Batch mobile device multi-task processing method and device and storage medium

Abstract

The invention discloses a batch mobile device multi-task processing method and device and a storage medium, relates to the technical field of mobile device task processing, and mainly aims at improving the overall processing efficiency of multiple tasks in multiple mobile devices. The method comprises the following steps: respectively establishing communication connection with each to-be-processed device through a protocol port of each to-be-processed device; in response to a trigger signal of a multi-task processing behavior corresponding to each to-be-processed device, obtaining a device identification identifier of each to-be-processed device; and on the basis of the device identification identifier, determining each processing task in each to-be-processed device, and respectively controlling each to-be-processed device to execute each corresponding processing task in parallel through the protocol port so as to perform multi-task processing on each to-be-processed device.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile device task processing, and in particular to a method, device and storage medium for batch mobile device multi-task processing. Background Art

[0002] With the rapid development of mobile devices and applications, the need to test and operate mobile devices is increasing.

[0003] Currently, when multiple tasks in multiple mobile devices are to be processed, the tasks are usually processed one by one on the mobile devices, and each task in the mobile devices is processed one by one, that is, only one task in one mobile device can be processed at a time, resulting in low efficiency in task processing. Summary of the invention

[0004] The present invention provides a method, device and storage medium for batch mobile device multi-task processing, which are mainly capable of improving the overall processing efficiency of multiple tasks in multiple mobile devices.

[0005] According to a first aspect of the present invention, a method for multitasking of batch mobile devices is provided, comprising:

[0006] Establishing communication connections with each of the devices to be processed through the protocol ports of the devices to be processed;

[0007] In response to a trigger signal of a multi-task processing behavior corresponding to each of the to-be-processed devices, acquiring a device identification identifier of each of the to-be-processed devices;

[0008] Based on the device identification identifier, each processing task in each of the devices to be processed is determined, and each of the devices to be processed is controlled through the protocol port to execute the corresponding processing tasks in parallel, so as to perform multi-task processing on each of the devices to be processed.

[0009] Optionally, the devices to be processed include Android mobile devices and iOS mobile devices; the processing tasks include: application testing tasks corresponding to the tested applications in the devices to be processed, pre-download application attribute information acquisition tasks for the applications to be downloaded, application running information acquisition tasks for the applications to be uninstalled, and traffic analysis tasks for each application;

[0010] The controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol ports includes:

[0011] For any processing task in the Android mobile device and the iOS mobile device, respectively determine a first processing thread corresponding to the Android mobile device and a second processing thread corresponding to the iOS mobile device;

[0012] Based on the first processing thread and the second processing thread, controlling the Android mobile device and the iOS mobile device to execute the processing task in parallel through the protocol port;

[0013] For each processing task in any one of the Android mobile devices and iOS mobile devices to be processed, respectively determine the task processing threads corresponding to the application test task, the pre-download application attribute information acquisition task, the application running information acquisition task, and the traffic analysis task;

[0014] Based on each of the task processing threads, the device to be processed is controlled through the protocol port to execute the corresponding application testing task, pre-download application attribute information acquisition task, application operation information acquisition task, and traffic analysis task in parallel.

[0015] Optionally, after controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol port, the method further includes:

[0016] The processing data obtained after each of the to-be-processed devices executes the corresponding processing tasks is obtained, and based on the processing data, the application score of the to-be-processed application corresponding to each of the processing tasks is determined, and based on the application score, the to-be-processed application is processed accordingly.

[0017] Optionally, determining, based on the processing data, an application score of the to-be-processed application corresponding to each of the processing tasks, and performing corresponding processing on the to-be-processed application based on the application score, includes:

[0018] For any device to be processed to execute an application test task of the tested application, determine a test score of the tested application based on test data obtained after executing the application test task;

[0019] Based on the test score, determine whether it is necessary to perform defect repair on the tested application; if defect repair is required, obtain log data during the execution of the application test task, and perform defect repair on the tested application based on the log data;

[0020] For any device to be processed, a task of obtaining attribute information of a pre-downloaded application of the application to be downloaded is executed, a download score of the application to be downloaded is determined based on the attribute information obtained after executing the task of obtaining attribute information of the pre-downloaded application, and the download score is displayed to the user terminal to which the device to be processed belongs;

[0021] receiving a feedback instruction triggered by a user terminal for the download score, and when the feedback instruction is a download instruction, controlling the device to be processed to download the application to be downloaded through the protocol port;

[0022] For any device to be processed, a task of obtaining application running information of the application to be uninstalled is performed, and based on the running information obtained after performing the task of obtaining the application running information, an uninstall score of the application to be uninstalled is determined, and the uninstall score is displayed to the user terminal to which the device to be processed belongs;

[0023] receiving a response instruction triggered by the user terminal in response to the uninstall score, and when the response instruction is an uninstall instruction, controlling the device to be processed to uninstall the application to be uninstalled through the protocol port;

[0024] For any device to be processed, a traffic analysis task for each application is performed, and based on the traffic usage data obtained after performing the traffic analysis task, the device to be processed is controlled through the protocol port to set the network usage authority for each application.

[0025] Optionally, determining the uninstall score of the application to be uninstalled based on the operation information obtained after executing the application operation information acquisition task includes:

[0026] Obtaining behavior link data of a user of a mobile device for the application to be uninstalled;

[0027] Determining a behavior feature vector corresponding to the behavior link data, and determining an operation feature vector corresponding to the operation information;

[0028] Performing principal component analysis on the behavior feature vector to obtain a behavior principal component feature vector, and performing principal component analysis on the operation feature vector to obtain an operation principal component feature vector;

[0029] The behavior principal component feature vector and the operation principal component feature vector are fused to obtain a fused feature vector, and the fused feature vector is input into a preset score prediction model for score prediction to obtain an uninstall score of the application to be uninstalled.

[0030] Optionally, before determining the application score of the to-be-processed application corresponding to each of the processing tasks based on the processing data, the method further includes:

[0031] For the processed data obtained after any processing device to be processed executes any processing task, determine the median corresponding to the processed data, determine a first intermediate value between the minimum value in the processed data and the median, and determine the first intermediate value as the first quartile corresponding to the processed data;

[0032] Determine a second intermediate value between the maximum value in the processed data and the median, and determine the second intermediate value as a third quartile corresponding to the processed data;

[0033] Calculating the distance between the first quartile and the third quartile, and determining the distance as the interquartile range corresponding to the processed data;

[0034] Calculate the anomaly detection lower limit value corresponding to the processed data according to the first quartile and the interquartile range;

[0035] Calculate an upper limit value of abnormality detection corresponding to the processed data according to the third quartile and the interquartile range;

[0036] In the processed data, data outside the abnormality detection lower limit value to the abnormality detection upper limit value is determined as abnormal data;

[0037] Eliminating abnormal data in the processed data to obtain cleaned processed data;

[0038] The determining, based on the processing data, an application score of the to-be-processed application corresponding to each of the processing tasks comprises:

[0039] Based on the cleaned processing data, an application score of the to-be-processed application corresponding to each of the processing tasks is determined.

[0040] Optionally, after establishing communication connections with each of the devices to be processed through the protocol ports of each of the devices to be processed, the method further includes:

[0041] Establishing a device status list based on the device identification identifier of each of the devices to be processed;

[0042] Monitor the connection status information of each of the devices to be processed in real time, and update the device status list in real time based on the device identification identifier and the connection status information;

[0043] The controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol ports includes:

[0044] Based on each processing task corresponding to each of the to-be-processed devices, a preset graphical user interface library is used to determine a graphical operation guide for each of the to-be-processed devices to execute each of the processing tasks;

[0045] Based on the graphic operation guide, each of the devices to be processed is controlled through the protocol port to execute the corresponding processing tasks in parallel.

[0046] According to a second aspect of the present invention, there is provided a multi-task processing device for batch mobile devices, comprising:

[0047] An establishing unit, used to establish a communication connection with each of the devices to be processed through a protocol port of each of the devices to be processed;

[0048] an acquisition unit, configured to acquire a device identification of each of the devices to be processed in response to a trigger signal of a multi-task processing behavior corresponding to each of the devices to be processed;

[0049] The task execution unit is used to determine each processing task in each of the devices to be processed based on the device identification identifier, and control each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-tasking processing on each of the devices to be processed.

[0050] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which implements the above batch mobile device multi-tasking processing method when executed by a processor.

[0051] According to a fourth aspect of the present invention, there is provided a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for multi-tasking of batch mobile devices when executing the program.

[0052] According to a method, device and storage medium for multi-task processing of batch mobile devices provided by the present invention, compared with the current method of processing multiple tasks in multiple mobile devices, which usually processes tasks on mobile devices one by one and processes each task in the mobile devices one by one, the present invention establishes communication connections with each of the devices to be processed through the protocol ports of each device to be processed; then, in response to the trigger signal of the multi-task processing behavior corresponding to each device to be processed, obtains the device identification of each device to be processed; finally, based on the device identification, determines each processing task in each device to be processed, and controls each device to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-task processing on each device to be processed. Thus, by allocating an independent thread to each processing task in each device to be processed, the processing process of each task in each device is isolated, each task in each device to be processed is controlled to be performed independently, and each task in each device to be processed can be performed simultaneously, thereby improving the overall processing efficiency of multiple tasks in batch devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0054] Figure 1 A flow chart of a method for multi-tasking of batch mobile devices provided by an embodiment of the present invention is shown;

[0055] Figure 2Another flow chart of a multi-task processing method for batch mobile devices provided by an embodiment of the present invention is shown;

[0056] Figure 3 A schematic structural diagram of a multi-task processing device for batch mobile devices provided by an embodiment of the present invention is shown;

[0057] Figure 4 A schematic structural diagram of another multi-task processing device for batch mobile devices provided by an embodiment of the present invention is shown;

[0058] Figure 5 A schematic diagram of the physical structure of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0059] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0060] Currently, tasks are processed one by one on mobile devices, and each task in the mobile device is processed one by one, resulting in that only one task in a mobile device can be processed at a time, resulting in low efficiency in task processing.

[0061] In order to solve the above problems, an embodiment of the present invention provides a method for multi-tasking of batch mobile devices, such as Figure 1 As shown, the method includes:

[0062] 101. Establish communication connections with each device to be processed through the protocol port of each device to be processed.

[0063] Among them, the devices to be processed include Android mobile devices (Android devices) and iOS (iPhone Operating System, a mobile operating system) mobile devices. Android mobile devices include Android phones, Android tablets, etc., and iOS mobile devices include iOS phones, iOS tablets, iOS computers, etc.

[0064] For the embodiment of the present invention, in order to realize the simultaneous independent execution of batch tasks in batch devices, a toolbox is constructed. The toolbox can complete the testing, installation, management and other task execution operations of multiple mobile devices such as Android mobile devices and iOS mobile devices in one stop. The toolbox provided by the embodiment of the present invention can realize efficient testing and operation of multiple mobile devices, improve work efficiency, simplify operation procedures, support multi-threaded operations, and adapt to multi-device multi-task testing environments. Based on this, in order to use the toolbox to process multiple devices and multiple tasks, it is first necessary to configure the environment of each mobile device and the toolbox to ensure the stable processing of subsequent tasks. For example, ensure that the Python (a computer programming language) environment version of each mobile device is 3.8 or above, install iTunes (a digital media playback application) in the iOS device to ensure the connection and communication of the iOS device, configure the ADB (Android Debug Bridge, a bridge tool between the Android device and the toolbox) environment variable in the Android mobile device, ensure that the command line tool in the toolbox can call the ADB function, etc. After the environment is configured, it is necessary to establish a connection between the toolbox and each mobile device. At this time, the Android device needs to turn on the developer mode and enable USB (Universal Serial Bus, Universal Serial Bus) debugging option, the iOS device needs to connect to the toolbox once through iTunes and then trust the toolbox on the device, that is, during the connection process, it is first necessary to determine the protocol port of each mobile device, and then establish a connection between the toolbox and each mobile device based on the protocol port, wherein the protocol port can be the serial port of each mobile device, and a communication connection with each mobile device is established through the serial port of each mobile device. When establishing the connection, it is necessary to determine the unique device identifier of each mobile device in advance, and use the unique device identifier to distinguish each mobile device, so as to establish a communication connection with each mobile device, so as to facilitate the subsequent simultaneous batch task processing of each mobile device.

[0065] 102. In response to a trigger signal of a multi-task processing behavior corresponding to each device to be processed, obtain a device identification of each device to be processed.

[0066] The device identification mark may be a graphic mark, a digital mark, etc. of each mobile device. As long as the device identification mark can uniquely identify the device, the embodiment of the present invention does not limit the specific form of the device identification mark.

[0067] For the embodiment of the present invention, after establishing a communication connection with each mobile device, the user will select each task to be processed in each mobile device in the toolbox graphical interface. Specifically, each mobile device and each task to be processed therein are displayed in the toolbox graphical interface in the form of a device identification identifier and a task identifier. When the user clicks on each mobile device and the task to be processed in each mobile device in the graphical interface, a processing trigger signal for multiple tasks in multiple devices is triggered. When the trigger signal is received, the device identification identifier of each mobile device and the task identification identifier of each task to be processed are obtained, wherein the task identification identifier can uniquely determine the corresponding task, the device identification number of each mobile device is different, and the task identification number of each task to be processed is also different, so that the device to be processed is identified based on the device identification number, and the task to be processed is identified based on the task identification number, so as to realize the subsequent simultaneous processing of multiple tasks in multiple devices.

[0068] 103. Based on the device identification identifier, determine each processing task in each device to be processed, and control each device to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-task processing on each device to be processed.

[0069] Among them, the various processing tasks include: application attribute information acquisition task of pre-downloaded applications, application testing task in mobile devices, application operation information acquisition task, traffic usage analysis task of each application in mobile devices, application crash information acquisition task, application data clearing task, application process end task, screenshot task, proxy setting task, proxy closing task, network debugging task, etc.

[0070] For the embodiments of the present invention, after determining the device identification number of each mobile device and the task identification number of each processing task in each mobile device, the processing tasks in the independent mobile devices are constructed. Each processing task can be implemented by executing the corresponding independent code. The independent code can be implemented by a pre-constructed code template. Taking a target task in a mobile device as an example, the device identification identifier of the mobile device and the task identification identifier of the target task are input into the corresponding positions in the code template to generate a task execution code, and the task execution code is used to execute the target task in the mobile device. Therefore, according to the above method, the task execution code of each task in each mobile device can be determined, and each task execution code can be executed at the same time, so as to realize the simultaneous independent execution of each task in each mobile device, thereby improving the overall processing efficiency of multiple devices and multiple tasks and saving task processing time. Specifically, the protocol port is connected to the test execution terminal, that is, the toolbox, and each protocol port can be a USB interface, etc. The instructions triggered in the toolbox are transmitted to each mobile device through the protocol port, and the task execution code of each task in each mobile device is written through the protocol port to realize the control of each mobile device to execute the corresponding processing tasks in parallel. Therefore, by isolating the processing process of each task to be processed in each mobile device, it can be ensured that each task to be processed in each mobile device is executed independently at the same time, thereby improving the overall execution efficiency of the task. For example, it is necessary to execute the application test task and the pre-download application information acquisition task in the Android mobile device, and the application test task and the traffic usage analysis task in the iOS mobile device at the same time, then based on the code template, the task execution code of each task of the Android mobile device is determined respectively, and the task execution code of each task in the iOS mobile device is determined, and then based on each task execution code, through the protocol port of each mobile device, the Android mobile device and the iOS mobile device are controlled to independently execute each task at the same time.

[0071] According to a method for multi-tasking of batch mobile devices provided by the present invention, compared with the current method of processing multiple tasks in multiple mobile devices, which usually processes tasks on mobile devices one by one and processes each task in the mobile devices one by one, the present invention establishes communication connections with each of the devices to be processed through the protocol ports of each device to be processed; then, in response to the trigger signal of the multi-tasking processing behavior corresponding to each device to be processed, obtains the device identification of each device to be processed; finally, based on the device identification, determines each processing task in each device to be processed, and controls each device to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-tasking on each device to be processed. Thus, by allocating an independent thread to each processing task in each device to be processed, the processing process of each task in each device is isolated, and each task in each device to be processed is controlled to be performed independently, and each task in each device to be processed can be performed simultaneously, thereby improving the overall processing efficiency of multiple tasks in batch devices.

[0072] Further, in order to better illustrate the above process of processing the mobile device, as a refinement and extension of the above embodiment, the embodiment of the present invention provides another method for multi-tasking processing of batch mobile devices, such as Figure 2 As shown, the method includes:

[0073] 201. Establish communication connections with each device to be processed through the protocol port of each device to be processed.

[0074] For the embodiment of the present invention, after establishing a communication connection with each device to be processed according to the protocol port of each device to be processed, the method includes: establishing a device status list based on the device identification identifier of each device to be processed; monitoring the connection status information of each device to be processed in real time, and updating the device status list in real time based on the device identification identifier and the connection status information.

[0075] Among them, the connection status information refers to whether the mobile device is connected to the toolbox. Specifically, after designing the toolbox, a detailed user manual and online help document are provided to guide users on how to install, configure and use the toolbox. In the process of controlling the execution of each task in each mobile device, the toolbox needs to implement a comprehensive exception capture and processing mechanism to ensure that clear error information is provided when the task fails to execute, and record detailed operation logs for problem tracking. In addition, the toolbox can use the tkinter (graphical user interface library) library to design an intuitive and easy-to-use GUI (Graphical User Interface) to provide users with clear operation instructions and feedback, ensuring that users can quickly and accurately control the toolbox, thereby improving the processing efficiency and accuracy of multiple devices and multiple tasks.

[0076] Specifically, a monitoring service runs in the background of the toolbox to monitor the plugging and unplugging events of the mobile device in real time, and updates the device status in real time through a graphical interface or a status list.

[0077] 202. In response to a trigger signal of a multi-task processing behavior corresponding to each to-be-processed device, obtain a device identification of each to-be-processed device.

[0078] Among them, the device identification identifier can be the serial port number of each mobile device, or it can be a unique number set for each mobile device. When a unique number is set for each mobile device, a one-to-one mapping relationship must be established between the unique number and the device serial port number so that the mobile device can be uniquely identified by the unique number, thereby facilitating simultaneous task processing of multiple mobile devices.

[0079] 203. Based on the device identification identifier, determine each processing task in each to-be-processed device, and control each to-be-processed device to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-task processing on each to-be-processed device.

[0080] Among them, the devices to be processed include Android mobile devices and iOS mobile devices; the processing tasks include: application testing tasks corresponding to the tested applications in the devices to be processed, pre-download application attribute information acquisition tasks for the applications to be downloaded, application running information acquisition tasks for the applications to be uninstalled, and traffic analysis tasks for each application.

[0081] Corresponding to the embodiment of the present invention, in order to realize simultaneous independent processing of various tasks in the Android mobile device and the iOS mobile device, step 203 specifically includes: for any processing task in the Android mobile device and the iOS mobile device, respectively determine the first processing thread corresponding to the Android mobile device and the second processing thread corresponding to the iOS mobile device; based on the first processing thread and the second processing thread, control the Android mobile device and the iOS mobile device to execute the processing tasks in parallel through the protocol port; for each processing task in any one of the Android mobile device and the iOS mobile device to be processed, respectively determine the task processing threads corresponding to the application test task, the pre-download application attribute information acquisition task, the application running information acquisition task, and the traffic analysis task; based on each of the task processing threads, control the device to be processed through the protocol port to execute the corresponding application test task, the pre-download application attribute information acquisition task, the application running information acquisition task, and the traffic analysis task in parallel.

[0082] Specifically, taking the processing of any task in an Android mobile device and an iOS mobile device as an example, first determine the processing thread for any task in the Android mobile device, and determine the processing thread for any task in the iOS mobile device, and then start the two processing threads at the same time to achieve simultaneous parallel processing of any task in the Android mobile device and the iOS mobile device. In another embodiment of the present invention, taking the processing of multiple tasks in an Android mobile device as an example, respectively determine the processing threads of the multiple tasks, and then start each processing thread at the same time to achieve simultaneous independent processing of each task in the Android mobile device, thus according to the above-mentioned method, that is, the toolbox adopts a thread-safe data structure and synchronization mechanism, it is possible to achieve simultaneous parallel processing of multiple tasks in multiple mobile devices, thereby improving the overall processing efficiency of multiple devices and multiple tasks, and ensuring that multiple devices and multiple tasks run stably without interfering with each other.

[0083] 204. Obtain processing data obtained after each to-be-processed device executes each corresponding processing task, and determine application scores of the to-be-processed applications corresponding to each processing task based on the processing data, and perform corresponding processing on the to-be-processed applications based on the application scores.

[0084] According to the embodiment of the present invention, after the mobile device executes the application test task of the tested application, the test data corresponding to the tested application is obtained, wherein the test data includes: the startup time, response time, and usage fluency data of the tested application; after the mobile device executes the pre-download application attribute information acquisition task of the application to be downloaded, the attribute information of the application to be downloaded is obtained, wherein the attribute information includes the occupied memory, evaluation information, memory consumption, download quantity, and other information of the application to be downloaded. If the Android mobile device executes the pre-download application attribute information acquisition task, the APK (Android Package Kit) file of the application to be downloaded is pre-determined, and the Androguard (a full-featured Python tool) library is used to parse the APK file to extract and display the basic attribute information of the application; after the mobile device executes the application running information acquisition task of the application to be uninstalled, the running information of the application to be uninstalled is obtained, wherein the running information includes: historical usage information, occupied memory information, CPU (Central Processing Unit, central processing unit) information, crash information, traffic consumption, and other information of the application to be uninstalled; after the mobile device executes the traffic analysis task, the traffic usage data is obtained, wherein the traffic usage data refers to information such as the traffic usage of each application in the mobile device within a specified time.Specifically, after controlling the mobile device to process each processing task, the processing data corresponding to each of the above tasks will be obtained. Then, the next processing process needs to be determined according to each processing data. Based on this, step 204 specifically includes: executing the application test task of the tested application for any device to be processed, and determining the test score of the tested application based on the test data obtained after executing the application test task; judging whether it is necessary to repair defects in the tested application based on the test score, and if defect repair is required, obtaining the log data during the execution of the application test task, and repairing defects in the tested application based on the log data; executing the pre-download application attribute information acquisition task of the application to be downloaded for any device to be processed, and determining the download score of the application to be downloaded based on the attribute information obtained after executing the pre-download application attribute information acquisition task, and reporting the score to the device to be processed. The user terminal to which it belongs displays a download score; receives a feedback instruction triggered by the user terminal for the download score, and when the feedback instruction is a download instruction, controls the device to be processed to download the application to be downloaded through the protocol port; performs an application operation information acquisition task for the application to be uninstalled for any device to be processed, determines the uninstall score of the application to be uninstalled based on the operation information obtained after performing the application operation information acquisition task, and displays the uninstall score to the user terminal to which the device to be processed belongs; receives a response instruction triggered by the user terminal for the uninstall score, and when the response instruction is an uninstall instruction, controls the device to be processed to uninstall the application to be uninstalled through the protocol port; performs a traffic analysis task for each application for any device to be processed, and based on the traffic usage data obtained after performing the traffic analysis task, controls the device to be processed to set network usage permissions for each application through the protocol port.

[0085] Specifically, taking a mobile device as an example, after the mobile device executes the application testing task on the tested application, the test data is obtained, and then the test score corresponding to the tested application is determined based on the test data. That is, if the response time of the tested application is shorter, the startup time is shorter, and the usage fluency is higher, the test score is higher. When the test score is lower than the threshold set in advance according to actual needs, it is determined that the tested application needs to be defect-fixed. The specific repair method may be to end useless processes in the application, or clear useless cache data in the application, etc.

[0086] After the task of obtaining the attribute information of the pre-downloaded application of the application to be downloaded is completed by controlling the mobile device, the basic attribute information of the pre-downloaded application will be obtained. According to the attribute information, the download score of the pre-downloaded application is evaluated. For example, the smaller the memory occupied by the pre-downloaded application, the higher the evaluation of other users who have used it, the smaller the memory consumption, and the more download times, the higher the download score. Then, the download score of the application to be downloaded is displayed to the user terminal, and a click button for downloading is displayed to the user terminal at the same time. The user of the user terminal will determine whether to download the application according to the download score. If downloading, the download button is clicked. After receiving the download instruction returned by the user terminal, the mobile device is controlled to download the application. Specifically, the toolbox can automatically call the adb install-r command (a command for installing an application) to download and install the application. If an Android device that needs to enter a password is encountered, the automatic password input installation can also be realized. By displaying the download score to the user, the user evaluates whether to download the application according to the download score, which can help the user better understand the application, so that it can clearly know whether the application needs to be downloaded, and avoid the user blindly downloading unwanted applications and wasting download resources. When downloading an application on an iOS mobile device, select the IPA (iPhone Application) file through the file explorer, and the toolbox calls the tidevice library (a Python library for connecting to and controlling iOS devices) to download and install the application. The tidevice library can also obtain and display basic information about the device or application, list the applications installed on the device, and provide the functions of starting, killing, and viewing processes.

[0087] When the task of controlling the mobile device to obtain the application running information of the application to be uninstalled is completed, the running information of the application to be uninstalled will be obtained, and the uninstall score of the application to be uninstalled will be evaluated based on the attribute information, wherein the specific method for determining the uninstall score includes: obtaining the behavior link data of the user of the mobile device for the application to be uninstalled; determining the behavior feature vector corresponding to the behavior link data, and determining the running feature vector corresponding to the running information; performing principal component analysis on the behavior feature vector to obtain the behavior principal component feature vector, and performing principal component analysis on the running feature vector to obtain the running principal component feature vector; fusing the behavior principal component feature vector and the running principal component feature vector to obtain a fused feature vector, and inputting the fused feature vector into a preset score prediction model for score prediction to obtain the uninstall score of the application to be uninstalled.

[0088] Among them, the behavior link data refers to the historical interaction data between the user of the mobile device and the application to be uninstalled, that is, the data record of a series of continuous behaviors performed by the user on the application to be uninstalled. These data describe in detail the various steps and interaction process data experienced by the user from entering the application to be uninstalled to completing a task or goal, including the number of interactions, browsing time, search behavior, etc. Specifically, after obtaining the behavior link data and operation information of the application to be uninstalled, the behavior feature vector corresponding to the behavior link data and the operation feature vector corresponding to the operation information are determined respectively by using word embedding and other methods, and then the principal component feature vectors in the behavior feature vector and the operation feature vector are determined respectively. The specific method for determining the principal component feature vector includes: constructing a feature matrix based on the behavior feature vector; determining the element mean of each element in the feature matrix, and subtracting each element in the feature matrix from the element mean to obtain a centralized feature matrix; determining the covariance matrix corresponding to the centralized feature matrix; performing eigenvalue decomposition on the covariance matrix to obtain matrix eigenvalues ​​and matrix eigenvectors; based on the size of the matrix eigenvalues, selecting a preset number of matrix feature vectors from the matrix feature vector, and determining the preset number of matrix feature vectors as the behavior principal component feature vector. Similarly, based on the running eigenvector, construct a feature matrix; determine the element mean of each element in the feature matrix, and subtract each element in the feature matrix from the element mean to obtain a centralized feature matrix; determine the covariance matrix corresponding to the centralized feature matrix; perform eigenvalue decomposition on the covariance matrix to obtain matrix eigenvalues ​​and matrix eigenvectors; based on the size of the matrix eigenvalues, select a preset number of matrix eigenvectors from the matrix eigenvector, and determine the preset number of matrix eigenvectors as the running principal component eigenvectors. Furthermore, each element in the behavior feature vector is multiplied by the corresponding element in the operation feature vector to obtain an initial fused feature vector, and the initial fused feature vector is transformed using a preset transformation coefficient (set according to actual needs) to obtain a fused feature vector, and then the fused feature vector is input into a preset score prediction model for score prediction to obtain an uninstall score of the application to be uninstalled, wherein the preset score prediction model is obtained after training based on a sample training set, and the specific training process is: constructing multiple preset initial models and obtaining sample training links, wherein the sample training set includes sample behavior link data and sample operation data of the sample application, as well as the actual uninstall score corresponding to the sample application; according to the number of preset initial models, the sample training set is divided into multiple groups of test data and multiple groups of verification data, and each group of test data is used to train the corresponding preset initial model, and then each group of test data is used to verify the trained preset initial model; finally, based on the verification result, a preset score prediction model whose prediction accuracy meets the requirements is selected.In an embodiment of the present invention, in the uninstall score prediction process, since the behavior link data and the operation information belong to data from different data sources, by fusing the data from different data sources into more significant and deeper features, and using the model to analyze the more significant and deeper features, the prediction performance of the model can be improved, thereby improving the score prediction accuracy, thereby improving the task processing accuracy, and at the same time, by comprehensively analyzing the application's behavior link data and operation information to determine the uninstall score, the prediction accuracy of the score can be further improved.

[0089] Furthermore, after determining the uninstall score of the application, the uninstall score is displayed to the user terminal, and a click button for uninstalling is displayed to the user terminal. The user of the user terminal will determine whether to uninstall the application based on the uninstall score, and click the uninstall button if uninstalling. After receiving the uninstall instruction returned by the user terminal, the mobile device is controlled to uninstall the application. By displaying the uninstall score to the user, the user evaluates whether to uninstall the application based on the uninstall score, which can help the user better understand the application so that he can clearly know whether the application needs to be uninstalled, avoiding the user from blindly uninstalling the application.

[0090] When the task of obtaining the application running information of each application in the mobile device is completed, the traffic usage data of each application will be obtained. When the traffic usage data of an application is too high, the network settings of the application will be performed to limit the network usage permissions of the application, such as controlling the update function of the application to only be performed under wifi, etc., thereby saving self-paid traffic resources.

[0091] At the same time, you can also control each mobile device to perform screenshot operations, proxy settings and proxy shutdown functions, log clearing functions, clearing application data, ending processes, obtaining application crash information, application performance data collection functions and other task processing functions. When performing tasks such as clearing application data and ending processes, you can enter the application package name and call the adb shell pm clear and adb shell am force-stop commands to clear application data and end processes.

[0092] In another embodiment of the present invention, in order to facilitate users to use the toolbox to control each mobile device to process each task, the method also includes: based on the processing tasks corresponding to each of the devices to be processed, using a preset graphical user interface library to determine the graphic operation instructions for each of the devices to be processed to perform each of the processing tasks; based on the graphic operation instructions, controlling each of the devices to be processed to perform the corresponding processing tasks in parallel through the protocol port.

[0093] The preset graphical user interface includes operation instructions for controlling each mobile device to perform each task through the toolbox. Specifically, an intuitive and easy-to-use graphical user interface can be designed in advance using the tkinter library, and the graphical user interface provides operation instructions and execution result feedback to the user, so that each mobile device can be quickly and accurately controlled to perform each task.

[0094] The embodiment of the present invention realizes the simultaneous independent execution of multiple tasks in batch mobile devices according to the toolbox. The toolbox integrates a full set of functions from application installation and management to performance testing, providing users with one-stop service; cross-platform support: supports both Android and iOS, two major mainstream mobile operating systems, to meet the needs of different users; multi-threaded operation: supports multi-threaded operation, allows multiple devices to be operated at the same time, greatly improving work efficiency; automated process: automates the execution of routine tasks, such as application installation, data clearing, etc., reduces manual intervention, and reduces the error rate of operation; real-time device monitoring: automatically monitors the plug-in and unplug status of the device, updates the device list in real time, and ensures that the user always has the latest device information; user-friendly interface: provides an intuitive and easy-to-use graphical user interface, simplifies the operation process, and improves the user experience; detailed information display: through the toolbox, detailed information of the application can be obtained, including package name, crash log, performance data, etc., which is convenient for users to analyze and debug; proxy and certificate management: simplifies the network proxy setting and certificate management process, which is convenient for users to quickly capture and analyze network packets; exception handling and logging: has exception capture and logging functions, which is convenient for problem tracking and technical support.

[0095] According to another method for multi-tasking of batch mobile devices provided by the present invention, compared with the current method of processing multiple tasks in multiple mobile devices, which usually processes tasks on mobile devices one by one and processes each task in the mobile devices one by one, the present invention establishes communication connections with each of the devices to be processed through the protocol ports of each device to be processed; then, in response to the trigger signal of the multi-tasking processing behavior corresponding to each device to be processed, obtains the device identification of each device to be processed; finally, based on the device identification, determines each processing task in each device to be processed, and controls each device to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-tasking on each device to be processed. Thus, by allocating an independent thread to each processing task in each device to be processed, the processing process of each task in each device is isolated, and each task in each device to be processed is controlled to be performed independently, and each task in each device to be processed can be performed simultaneously, thereby improving the overall processing efficiency of multiple tasks in batch devices.

[0096] Further, as Figure 1The specific implementation of the present invention provides a batch mobile device multi-task processing device, such as Figure 3 As shown, the device includes: an establishing unit 31, an acquiring unit 32, and a task executing unit 33.

[0097] The establishing unit 31 may be used to establish a communication connection with each of the devices to be processed through a protocol port of each of the devices to be processed.

[0098] The acquisition unit 32 may be configured to acquire a device identification of each of the devices to be processed in response to a trigger signal of a multi-task processing behavior corresponding to each of the devices to be processed.

[0099] The task execution unit 33 can be used to determine each processing task in each of the devices to be processed based on the device identification identifier, and control each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-tasking on each of the devices to be processed.

[0100] In a specific application scenario, in order to control each device to be processed to execute the corresponding processing tasks in parallel through the protocol port, such as Figure 4 As shown, the task execution unit 33 includes a determination module 331 and an execution module 332 .

[0101] The determination module 331 may be used to determine, for any processing task in an Android mobile device and an iOS mobile device, a first processing thread corresponding to the Android mobile device and a second processing thread corresponding to the iOS mobile device, respectively.

[0102] The execution module 332 may be configured to control the Android mobile device and the iOS mobile device to execute the processing tasks in parallel through the protocol port based on the first processing thread and the second processing thread.

[0103] The determination module 331 can also be used to determine the task processing threads corresponding to the application testing task, the pre-downloaded application attribute information acquisition task, the application running information acquisition task, and the traffic analysis task for each processing task in any one of the Android mobile devices and iOS mobile devices to be processed.

[0104] The execution module 332 can also be used to control the device to be processed to execute corresponding application testing tasks, pre-download application attribute information acquisition tasks, application operation information acquisition tasks, and traffic analysis tasks in parallel based on each of the task processing threads through the protocol port.

[0105] In a specific application scenario, in order to process each application to be processed in each device to be processed, the task execution unit 33 can also be used to obtain processing data obtained after each device to be processed executes the corresponding processing task, and based on the processing data, determine the application score of the application to be processed corresponding to each processing task, and based on the application score, perform corresponding processing on the application to be processed.

[0106] In a specific application scenario, in order to perform corresponding processing on the application to be processed, the task execution unit 33 further includes: a repair module 333 , a download module 334 , an uninstall module 335 , and a setting module 336 .

[0107] The determination module 331 may also be used to execute an application test task of a tested application for any device to be processed, and determine a test score of the tested application based on test data obtained after executing the application test task.

[0108] The repair module 333 can be used to determine whether the tested application needs to be repaired based on the test score. If defect repair is required, log data during the execution of the application test task is obtained, and defect repair is performed on the tested application based on the log data.

[0109] The determination module 331 can also be used to perform a pre-download application attribute information acquisition task for the application to be downloaded for any device to be processed, determine the download score of the application to be downloaded based on the attribute information obtained after performing the pre-download application attribute information acquisition task, and display the download score to the user terminal to which the device to be processed belongs.

[0110] The download module 334 may be configured to receive a feedback instruction triggered by a user terminal in response to the download score, and when the feedback instruction is a download instruction, control the device to be processed to download the application to be downloaded through the protocol port.

[0111] The determination module 331 can also be used to execute the application running information acquisition task of the application to be uninstalled for any device to be processed, determine the uninstall score of the application to be uninstalled based on the running information obtained after executing the application running information acquisition task, and display the uninstall score to the user terminal to which the device to be processed belongs.

[0112] The uninstall module 335 may be configured to receive a response instruction triggered by the user terminal in response to the uninstall score, and when the response instruction is an uninstall instruction, control the device to be processed to uninstall the application to be uninstalled through the protocol port.

[0113] The setting module 336 can be used to perform traffic analysis tasks for various applications on any device to be processed, and based on the traffic usage data obtained after executing the traffic analysis task, control the device to be processed through the protocol port to set network usage permissions for various applications.

[0114] In a specific application scenario, in order to determine the uninstall score of the application to be uninstalled, the determination module 331 can be specifically used to obtain the behavior link data of the user of the mobile device for the application to be uninstalled; determine the behavior feature vector corresponding to the behavior link data, and determine the operation feature vector corresponding to the operation information; perform principal component analysis on the behavior feature vector to obtain the behavior principal component feature vector, and perform principal component analysis on the operation feature vector to obtain the operation principal component feature vector; fuse the behavior principal component feature vector and the operation principal component feature vector to obtain a fused feature vector, and input the fused feature vector into a preset score prediction model for score prediction to obtain the uninstall score of the application to be uninstalled.

[0115] In a specific application scenario, in order to clean the processed data, the device further includes a cleaning unit 34 .

[0116] The cleaning unit 34 can be used to determine the median corresponding to the processed data obtained after any processing task is executed by any device to be processed, and determine the first intermediate value between the minimum value in the processed data and the median, and determine the first intermediate value as the first quartile corresponding to the processed data; determine the second intermediate value between the maximum value in the processed data and the median, and determine the second intermediate value as the third quartile corresponding to the processed data; calculate the distance between the first quartile and the third quartile, and determine the distance as the interquartile range corresponding to the processed data; calculate the lower limit value of abnormality detection corresponding to the processed data according to the first quartile and the interquartile range; calculate the upper limit value of abnormality detection corresponding to the processed data according to the third quartile and the interquartile range; in the processed data, determine the data outside the lower limit value of abnormality detection to the upper limit value of abnormality detection as abnormal data; remove the abnormal data in the processed data to obtain the cleaned processed data.

[0117] The task execution unit 33 may be specifically configured to determine the application score of the to-be-processed application corresponding to each of the processing tasks based on the cleaned processing data.

[0118] In a specific application scenario, in order to observe the device status in real time, the apparatus further includes an updating unit 35 .

[0119] The establishing unit 31 may also be configured to establish a device status list based on the device identification identifier of each device to be processed.

[0120] The updating unit 35 may be used to monitor the connection status information of each of the devices to be processed in real time, and update the device status list in real time based on the device identification identifier and the connection status information.

[0121] In a specific application scenario, in order to execute tasks, the task execution unit 33 can also be used to determine the graphic operation instructions for each device to be processed to execute each processing task based on the processing tasks corresponding to each device to be processed, using a preset graphical user interface library; based on the graphic operation instructions, each device to be processed is controlled through the protocol port to execute the corresponding processing tasks in parallel.

[0122] It should be noted that for other corresponding descriptions of the functional modules involved in the multi-task processing device for batch mobile devices provided by the embodiment of the present invention, reference can be made to Figure 1 The corresponding description of the method shown will not be repeated here.

[0123] Based on the above Figure 1 The method shown, accordingly, an embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented: establishing communication connections with each of the devices to be processed through the protocol ports of each of the devices to be processed; obtaining a device identification identifier of each of the devices to be processed in response to a trigger signal of a multi-task processing behavior corresponding to each of the devices to be processed; determining each processing task in each of the devices to be processed based on the device identification identifier, and controlling each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol ports, so as to perform multi-tasking on each of the devices to be processed.

[0124] Based on the above Figure 1 The method shown and Figure 3 The embodiment of the device shown in the figure, the embodiment of the present invention also provides a physical structure diagram of a computer device, such as Figure 5As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43, and when the processor 41 executes the program, the following steps are implemented: establishing communication connections with each of the devices to be processed through the protocol ports of each of the devices to be processed; obtaining a device identification identifier of each of the devices to be processed in response to a trigger signal of a multi-tasking behavior corresponding to each of the devices to be processed; determining each of the processing tasks in each of the devices to be processed based on the device identification identifier, and controlling each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol ports, so as to perform multi-tasking on each of the devices to be processed.

[0125] Through the technical solution of the present invention, the present invention establishes communication connections with each of the devices to be processed through the protocol ports of each device to be processed; then, in response to the trigger signal of the multi-task processing behavior corresponding to each of the devices to be processed, obtains the device identification of each of the devices to be processed; finally, based on the device identification, determines each of the processing tasks in each of the devices to be processed, and controls each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol ports, so as to perform multi-task processing on each of the devices to be processed. Thus, by allocating an independent thread to each of the processing tasks in each of the devices to be processed, the processing process of each task in each of the devices to be processed is isolated, and each of the tasks in each of the devices to be processed is controlled to be performed independently, and each of the tasks in each of the devices to be processed can be performed simultaneously, thereby improving the overall processing efficiency of multiple tasks in batch devices.

[0126] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for multitasking of batch mobile devices, characterized in that: include: Establishing communication connections with each of the devices to be processed through the protocol ports of the devices to be processed; In response to a trigger signal of a multi-task processing behavior corresponding to each of the to-be-processed devices, acquiring a device identification identifier of each of the to-be-processed devices; Based on the device identification identifier, each processing task in each of the devices to be processed is determined, and each of the devices to be processed is controlled through the protocol port to execute the corresponding processing tasks in parallel, so as to perform multi-task processing on each of the devices to be processed.

2. The method according to claim 1, characterized in that The devices to be processed include Android mobile devices and iOS mobile devices; the processing tasks include: application testing tasks corresponding to the tested applications in the devices to be processed, pre-download application attribute information acquisition tasks for the applications to be downloaded, application running information acquisition tasks for the applications to be uninstalled, and traffic analysis tasks for each application; The controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol ports includes: For any processing task in the Android mobile device and the iOS mobile device, respectively determine a first processing thread corresponding to the Android mobile device and a second processing thread corresponding to the iOS mobile device; Based on the first processing thread and the second processing thread, controlling the Android mobile device and the iOS mobile device to execute the processing task in parallel through the protocol port; For each processing task in any one of the Android mobile devices and iOS mobile devices to be processed, respectively determine the task processing threads corresponding to the application test task, the pre-download application attribute information acquisition task, the application running information acquisition task, and the traffic analysis task; Based on each of the task processing threads, the device to be processed is controlled through the protocol port to execute the corresponding application testing task, pre-download application attribute information acquisition task, application operation information acquisition task, and traffic analysis task in parallel.

3. The method according to claim 1, characterized in that: After controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol port, the method further includes: The processing data obtained after each of the to-be-processed devices executes the corresponding processing tasks is obtained, and based on the processing data, the application score of the to-be-processed application corresponding to each of the processing tasks is determined, and based on the application score, the to-be-processed application is processed accordingly.

4. The method according to claim 3, characterized in that The step of determining, based on the processing data, an application score of the application to be processed corresponding to each of the processing tasks, and performing corresponding processing on the application to be processed based on the application score, comprises: For any device to be processed to execute an application test task of the tested application, determine a test score of the tested application based on test data obtained after executing the application test task; Based on the test score, determine whether it is necessary to perform defect repair on the tested application; if defect repair is required, obtain log data during the execution of the application test task, and perform defect repair on the tested application based on the log data; For any device to be processed, a task of obtaining attribute information of a pre-downloaded application of the application to be downloaded is executed, a download score of the application to be downloaded is determined based on the attribute information obtained after executing the task of obtaining attribute information of the pre-downloaded application, and the download score is displayed to the user terminal to which the device to be processed belongs; receiving a feedback instruction triggered by a user terminal in response to the download score, and when the feedback instruction is a download instruction, controlling the device to be processed to download the application to be downloaded through the protocol port; For any device to be processed, a task of obtaining application running information of the application to be uninstalled is performed, and based on the running information obtained after performing the task of obtaining the application running information, an uninstall score of the application to be uninstalled is determined, and the uninstall score is displayed to the user terminal to which the device to be processed belongs; receiving a response instruction triggered by the user terminal in response to the uninstall score, and when the response instruction is an uninstall instruction, controlling the device to be processed to uninstall the application to be uninstalled through the protocol port; For any device to be processed, a traffic analysis task for each application is performed, and based on the traffic usage data obtained after performing the traffic analysis task, the device to be processed is controlled through the protocol port to set the network usage authority for each application.

5. The method according to claim 4, characterized in that The step of determining the uninstall score of the application to be uninstalled based on the operation information obtained after executing the application operation information acquisition task includes: Obtaining behavior link data of a user of a mobile device for the application to be uninstalled; Determining a behavior feature vector corresponding to the behavior link data, and determining an operation feature vector corresponding to the operation information; Performing principal component analysis on the behavior feature vector to obtain a behavior principal component feature vector, and performing principal component analysis on the operation feature vector to obtain an operation principal component feature vector; The behavior principal component feature vector and the operation principal component feature vector are fused to obtain a fused feature vector, and the fused feature vector is input into a preset score prediction model for score prediction to obtain an uninstall score of the application to be uninstalled.

6. The method according to claim 3, characterized in that Before determining the application score of the to-be-processed application corresponding to each of the processing tasks based on the processing data, the method further includes: For the processed data obtained after any processing device to be processed executes any processing task, determine the median corresponding to the processed data, determine a first intermediate value between the minimum value in the processed data and the median, and determine the first intermediate value as the first quartile corresponding to the processed data; Determine a second intermediate value between the maximum value in the processed data and the median, and determine the second intermediate value as a third quartile corresponding to the processed data; Calculating the distance between the first quartile and the third quartile, and determining the distance as the interquartile range corresponding to the processed data; Calculate the anomaly detection lower limit value corresponding to the processed data according to the first quartile and the interquartile range; Calculate an upper limit value of abnormality detection corresponding to the processed data according to the third quartile and the interquartile range; In the processed data, data outside the abnormality detection lower limit value to the abnormality detection upper limit value is determined as abnormal data; Eliminating abnormal data in the processed data to obtain cleaned processed data; The determining, based on the processing data, an application score of the to-be-processed application corresponding to each of the processing tasks comprises: Based on the cleaned processing data, an application score of the to-be-processed application corresponding to each of the processing tasks is determined.

7. The method according to claim 1, characterized in that After establishing communication connections with each of the devices to be processed through the protocol ports of each of the devices to be processed, the method further includes: Establishing a device status list based on the device identification identifier of each of the devices to be processed; Monitor the connection status information of each of the devices to be processed in real time, and update the device status list in real time based on the device identification identifier and the connection status information; The controlling the devices to be processed to execute the corresponding processing tasks in parallel respectively through the protocol ports includes: Based on each processing task corresponding to each of the to-be-processed devices, a preset graphical user interface library is used to determine a graphical operation guide for each of the to-be-processed devices to execute each of the processing tasks; Based on the graphic operation guide, each of the devices to be processed is controlled through the protocol port to execute the corresponding processing tasks in parallel.

8. A multi-task processing device for batch mobile equipment, characterized in that: include: An establishing unit, used to establish a communication connection with each of the devices to be processed through a protocol port of each of the devices to be processed; an acquisition unit, configured to acquire a device identification of each of the devices to be processed in response to a trigger signal of a multi-task processing behavior corresponding to each of the devices to be processed; The task execution unit is used to determine each processing task in each of the devices to be processed based on the device identification identifier, and control each of the devices to be processed to execute the corresponding processing tasks in parallel through the protocol port, so as to perform multi-tasking processing on each of the devices to be processed.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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