation task information of the target software.
[0051] In a feasible implementation manner, clarify the target of the target software simulation; according to the target, determine the physical phenomena or system behaviors that need to be simulated; next, identify the input data required for the simulation task, such as model attributes, boundary conditions, etc.; according to the input data, determine the simulation process, including the initialization of the model, the setting of the simulation time, the selection of the simulation step size, the recording of the simulation results, etc.; determine the output of the simulation results. Further, summarize the above content as the simulation task information of the target software.
[0052] In a feasible implementation manner, in order to obtain the simulation target and the required simulation task type, the input operation can be submitted to the target large model, and the target large model performs action planning and task reasoning to obtain the simulation task information of the target software. Since the target large model can be a pre-trained deep learning model, a machine learning model, or other types of complex computing models, substitute the input operation into the target large model to obtain the simulation task information related to the simulation target. Among them, the input operation is usually passed to the input layer of the target large model and waits for the large model to output the simulation task information.
[0053] In a feasible implementation, the output simulation task information may be one or more feature vectors, probability distributions, text descriptions, or other forms of data. Then, according to the output format of the target large model and the expected simulation task information, appropriate post-processing can be performed, including: checking whether the simulation task information obtained from the target large model is complete, accurate, and meets the expectations. If the information is incomplete or there are errors, it may be necessary to query the target large model again or perform error handling; converting the obtained simulation task information into a form that can be understood by the user. As an example, appropriate UI elements (such as pop-up windows, tables, icons, etc.) or output command-line interfaces (such as print statements, file outputs, etc.) can be used to display the formatted simulation task information to the user.
[0054] S202, determine the simulation target by the pre-trained target large model according to the historical data related to the simulation task and the simulation task information.
[0055] In a feasible implementation, prompt words for the target large model can be generated according to the historical data related to the simulation task and the simulation task information. Among them, the target large model is obtained by training the large model based on the pre-configured prompt word template and reference examples of the large model, and combined with structured sample data. As an example, this large model can be a large multimodal model (Large Multimodal Models, that is, LMM large model), and the structured sample data is obtained based on the structured processing of the sample data, and / or the sample data is obtained based on the historical data related to multiple historical simulation tasks.
[0056] Furthermore, as an example, the sample data includes at least one of visual information elements and text information associated with the visual information elements, where the visual information elements are obtained by screening the sample historical data related to the historical simulation task; and / or the text information is obtained by character recognition of the visual information elements.
[0057] As an example, the prompt word template includes the information after structuring the requirements of the simulation task and the specific operation content associated with the requirements, where the requirements are obtained based on the business background of the target software simulation task.
[0058] As an example, the reference examples include the execution actions of the target software and the execution targets associated with the execution actions, where the execution actions are obtained based on the requirements of the target software simulation task.
[0059] As an example, structured reference information can be obtained by structuring historical data related to the simulation task and simulation task information. Then, based on the association between the structured reference information and the prompt template, at least one of the local objectives of the simulation task (this local objective focuses on the specific operations and execution details during the simulation process and is the refinement of the simulation objective in specific implementation), the conditions required to achieve the local objective, and the expected results of the simulation task is generated; furthermore, at least one of the local objective, conditions, and expected results is determined as the prompt for the target large model.
[0060] In a feasible implementation manner, the prompt can be input into the target large model, and the target large model determines the user interface elements required for the simulation task based on the prompt. Among them, the target large model can parse the simulation task based on the prompt to obtain multiple simulation steps corresponding to the simulation task and the output content format expected by the simulation steps. For complex simulation tasks including multi-step operation processes, the target large model can understand the dependency relationship between sub-tasks and simulation objectives in the complex simulation task; according to the understanding result, determine the order between sub-tasks; perform structured processing on each simulation step and output content format based on the pre-configured output reference example to obtain at least one of titles and paragraphs, menus and links, and notifications and instructions; determine at least one of titles and paragraphs, menus and links, and notifications and instructions as the user interface elements required for the simulation task.
[0061] After obtaining the user interface elements required for the simulation task, the user interface elements are determined as the simulation objective.
[0062] S203, the target large model disassembles the simulation task required to be executed for the simulation objective to obtain the simulation process of the target software.
[0063] In a feasible implementation manner, the target large model disassembles the simulation task into a series of specific sub-tasks based on the simulation objective. These sub-tasks include: determining the corresponding model parameters and establishing the model structure according to the constraints of the target large model; collecting various data required for the simulation, such as input data and verification data; performing the simulation task according to the boundary conditions, initial conditions, solution selection, etc. of the simulation task, and during the simulation process, debugging and optimizing the target large model to ensure the accuracy and reliability of the simulation results; analyzing and evaluating the simulation results to verify whether the simulation objective is achieved.
[0064] In a feasible implementation, since the target large model has been pre-trained, it has professional knowledge in a specific field or industry, so it can accurately understand the simulation target and correct possible deviations and errors during the process of disassembling the simulation task. The multi-step operation process in the simulation task is often in a dynamically changing environment, and the simulation target, steps, and conditions may all change over time. By combining the historical data related to the simulation task, the target large model learns to adapt to these changes.
[0065] In a feasible implementation, in the multi-step operation process, the target large model identifies the key steps of the simulation process, obtains the dependency relationship of the entire process based on the key steps, and then determines the step sequence. Through historical data, identify the simulation results of the target software in different scenarios and use them as references and comparisons. Then, by setting time steps, boundary conditions, output variables, etc., monitor each simulation step obtained from the disassembly of the simulation task, and collect simulation data; perform post-processing on the simulation results, extract key indicators; compare the simulation results with the expected target, evaluate the performance of the simulation object of the target software, analyze potential problems found in the simulation, and propose improvement suggestions.
[0066] In a feasible implementation, display the simulation process of the target software, and monitor at least one of the parameter indicators related to the simulation target and the simulation results during the simulation process.
[0067] If it is determined that the simulation fails based on at least one of the parameter indicators and the simulation results, obtain failure information, and update the prompt words based on the failure information. The failure information may include: the abnormal simulation steps and / or deviation values that cause the simulation to fail; the deviation value is obtained based on the simulation target and the simulation results corresponding to the abnormal simulation steps.
[0068] If it is determined that the simulation is successful based on at least one of the parameter indicators and the simulation results, annotate the simulation steps, and obtain a screenshot of the annotated test steps, and store the screenshot as historical data related to the simulation task.
[0069] In summary, for the software simulation method provided by the embodiments of the present application, in the embodiments of the present application, by obtaining simulation task information through input operations, it is possible to ensure that users or systems have a clear understanding of the simulation target, which helps to concentrate resources in subsequent steps and perform efficient simulation for specific targets; based on the simulation task information, it helps to refine the simulation process and ensure that each step meets the preset simulation objectives and requirements; based on the historical data related to the simulation target and simulation tasks, it can provide valuable references and lessons for the current simulation, thereby improving the accuracy and efficiency of the simulation; decomposing complex simulation tasks into smaller tasks that are easier to manage and execute reduces the difficulty and complexity of the simulation; the display of the simulation process enables users or systems to intuitively understand the progress and status of the simulation, which helps to timely discover and solve problems that may occur during the simulation process and improve the controllability and reliability of the simulation; by showing the simulation process, users or systems can make more accurate optimization strategies based on real-time data, and at the same time it helps to indicate sharing and deep learning.
[0070] Figure 3 It is a schematic flowchart of another software simulation method provided by the embodiments of the present application.
[0071] As Figure 3 shown, the method includes but is not limited to the following steps:
[0072] S301, Generate prompts for the target large model according to the historical data related to the simulation task and the simulation task information.
[0073] S302, Input the prompts into the target large model, and the target large model determines the simulation target based on the prompts.
[0074] S303, In response to the input operation for the target software, obtain the simulation task information of the target software according to the simulation target and the simulation tasks required to be executed for the simulation target.
[0075] S304, Based on the simulation task information, the target large model performs simulation planning and displays the simulation process of the target software, where the simulation process includes at least one simulation step obtained by decomposing the simulation tasks based on the historical data related to the simulation target and the simulation tasks.
[0076] S305, Monitor at least one of the parameter indicators related to the simulation target and the simulation results during the simulation process.
[0077] S306, If it is determined that the simulation fails based on at least one of the parameter indicators and the simulation results, obtain the failure information and update the prompts based on the failure information.
[0078] In S307, if it is determined that the simulation is successful based on at least one of the parameter indicators and the simulation results, label the simulation steps, obtain a screenshot of the labeled simulation test steps, and store the screenshot as historical data related to the simulation task.
[0079] For further specific introductions of steps S301 to S307, reference can be made to the relevant content recorded in the above embodiments, which will not be elaborated here.
[0080] As an example, select the ANSA software (used for geometric processing) as the target software, select the pre-trained LMM large model as the target large model, select mesh generation as the simulation task, use the geometric graphics file (such as a vehicle structure diagram) as the input information, and use the mesh generation of the geometric graphics as the simulation target. Generate a prompt for the target large model based on the historical data and simulation task information related to the simulation task; input the prompt into the target large model, and the target large model determines the user interface elements required for the simulation task based on the prompt; monitor at least one of the parameter indicators related to the simulation target and the simulation results during the simulation process; if the mesh generation (simulation target) fails, refine the prompt based on the obtained failure information; if the mesh generation is successful, label the simulation steps, obtain a screenshot of the labeled simulation test steps, and store the screenshot as the historical data related to the simulation task.
[0081] In summary, for the software simulation method provided by the embodiments of the present application, in the embodiments of the present application, obtaining simulation task information through input operations can ensure that users or systems have a clear understanding of the simulation target, which helps to concentrate resources in subsequent steps and perform efficient simulations for specific targets; based on the simulation task information, it helps to refine the simulation process and ensure that each step meets the preset simulation targets and requirements; based on the simulation target and the historical data related to the simulation task, it can provide valuable references and references for the current simulation, thereby improving the accuracy and efficiency of the simulation; decomposing complex simulation tasks into smaller tasks that are easier to manage and execute, reducing the difficulty and complexity of the simulation; the display of the simulation process enables users or systems to intuitively understand the progress and status of the simulation, which helps to promptly discover and solve possible problems during the simulation process, improving the controllability and reliability of the simulation; by displaying the simulation process, users or systems can make more accurate optimization strategies based on real-time data, and at the same time, it helps to indicate sharing and deep learning.
[0082] Figure 4 It is a schematic structural diagram of a software simulation device provided by the embodiments of the present application. As Figure 4 shown, the software simulation device 400 includes:
[0083] An acquisition module 401 is configured to acquire simulation task information of a target software in response to an input operation. The simulation task information is used to indicate a simulation target and simulation tasks to be executed for the simulation target.
[0084] A display module 402 is configured to display a simulation process of the target software. The simulation process includes at least one simulation step obtained by disassembling the simulation tasks based on historical data related to the simulation target and the simulation tasks.
[0085] Figure 5 FIG. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Figure 5 The illustrated electronic device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.
[0086] As Figure 5 shown, the electronic device 500 includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a memory 506 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.
[0087] The following components are connected to the I / O interface 505: a memory 506 including a hard disk, etc.; and a communication part 507 including a network interface card such as a LAN (Local Area Network) card, a modem, etc., and the communication part 507 performs communication processing via a network such as the Internet; a driver 508 is also connected to the I / O interface 505 as needed.
[0088] Specifically, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication part 507. When the computer program is executed by the processor 501, the above functions defined in the method of the present application are performed.
[0089] In an exemplary embodiment, a storage medium including instructions is further provided, such as a memory including instructions, and the above instructions can be executed by the processor 501 of the electronic device 500 to complete the above method. Optionally, the storage medium may be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.
[0090] In the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.
[0091] Figure 6 FIG. [0000205] is a schematic structural diagram of another electronic device provided according to an embodiment of the present application. Figure 6 The illustrated electronic device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application. As Figure 6 shown, the electronic device 600 includes a processor 601 and a memory 602. Among them, the memory 602 is used to store program code, and the processor 601 is connected to the memory 602 and is used to read the program code from the memory 602 to implement the software simulation method in the above embodiment.
[0092] Optionally, the number of processors 601 may be one or more.
[0093] Optionally, the electronic device may further include an interface 603, and the number of this interface 603 may be multiple. The interface 603 can be connected to an application program and can receive data from external devices such as sensors.
[0094] Other embodiments of the present invention will be readily apparent to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following the general principles of the invention and including known common general knowledge or conventional technical means in the technical field not disclosed in this application. The specification and examples are only to be considered as exemplary, and the true scope and spirit of this application are pointed out by the following claims.
[0095] It should be understood that this application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is only limited by the appended claims.
Claims
1. A software simulation method, characterized in that, Including: In response to an input operation, obtain simulation task information of a target software; wherein, the simulation task information is used to indicate a simulation target and simulation tasks to be executed for the simulation target; Display the simulation process of the target software, wherein the simulation process includes at least one simulation step obtained by disassembling the simulation tasks based on the simulation target and historical data related to the simulation tasks.
2. The method according to claim 1, wherein The method further includes: Generate a prompt for a target large model based on the historical data related to the simulation tasks and the simulation task information; Input the prompt into the target large model, and the target large model determines user interface elements required for the simulation task based on the prompt; Determine the user interface elements as the simulation target.
3. The method according to claim 2, wherein The generating a prompt for a target large model based on the historical data related to the simulation tasks and the simulation task information includes: Perform structured processing on the historical data related to the simulation tasks and the simulation task information to obtain structured reference information; Based on the association between the structured reference information and a prompt template, generate at least one of a local target of the simulation task, conditions required to achieve the local target, and an expected result of the simulation task; Determine at least one of the local target, the conditions, and the expected result as the prompt for the target large model.
4. The method according to claim 2, wherein The inputting the prompt into the target large model, and the target large model determines user interface elements required for the simulation task based on the prompt includes: The target large model parses the simulation task based on the prompt to obtain multiple simulation steps corresponding to the simulation task and the expected output content format of the simulation steps; Perform structured processing on each of the simulation steps and the output content format based on a pre-configured output reference example to obtain at least one of headings and paragraphs, menus and links, and notifications and instructions; Determine at least one of the headings and paragraphs, the menus and links, and the notifications and instructions as the user interface elements required for the simulation task.
5. The method according to any one of claims 1 to 4, characterized in that The method further includes: Monitor at least one of parameter indicators related to the simulation target and simulation results during the simulation process; If at least one of the parameter indicators and the simulation results determines that the simulation fails, obtain failure information, and update the prompt based on the failure information.
6. The method according to claim 5, wherein The failure information includes: an abnormal simulation step and / or a deviation value that causes the simulation to fail, wherein the deviation value is obtained based on the simulation target and the simulation result corresponding to the abnormal simulation step.
7. The method according to claim 5, wherein It further includes: If it is determined that the simulation is successful based on at least one of the parameter indicators and the simulation results, annotate the simulation steps, obtain a screenshot of the annotated simulation test steps, and store the screenshot as historical data related to the simulation task.
8. The method according to claim 2, characterized in that, The target large model is obtained by training the large model based on a pre-configured prompt template and reference example of the large model, and in combination with structured sample data. Among them, the structured sample data is obtained based on the structured processing of the sample data, and / or the sample data is obtained based on historical data related to multiple historical simulation tasks.
9. The method according to claim 8, wherein The sample data includes at least one of: visual information elements and text information associated with the visual information elements; Among them, the visual information elements are obtained by screening sample historical data related to historical simulation tasks; and / or the text information is obtained by character recognition of the visual information elements.
10. The method according to claim 8, wherein The prompt word template includes information obtained by structuring the requirements of the simulation task and the specific operation content associated with the requirements, where the requirements are obtained based on the business background of the target software simulation task.
11. The method according to claim 8, wherein The reference example includes the execution actions of the target software and the execution objectives associated with the execution actions, where the execution actions are obtained based on the requirements of the target software simulation task.
12. A software simulation device, characterized in that, Including: An acquisition module, which is used to acquire the simulation task information of the target software in response to an input operation; where the simulation task information is used to indicate the simulation objective and the simulation tasks to be executed for the simulation objective; A display module, which is used to display the simulation process of the target software, where the simulation process includes at least one simulation step obtained by disassembling the simulation task based on the simulation objective and historical data related to the simulation task.
13. An electronic device, characterized in that, Including: A processor; A memory for storing instructions executable by the processor; Among them, the processor is configured to execute the instructions to implement the method according to any one of claims 1 to 11.
14. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the method according to any one of claims 1 to 13.
15. A computer program product, characterized in that, Including a computer program, which implements the method according to any one of claims 1-13 when executed by a processor.