Vehicle-mounted application evaluation method and device and computer readable storage medium

Abstract

The invention relates to a vehicle-mounted application evaluation method and device and a computer readable storage medium, and relates to the technical field of new energy automobiles. The method comprises the following steps: acquiring multiple resource attributes of the vehicle-mounted application in a non-running state; based on the resource attributes and at least one evaluation model corresponding to each resource attribute, determining a static performance evaluation result of the vehicle-mounted application; acquiring data of a plurality of operation indexes of the vehicle-mounted application in an operation state; based on the data of the operation indexes and at least one evaluation model corresponding to each operation index, determining a dynamic performance evaluation result of the vehicle-mounted application; wherein the evaluation model of each operation index is constructed based on a reference value of the operation index of the template application and a preset score of the reference value; and according to the weights corresponding to the static performance evaluation result and the dynamic performance evaluation result, fusing the static performance evaluation result and the dynamic performance evaluation result to obtain a vehicle-mounted application evaluation result. By adopting the method, the accuracy of an evaluation result can be improved.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle technology, and in particular to a vehicle-mounted application evaluation method, device, and computer-readable storage medium. Background Art

[0002] In the car system, there are many in-vehicle applications, which cover vehicle settings, Bluetooth phones, multimedia applications, navigation, car assistants and other functions. They are installed in the car system to meet the different functional needs of users. Different in-vehicle applications have different performances. In related technologies, the method of evaluating the performance of applications usually uses a preset test script to test the performance of the application, and evaluates the performance of the application based on the various performance data obtained from the test.

[0003] However, the application performance evaluation methods and evaluation results of related technologies have limitations. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle-mounted application evaluation method, device, new energy vehicle, computer-readable storage medium and computer program product that can improve the accuracy of evaluation results in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a vehicle-mounted application evaluation method, comprising:

[0006] Acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources;

[0007] Determining a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes;

[0008] Acquire data of multiple operating indicators of the vehicle-mounted application in a running state;

[0009] Determine the dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application;

[0010] The static performance evaluation result and the dynamic performance evaluation result are fused according to their respective corresponding weights to obtain the evaluation result of the vehicle-mounted application.

[0011] In combination with the first aspect, in one embodiment, the plurality of resource attributes in the non-operating state include a plurality of resource attributes; and the obtaining of the resource attributes of the vehicle-mounted application in the non-operating state includes:

[0012] Obtaining the installation package size of the in-vehicle application;

[0013] Based on the decompilation result of the installation package of the in-vehicle application, obtaining target file information and target resource information of the in-vehicle application;

[0014] The target file information is information characterizing the file redundancy of the in-vehicle application; the target resource information is information characterizing the resource redundancy and / or the proportion of high-time-consuming resources of the in-vehicle application.

[0015] In combination with the first aspect, in one embodiment, determining the static performance evaluation result of the in-vehicle application based on at least one evaluation model corresponding to each of the resource attributes includes:

[0016] Based on the evaluation model corresponding to the installation package size, determining a comparison result between the installation package size and at least one scoring threshold included in the evaluation model, and determining a performance score of the installation package size according to the comparison result;

[0017] Based on the evaluation model corresponding to the target file information, determining a comparison result between the target file information and at least one scoring threshold included in the evaluation model, and determining a performance score of the target file information according to the comparison result;

[0018] Based on the evaluation model corresponding to the target resource information, determining a comparison result between the target resource information and at least one scoring threshold included in the evaluation model, and determining a performance score of the target resource information according to the comparison result;

[0019] Determining a static performance evaluation result of the in-vehicle application based on the performance score of the installation package size, the performance score of the target file information, and the performance score of the target resource information;

[0020] The evaluation model corresponding to the installation package size, the evaluation model corresponding to the target file information, and the evaluation model corresponding to the target resource information are different from each other.

[0021] In combination with the first aspect, in one embodiment, the data of the operating indicator includes a cold start time and multiple stress test indicator values, and the acquiring the data of the multiple operating indicators of the vehicle-mounted application in the running state includes:

[0022] Calling a preset command line tool to start the in-vehicle application and determining a cold start time of the in-vehicle application;

[0023] The vehicle-mounted application is stress-tested according to a preset stress-testing script to obtain multiple stress-testing indicator values ​​of the vehicle-mounted application.

[0024] In combination with the first aspect, in one embodiment, before determining the dynamic evaluation result of the in-vehicle application based on at least one evaluation model corresponding to the operation indicator, the method further includes:

[0025] Calling the preset command line tool to start the template application, and calling the preset stress testing script to perform stress testing on the template application, to obtain the cold start time and multiple stress testing indicator values ​​of the template application, which are used as reference values ​​of the cold start time and stress testing indicator reference values ​​of various stress testing indicators respectively;

[0026] Obtaining a preset score corresponding to the cold start time reference value of the template application and a preset score corresponding to each stress testing indicator reference value;

[0027] Determine a cold start score proportionality coefficient according to a cold start time reference value and its corresponding preset score, a cold start score threshold and its corresponding cold start time, and construct an evaluation model corresponding to the cold start time based on the cold start score proportionality coefficient;

[0028] According to the stress testing indicator reference value and its corresponding preset score, the stress testing indicator score threshold and its corresponding stress testing indicator value, the stress testing indicator score proportional coefficient of each stress testing indicator is determined, and an evaluation model corresponding to each stress testing indicator is constructed based on the stress testing indicator score proportional coefficient.

[0029] In combination with the first aspect, in one embodiment, determining the dynamic evaluation result of the in-vehicle application based on at least one evaluation model corresponding to each of the operating indicators includes:

[0030] Substituting the cold start time into the evaluation model corresponding to the cold start time, and obtaining a performance score for the cold start time based on a difference between the cold start time and the cold start score threshold and the cold start score proportionality coefficient;

[0031] Substituting the stress test indicator value into the evaluation model corresponding to the stress test indicator, and obtaining a performance score of the stress test indicator value based on a difference between the stress test indicator value and the stress test indicator scoring threshold and the stress test indicator score proportionality coefficient;

[0032] Determining a dynamic performance evaluation result of the in-vehicle application based on the performance score of the cold start time and the performance scores of each of the stress test indicator values;

[0033] The evaluation model corresponding to the stress testing indicator is different from the evaluation model corresponding to the cold start time.

[0034] In combination with the first aspect, in one embodiment, determining the dynamic performance evaluation result of the in-vehicle application based on the performance score of the cold start time and the performance scores of each of the stress test indicator values ​​includes:

[0035] According to the weights corresponding to the performance score of the cold start time and the performance scores of the multiple stress measurement indicator values, the performance score of the cold start time and the performance scores of the multiple stress measurement indicator values ​​are integrated to obtain a dynamic evaluation result of the in-vehicle application.

[0036] In combination with the first aspect, in one embodiment, the method described in any one of the above embodiments further includes:

[0037] Based on the evaluation results of each of the in-vehicle applications in the vehicle system and a preset performance level evaluation model, the performance level of each of the in-vehicle applications is obtained;

[0038] The evaluation results and / or performance levels of the plurality of vehicle-mounted applications in the vehicle-mounted system are displayed.

[0039] In a second aspect, the present application also provides a vehicle-mounted application evaluation device, comprising:

[0040] A first acquisition module is used to acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources;

[0041] A static evaluation module, configured to determine a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes;

[0042] A second acquisition module is used to acquire data of multiple operating indicators of the vehicle-mounted application in a running state;

[0043] a dynamic evaluation module, configured to determine a dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on a reference value of the operating indicator of the template application and a preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application;

[0044] The application evaluation module is used to obtain the evaluation result of the vehicle-mounted application by fusing the static performance evaluation result and the dynamic performance evaluation result according to the weights corresponding to the static performance evaluation result and the dynamic performance evaluation result.

[0045] In a third aspect, the present application further provides a new energy vehicle, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0046] Get multiple resource attributes of the vehicle application in a non-operating state;

[0047] Determine a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources;

[0048] Acquire data of multiple operating indicators of the vehicle-mounted application in a running state;

[0049] Determine the dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application;

[0050] The static performance evaluation result and the dynamic performance evaluation result are fused according to their respective corresponding weights to obtain the evaluation result of the vehicle-mounted application.

[0051] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0052] Acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources;

[0053] Determining a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes;

[0054] Acquire data of multiple operating indicators of the vehicle-mounted application in a running state;

[0055] Determine the dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application;

[0056] The static performance evaluation result and the dynamic performance evaluation result are fused according to their respective corresponding weights to obtain the evaluation result of the vehicle-mounted application.

[0057] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0058] Acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources;

[0059] Determining a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes;

[0060] Acquire data of multiple operating indicators of the vehicle-mounted application in a running state;

[0061] Determine the dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application;

[0062] The static performance evaluation result and the dynamic performance evaluation result are fused according to their respective corresponding weights to obtain the evaluation result of the vehicle-mounted application.

[0063] The above-mentioned vehicle-mounted application evaluation method, device, computer equipment, computer-readable storage medium and computer program product, the method obtains multiple resource attributes (i.e. static attributes) of the vehicle-mounted application in a non-operating state, wherein the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files and the proportion of high-time-consuming resources, and determines the static performance evaluation result of the vehicle-mounted application based on the static attributes and at least one evaluation model corresponding to each static attribute, thereby realizing the performance evaluation of the vehicle-mounted application in a non-operating state. In addition, multiple operating index data (i.e. dynamic operating data) of the vehicle-mounted application in a running state are obtained, and the dynamic performance evaluation result of the vehicle-mounted application is determined based on each dynamic operating data and at least one corresponding evaluation model, thereby realizing the performance evaluation of the vehicle-mounted application in a running state; wherein the evaluation model corresponding to each operating index is constructed based on the reference value of the operating index of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating index of the template application is the same as the test environment of the vehicle-mounted application. Furthermore, according to the weights corresponding to the static performance evaluation results and the dynamic performance evaluation results, the static performance evaluation results and the dynamic performance evaluation results are fused to obtain the evaluation results of the vehicle-mounted application. This method not only combines the static performance evaluation results and the dynamic evaluation results to obtain more comprehensive evaluation results of the vehicle-mounted application, but also considers the importance of the static performance evaluation results and the dynamic evaluation results to the overall performance evaluation results of the vehicle-mounted application, thereby improving the objectivity and accuracy of the performance evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0065] Figure 1 is a flow chart of a method for evaluating an in-vehicle application in one embodiment;

[0066] Figure 2 A schematic diagram of a flow chart of steps for constructing an evaluation model corresponding to an operating indicator in an embodiment;

[0067] Figure 3 A schematic flow chart of the steps of determining a dynamic evaluation result in one embodiment;

[0068] Figure 4 is a structural block diagram of a performance evaluator for an in-vehicle application in one embodiment;

[0069] Figure 5A schematic diagram of a static evaluation process in one embodiment;

[0070] Figure 6 A schematic diagram of a flow chart of a dynamic evaluation step in an embodiment;

[0071] Figure 7 is a structural block diagram of a vehicle-mounted application evaluation device in one embodiment;

[0072] Figure 8 Schematic diagram of the internal structure of a new energy vehicle in one embodiment. DETAILED DESCRIPTION

[0073] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0074] As described in the background technology, the application performance evaluation method of the related technology has the problem of limited evaluation results. The inventors have found that the reason for this problem is that, for example, in a car system based on the Android system, there are in-vehicle applications to be evaluated. These applications are usually in-vehicle applications such as vehicle settings, Bluetooth phones, multimedia applications, navigation, and car assistants. These applications are installed in the car system to meet the different functional requirements of users and the smoothness of system operation. Therefore, it is necessary to perform performance evaluation on each in-vehicle application. In the related technology, the evaluation of the application is usually to analyze the defects of the application code, or to test the performance of the application using a preset test script, and to evaluate the performance of the application based on the various performance data obtained from the test. However, these performance evaluation methods still have limitations and lack more accurate evaluation of the application.

[0075] Based on the above reasons, the present application provides a method for evaluating vehicle-mounted applications, which obtains evaluation results of vehicle-mounted applications by performing static performance evaluation on the static properties of the vehicle-mounted applications and dynamic performance evaluation on the dynamic properties, and integrating the static performance evaluation results and the dynamic performance evaluation results as well as the degree of influence of the two on the application performance, aiming to improve the accuracy of the evaluation results of vehicle-mounted applications.

[0076] In one embodiment, Figure 1 As shown, a method for evaluating vehicle-mounted applications is provided. This embodiment takes the application of this method to a preset performance evaluation application as an example for illustration. It can be understood that the application can be run in the vehicle system or in the vehicle external detection device system. When evaluating, the external device can be connected to the vehicle system. In this embodiment, the method includes the following steps S102 to S110. Among them:

[0077] Step S102, obtaining multiple resource attributes of the vehicle-mounted application in a non-operating state.

[0078] Among them, the in-vehicle application can be application software installed in the car system, such as vehicle settings, Bluetooth phone, multimedia applications, navigation, and car assistant application software, which are used to meet the different needs of car system users.

[0079] The non-running state may be a state in which the vehicle-mounted application is not started, also referred to as a stationary state.

[0080] The resource attributes may be resource-related information that can reflect the performance of the in-vehicle application in a non-operating state, for example, the size of the in-vehicle application installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources.

[0081] Optionally, when the in-vehicle application to be performance evaluated is in a non-operating state, the performance evaluation application reads multiple resource attributes of the in-vehicle application as a basis for subsequent performance evaluation.

[0082] Step S104 : determining a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each resource attribute.

[0083] Among them, the evaluation model corresponding to the resource attributes can be a mathematical model constructed after statistical analysis and regularity analysis of the resource attributes of a large number of vehicle-mounted applications, or an artificial intelligence model obtained by deep learning training of the neural network based on the historical resource attribute data of vehicle-mounted applications.

[0084] Among them, the static performance evaluation result represents the performance evaluation result of the vehicle-mounted application in a non-operating state, and is used to reflect the performance of the vehicle-mounted application in a non-operating state.

[0085] Optionally, the performance evaluation application substitutes the resource attributes into at least one evaluation model corresponding to the resource attributes, performs quantitative scoring or grade classification on the resource attributes according to the evaluation rules of the evaluation model, and determines a static performance evaluation result of the in-vehicle application.

[0086] It should be noted that resource attributes may include multiple resource attributes, each resource attribute corresponds to an evaluation model, different operating indicators correspond to different evaluation models, or each resource attribute may also correspond to multiple evaluation models. For example, evaluation models corresponding to different parameter thresholds are set for each resource attribute. When performing evaluation, the resource attributes are first matched with the parameter thresholds to correspond to the adapted evaluation model.

[0087] Step S106, obtaining data of multiple operating indicators of the vehicle-mounted application in the operating state.

[0088] The running state may be that the in-vehicle application is in a started working state, indicating that the in-vehicle application is in a working state.

[0089] The operating indicators may be numerical values ​​or data used to measure and evaluate the performance of the vehicle-mounted application in the operating state, such as response time, throughput, resource utilization, and latency.

[0090] Optionally, the performance evaluation application starts the vehicle application and dynamically analyzes the vehicle application, reads the log records of the vehicle application during operation, or uses monitoring tools, performance analyzers and other tools to obtain data on multiple operating indicators of the vehicle application in operation.

[0091] Step S108 , determining a dynamic performance evaluation result of the vehicle-mounted application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators.

[0092] Among them, the evaluation model corresponding to the operating indicators can be a mathematical model constructed after statistical analysis and regularity analysis of the operating indicator data of a large number of vehicle-mounted applications, or an artificial intelligence model obtained by deep learning training of the neural network based on the historical operating indicator data of the vehicle-mounted applications.

[0093] Among them, the evaluation model corresponding to each operating indicator is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application.

[0094] Optionally, the performance evaluation application substitutes the operating indicator data into at least one evaluation model corresponding to the data of each operating indicator, performs quantitative scoring or grade classification on the operating indicator data according to the evaluation rules of the evaluation model, and determines the dynamic performance evaluation result of the vehicle-mounted application.

[0095] It should be noted that the operation indicator may include multiple operation indicators, each operation indicator corresponds to an evaluation model, and different operation indicators correspond to different evaluation models.

[0096] Step S110 , according to the weights corresponding to the static performance evaluation result and the dynamic performance evaluation result, the static performance evaluation result and the dynamic performance evaluation result are integrated to obtain the evaluation result of the vehicle-mounted application.

[0097] The weight may be a numerical value used to reflect the importance or influence of the static performance evaluation result or the dynamic performance evaluation result in the overall vehicle application evaluation result.

[0098] The in-vehicle application evaluation result may be information reflecting the overall performance of the in-vehicle application.

[0099] Optionally, the performance evaluation application obtains the preset weight of the static evaluation result and the preset weight of the dynamic evaluation result, and fuses the static performance evaluation result and the dynamic performance evaluation result according to the preset weight of the static evaluation result and the preset weight of the dynamic evaluation result. It can be understood that the fusion method can be to perform weighted summation of the static performance evaluation result and the dynamic performance evaluation result to obtain the evaluation result of the vehicle-mounted application. For example, Score_total=0.3*Score_static+0.7*Score_runtime, where the evaluation result of the vehicle-mounted application is Score_total, Score_static and 0.3 are the static performance evaluation result and its weight respectively, and Score_runtime and 0.7 are the dynamic performance evaluation result and its weight respectively.

[0100] In the above-mentioned vehicle-mounted application evaluation method, the method obtains multiple resource attributes (i.e., static attributes) of the vehicle-mounted application in a non-operating state, wherein the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources, and determines the static performance evaluation result of the vehicle-mounted application based on the static attributes and at least one evaluation model corresponding to each static attribute, thereby realizing the performance evaluation of the vehicle-mounted application in a non-operating state. In addition, the method also obtains data of multiple operating indicators of the vehicle-mounted application in a running state (i.e., dynamic operating data), and determines the dynamic performance evaluation result of the vehicle-mounted application based on each dynamic operating data and at least one evaluation model corresponding to each, thereby realizing the performance evaluation of the vehicle-mounted application in a running state; wherein the evaluation model corresponding to each operating indicator is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the vehicle-mounted application. Furthermore, according to the weights corresponding to the static performance evaluation results and the dynamic performance evaluation results, the static performance evaluation results and the dynamic performance evaluation results are fused to obtain the evaluation results of the vehicle-mounted application. This method not only combines the static performance evaluation results and the dynamic evaluation results to obtain more comprehensive evaluation results of the vehicle-mounted application, but also considers the importance of the static performance evaluation results and the dynamic evaluation results to the overall performance evaluation results of the vehicle-mounted application, thereby improving the objectivity and accuracy of the performance evaluation results.

[0101] In an exemplary embodiment, the resource attributes in the non-operating state include multiple resource attributes; step S102 obtains multiple resource attributes of the vehicle-mounted application in the non-operating state, including:

[0102] The size of the installation package of the vehicle-mounted application is obtained; based on the decompilation result of the installation package of the vehicle-mounted application, the target file information and target resource information of the vehicle-mounted application are obtained.

[0103] The installation package size may be the size of the installation package of the vehicle-mounted application, which is usually related to the specific application and function of the vehicle-mounted application, and the unit is bytes.

[0104] Decompilation can be the decompilation of application software, which refers to the process of converting a compiled program (such as an executable file or a library file) back to a source code that is closer to the source code; the decompilation result usually includes pseudocode or high-level language code, metadata, program logic and resource files, etc.

[0105] Among them, the target file information is information that characterizes the file redundancy of the vehicle-mounted application, such as the number of files with the same name in the SO file (SharedObject file), the number of pictures with the same name in the picture resource folder, and the number of resources defined in the mapping table but not used in the source code; among them, the target resource information is information that characterizes the resource redundancy and / or the proportion of high-time-consuming resources of the vehicle-mounted application, such as the layout depth of the layout file (interface layout file) and the number of frame animation resource files.

[0106] Optionally, the performance evaluation application reads the specification information of the vehicle-mounted application, obtains the size of the installation package of the vehicle-mounted application, and performs a decompilation operation on the installation package of the vehicle-mounted application to obtain the decompilation result, and further loads and parses the resource files and source code in the decompilation result to obtain the target file information and target resource information of the vehicle-mounted application. For example, the SO folder, image resource folder, resource mapping table and source code, layout layout file and drawable (drawable resource) folder are obtained from the decompilation result. In the SO folder and the image resource folder, the number of SO files with the same name and the number of pictures with the same name are determined; the resource mapping table and source code are compared and searched to determine the number of resources defined in the mapping table but not used in the source code; the layout layout file is loaded and parsed to obtain the layout depth of the layout layout file, and the number of layout layout files with a layout depth greater than 2 is determined; the files in the drawable folder are loaded in a loop, and the files found in the file are <animation-list>The standard file of node (an element used by the Android system to define animation in the Extensible Markup Language file) is recorded as a frame animation file, and the number of frame animation files is determined; the number of SO files with the same name and the number of pictures with the same name are determined as target file information, and the number of resources defined in the mapping table but not used in the source code, the number of layout files with a layout depth greater than 2, and the number of frame animation files are determined as target resource information.

[0107] In this embodiment, by obtaining the installation package size, target resource information and target file information of the vehicle-mounted application, the target resource information and target file information can respectively reflect the redundant file information, resource redundancy and proportion of high-time-consuming resources of the vehicle-mounted application, which are used as the basis for the static performance evaluation of the vehicle-mounted application, taking into account the influencing factors of the installation package size occupancy, redundant resources, redundant files and high-time-consuming resources of the vehicle-mounted application, thereby further improving the comprehensiveness and accuracy of the vehicle-mounted application evaluation results.

[0108] In an exemplary embodiment, step S104 determines the static performance evaluation result of the vehicle-mounted application based on at least one evaluation model corresponding to each resource attribute, including:

[0109] Based on the evaluation model corresponding to the installation package size, determine the comparison result between the installation package size and at least one scoring threshold included in the evaluation model, and determine the performance score of the installation package size based on the comparison result; based on the evaluation model corresponding to the target file information, determine the comparison result between the target file information and at least one scoring threshold included in the evaluation model, and determine the performance score of the target file information based on the comparison result; based on the evaluation model corresponding to the target resource information, determine the comparison result between the target resource information and at least one scoring threshold included in the evaluation model, and determine the performance score of the target resource information based on the comparison result; based on the performance score of the installation package size, the performance score of the target file information, and the performance score of the target resource information, determine the static performance evaluation result of the in-vehicle application.

[0110] Among them, the scoring threshold can be a threshold set based on the statistical analysis results of the resource attributes of a large number of vehicle-mounted applications. It can be understood that if there are multiple scoring thresholds, it means that there are multiple interval ranges divided by the thresholds. The comparison results of the resource attributes and the scoring thresholds are different, that is, the resource attributes are in different intervals, then the evaluation principles in the corresponding evaluation model are different; among them, the comparison result can be that the resource attributes are in one of the ranges of the scoring threshold.

[0111] The performance score may be a score obtained by calculating resource attributes according to the scoring principle of the evaluation model.

[0112] Among them, the evaluation model corresponding to the installation package size, the evaluation model corresponding to the target file information, and the evaluation model corresponding to the target resource information are different from each other.

[0113] Optionally, the performance evaluation application determines the comparison result between the installation package size and at least one scoring threshold included in the evaluation model based on the evaluation model corresponding to the installation package size, and determines the performance score of the installation package size based on the comparison result. For example, the full score of the performance score of the installation package size is set to 50 points, and the scoring thresholds of the installation package size are 50 and 150, corresponding to three intervals including (0, 50), [50, 150] and (150, ∞), in units of MB (megabytes). If the comparison result is that the installation package size is less than 50MB, the performance score is 50 points; if the comparison result is that the installation package size is greater than 150MB, the performance score is 0 points; if the comparison result is that the installation package size is greater than or equal to 50MB and less than or equal to 150MB, the corresponding performance score calculation expression in the performance model is: score_1=50-0.5*(x1-50), and the calculation result is an integer, where score_1 is the performance score of the installation package size, and x1 is the installation package size of the vehicle-mounted application.

[0114] Optionally, similar to the calculation method of the installation package size performance score, the performance evaluation application compares the target file information with at least one scoring threshold in the corresponding evaluation model, determines the comparison result between the target file information and at least one scoring threshold, and obtains the performance score of the target file information based on the comparison result and the calculation principle corresponding to the evaluation model. For example, the full score of the performance score of the SO file information is 10 points, and the evaluation model corresponding to the SO file information is:

[0115] score_2=10–2*(x2-1),1≤x2≤6

[0116] score_2=0,x2>6

[0117] Among them, x2 is the number of SO files with the same name, and score_2 is the performance score of the SO file information.

[0118] In addition, the performance score of the image resource file information is 10 points, and the evaluation model corresponding to the image resource file information is:

[0119] score_3=10–(x3-1),1≤x3≤11

[0120] score_3=0,x3>11

[0121] Among them, x3 is the number of pictures with the same name, and score_3 is the performance score of the picture resource file information.

[0122] Optionally, the performance evaluation application compares the target resource information with at least one scoring threshold in the corresponding evaluation model, determines the comparison result between the target resource information and the at least one scoring threshold, and obtains the performance score of the target resource information based on the comparison result and the calculation principle corresponding to the evaluation model. For example, the full score of the performance score of the redundant source code information is 10 points, and the evaluation model corresponding to the redundant source code information is:

[0123] score_4=10–(x4-1),1≤x4≤11

[0124] score_4=0,x4>11

[0125] Among them, x4 is the number of resources defined in the mapping table but not used in the source code, and score_4 is the performance score corresponding to the redundant source code.

[0126] In addition, the performance score of the layout file information is 10 points, and the evaluation model corresponding to the layout file information is:

[0127] score_5=10–x5, 0≤x5≤10

[0128] score_5=0,x5>11

[0129] Among them, x5 is the number of layout files with a layout depth greater than 2, and score_5 is the performance score of the layout file information.

[0130] In addition, the performance score of the frame animation file information is 10 points, and the performance evaluation model corresponding to the frame animation file information is:

[0131] score_6=10–2*x6,0≤x6≤5

[0132] score_6=0,x6>5

[0133] Among them, x6 is the number of frame animation files, and score_6 is the performance score corresponding to the frame animation file information.

[0134] Furthermore, the performance evaluation application determines the sum of the performance score of the installation package size, the performance score of the target file information, and the performance score of the target resource information as the static performance evaluation result of the vehicle-mounted application. For example, the calculation formula for the static performance evaluation result is:

[0135] Score_static=score_1+score_2+score_3+score_4+score_5+score_6

[0136] Among them, Score_static is the static performance evaluation result.

[0137] In this embodiment, the performance score of each resource attribute is quantified through the evaluation model of the installation package size, target file information, and target resource information, so that the pros and cons of the static performance of the in-vehicle application can be reflected more objectively and accurately. In addition, the static performance evaluation results of the in-vehicle application are obtained by integrating the quantified performance scores of resource attributes in multiple aspects, which further improves the comprehensiveness and accuracy of the performance evaluation results.

[0138] In an exemplary embodiment, the data of the operating indicators include cold start time and multiple stress test indicator values. Step S106 obtains data of multiple operating indicators of the vehicle-mounted application in the running state, including:

[0139] Call a preset command line tool to start the vehicle application and determine the cold start time of the vehicle application; perform stress testing on the vehicle application according to a preset stress testing script to obtain multiple stress testing indicator values ​​of the vehicle application.

[0140] Among them, the cold start time can refer to the time required from the first click of the application icon by the user to the full display of the application interface (including all visual elements) when the application is not loaded into the memory. For example, Android application startup includes cold start, hot start, and warm start. Cold start refers to the process in which the application process does not exist and the Activity does not exist. The system first creates a process for the application to be started and then creates an activity. Hot start refers to the process in which the application process exists and the Acitivity to be displayed has not been destroyed. There is no need to recreate the activity, and only the process needs to be switched from the background to the foreground. Warm start refers to the process in which the application process exists and the activity is destroyed, and the system needs to recreate the activity.

[0141] The command line tool may be a tool for interacting with a computer by inputting commands through a text interface (Shell). The command line tool used in this embodiment may be an ADB (Android Debug Bridge) command line tool.

[0142] Among them, the stress testing script can be a script code that automatically executes stress testing, which is used to simulate user behavior, generate traffic or call test interfaces; among them, stress testing can be a testing method that evaluates the performance, stability and reliability of the system (software / hardware) under extreme pressure by simulating high load and extreme conditions.

[0143] Among them, the stress test index value represents the runtime quality of the in-vehicle application under the stress test, including CPU (Central Processing Unit) usage, memory usage, and the freeze rate of the application display frame.

[0144] Optionally, the performance evaluation application calls a preset command line tool to automatically start the vehicle application, and determines the cold start time of the vehicle application by obtaining the "Displayed" time (a performance indicator used to measure the time it takes for the application interface to be first drawn and displayed on the screen). The performance evaluation application calls a preset stress testing script to perform multiple stress tests on the vehicle application using the Monkey tool (a stress testing tool for the Android system) to obtain multiple stress testing indicator values ​​for the vehicle application. It is understandable that the Monkey tool will automatically generate and send user events until the test ends or a certain stop condition is met. The test end condition can be that a preset number of tests are met. When the Monkey tool executes the test, the technician can specify parameters such as the test time, event frequency, and installation package name.

[0145] In this embodiment, starting the in-vehicle application through the command line tool can better realize the automation of the performance evaluation process, and obtaining performance data in multiple aspects such as cold start time and multiple stress test indicator values ​​provides data support for the subsequent dynamic performance evaluation of the in-vehicle application, further improving the comprehensiveness and accuracy of the performance evaluation results.

[0146] In an exemplary embodiment, Figure 2 As shown, before step S108 determines the dynamic evaluation result of the vehicle-mounted application based on at least one evaluation model corresponding to each of the operating indicators, it also includes:

[0147] Step S202, calling a preset command line tool to start the template application, and calling a preset stress testing script to perform stress testing on the template application, to obtain the cold start time and multiple stress testing indicator values ​​of the template application, which are used as reference values ​​for the cold start time and stress testing indicator reference values ​​for various stress testing indicators, respectively.

[0148] The template application may be a pre-set reference application for testing the performance of other vehicle-mounted applications.

[0149] Optionally, the performance evaluation application calls the preset command line tool to start the template application, and the performance evaluation application calls the preset stress test script to stress test the template application, and obtains the cold start time and multiple stress test indicator values ​​of the template application. The stress test indicator values ​​also include CPU usage, memory usage, application display frame freeze rate, etc. The cold start time of the template application is used as a reference value for the cold start time, and the multiple stress test indicator values ​​of the template application are used as stress test indicator reference values ​​for various stress test indicators. It should be noted that the template application includes the use of a thread pool with 5 threads to perform time-consuming tasks. The time-consuming tasks include network requests to load images, database operations, and image list display. The test environment of the template application is the same as that of the vehicle-mounted application. As a reference application, the template application can isolate the impact caused by the hardware capabilities of the vehicle system.

[0150] Step S204, obtaining a preset score corresponding to the reference value of the cold start time of the template application and a preset score corresponding to the reference value of each stress testing indicator.

[0151] Among them, the preset score can be a reference score set by the technician based on the performance of the template application.

[0152] Optionally, the performance evaluation application obtains a preset score corresponding to a reference value of the cold start time of the template application and a preset score corresponding to a reference value of each stress testing indicator, paving the way for subsequent construction of an evaluation model.

[0153] Step S206, determining a cold start score proportionality coefficient according to the cold start time reference value and its corresponding preset score, the cold start score threshold and its corresponding cold start time, and constructing an evaluation model corresponding to the cold start time based on the cold start score proportionality coefficient.

[0154] Among them, the scoring threshold can be a threshold set based on the statistical analysis results of the dynamic performance of a large number of vehicle-mounted applications. It can be understood that there can be multiple scoring thresholds, and the characterization threshold range can include multiple ranges. If the comparison results between the operating indicators and the scoring thresholds are different, the evaluation principles in the corresponding evaluation model will be different.

[0155] Among them, the cold start score ratio coefficient is used to adjust the scoring criteria of the evaluation model according to the performance of the template application, thereby isolating the impact of the hardware capabilities of the vehicle system on the performance evaluation results.

[0156] Optionally, the performance evaluation application determines the cold start score proportionality coefficient according to the cold start time reference value and its corresponding preset score, the cold start score threshold and its corresponding cold start time, and constructs an evaluation model corresponding to the cold start time based on the cold start score proportionality coefficient and the preset scoring rule. For example, the full score of the cold start time performance score is 100 points, the cold start time reference value is time_temp, the scoring threshold is 0.5s, and the preset score corresponding to the cold start time reference value is 80 points, then the cold start score proportionality coefficient is 20 / (time_temp-0.5).

[0157] Step S208, determining the stress testing indicator score ratio coefficient of each stress testing indicator according to the stress testing indicator reference value and its corresponding preset score, the stress testing indicator score threshold and its corresponding stress testing indicator value, and constructing an evaluation model corresponding to each stress testing indicator based on the stress testing indicator score ratio coefficient.

[0158] Optionally, the performance evaluation application determines the stress test indicator score ratio coefficient of each stress test indicator according to the stress test indicator reference value and its corresponding preset score, the stress test indicator score threshold and its corresponding stress test indicator value, and constructs the evaluation model corresponding to each stress test indicator based on the stress test indicator score ratio coefficient and the preset scoring rule. It can be understood that the method for determining the stress test indicator score ratio coefficient is the same as the principle for determining the cold start time score ratio coefficient. For example, the stress test indicator value is CPU occupancy, the full score of the performance score is 100 points, the stress test indicator reference value of CPU occupancy is cpu_temp, and one of the scoring thresholds is 40%, then the stress test indicator score ratio coefficient of CPU occupancy is 20 / (cpu_temp-40%).

[0159] In this embodiment, the template application is stress tested, the cold start time of the template application and multiple stress test indicator values ​​are used as reference values, and the proportional coefficient is determined by comprehensively combining the scoring threshold, reference value and preset score, and then a performance evaluation model is further constructed. The scoring criteria of the evaluation model are adjusted according to the performance of the template application, thereby isolating the impact of the hardware capabilities of the vehicle system on the performance evaluation results.

[0160] In an exemplary embodiment, Figure 3 As shown, step S108 determines the dynamic evaluation result of the vehicle-mounted application based on at least one evaluation model corresponding to each of the operating indicators, including:

[0161] Step S302: Substitute the cold start time into the evaluation model corresponding to the cold start time, and obtain the performance score of the cold start time based on the difference between the cold start time and the cold start score threshold and the cold start score proportional coefficient.

[0162] Optionally, the performance evaluation application substitutes the cold start time of the vehicle application into the evaluation model corresponding to the cold start time, compares the cold start time with the scoring threshold, and when the comparison result is that the cold start time is within the range to be calculated, the performance score of the cold start time is obtained based on the difference between the cold start time and the cold start scoring threshold and the cold start score proportional coefficient; when the comparison result is that the cold start time is less than or equal to the lower limit of the range to be calculated, the performance score is full marks; when the comparison result is that the cold start time is greater than or equal to the upper limit of the range to be calculated, the performance score is zero. For example, the full score of the performance score of the cold start time is 100 points, then the evaluation model corresponding to the cold start time is:

[0163] score_time_A=100-20 / (time_temp-0.5)*(time_A-0.5),0.5<time_A<3

[0164] score_time_A=100,time_A≤0.5

[0165] score_time_A=0,time_A≥3

[0166] Among them, score_time_A is the performance score of the cold start time, 20 / (time_temp-0.5) is the cold start score proportional coefficient, time_temp is the reference value of the cold start time, and time_A is the cold start time of the vehicle application.

[0167] Step S304: Substitute the stress test indicator value into the evaluation model corresponding to the stress test indicator, and obtain the performance score of the stress test indicator value based on the difference between the stress test indicator value and the stress test indicator scoring threshold and the stress test indicator score ratio coefficient.

[0168] The evaluation model corresponding to the stress testing indicator is different from the evaluation model corresponding to the cold start time.

[0169] Optionally, the performance evaluation application substitutes the stress test index value of the vehicle application into the evaluation model corresponding to the stress test index value, compares the stress test index value with the scoring threshold, and when the comparison result is that the stress test index value is within the range to be calculated, the performance score of the stress test index value is obtained based on the difference between the stress test index value and the scoring threshold of the stress test index value and the stress test index score proportional coefficient; when the comparison result is that the stress test index value is lower than or equal to the lower limit of the range to be calculated, the performance score is full marks; when the stress test index value is greater than or equal to the upper limit of the range to be calculated during cold start, the performance score is zero. For example, the full score of the performance score of each stress test index value is 100 points, and when the stress test index value is CPU occupancy, the corresponding evaluation model is:

[0170] score_cpu_A=100-20 / (cpu_temp-40%)*(cpu_A-40%), 40%<cpu_A<200%

[0171] score_cpu_A=100, cpu_A≤40%

[0172] score_cpu_A=0, cpu_A≥200%

[0173] Among them, score_cpu is the performance score of CPU occupancy, cpu_A is the CPU occupancy of the vehicle application, 20 / (cpu_temp-40%) is the stress test indicator score ratio coefficient of CPU occupancy, and cpu_temp is the stress test indicator reference value of CPU occupancy.

[0174] In addition, when the stress test indicator value is memory usage, the corresponding evaluation model is:

[0175] score_mem_A=100-20 / (mem_temp-80)*(mem_A-80),80<mem_A<600

[0176] score_mem_A=100, mem_A≤80

[0177] score_mem_A=0, mem_A≥600

[0178] Among them, score_mem_A is the performance score of memory usage, mem_A is the memory usage of the vehicle application, in MB, 20 / (mem_temp-80) is the score ratio coefficient of the stress test indicator of memory usage, and mem_temp is the reference value of the stress test indicator of memory usage.

[0179] In addition, when the stress test indicator value is the jam rate of the application display frame, the corresponding evaluation model is:

[0180] score_frame_A=100-20 / (frame_temp-0.5%)*(frame_A-50%), 0.5%<frame_A<50%

[0181] score_frame_A=100,frame_A≤0.5%

[0182] score_frame_A=0,frame_A≥50%

[0183] Among them, score_frame_A is the performance score of the jam rate of the application display frame, frame_A is the jam rate of the application display frame of the in-vehicle application, 20 / (frame_temp-80) is the stress test indicator score ratio coefficient of the application display frame jam rate, and frame_temp is the stress test indicator reference value of the application display frame jam rate.

[0184] Step S306 , determining a dynamic performance evaluation result of the vehicle-mounted application based on the performance score of the cold start time and the performance scores of various stress test indicator values.

[0185] Optionally, the performance evaluation application comprehensively considers the performance score of the cold start time and the performance scores of various stress test indicator values, and determines the comprehensive result as the dynamic performance evaluation result of the in-vehicle application.

[0186] In this embodiment, the performance score of each operating indicator is quantified through an evaluation model of cold start time and multiple stress test index values, so that the pros and cons of the dynamic performance of the vehicle-mounted application can be reflected more objectively and accurately. In addition, the dynamic performance evaluation results of the vehicle-mounted application are obtained by integrating the quantified performance scores of multiple aspects of operating indicators, which further improves the comprehensiveness and accuracy of the performance evaluation results.

[0187] In an exemplary embodiment, step S306 determines the dynamic performance evaluation result of the vehicle application based on the performance score of the cold start time and the performance scores of various stress test index values, including:

[0188] According to the weights corresponding to the performance score of the cold start time and the performance scores of multiple stress test indicator values, the performance score of the cold start time and the performance scores of multiple stress test indicator values ​​are integrated to obtain the dynamic evaluation result of the vehicle application.

[0189] Among them, the weight can represent the influence and importance of the cold start time and various stress test index values ​​on the dynamic performance evaluation results, and can be set according to actual scoring requirements and experience.

[0190] Optionally, the performance evaluation application obtains the weights corresponding to the performance scores of the cold start time and the performance scores of multiple stress test index values, and performs weighted summation processing on the performance scores of the cold start time and the performance scores of multiple stress test index values ​​to obtain the dynamic evaluation result of the vehicle-mounted application. For example, Score_runtime=0.7*(0.1*score_time_A+0.3*score_cpu_A+0.3*score_mem_A+0.3*score_frame_A), where Score_runtime is the dynamic evaluation result of the vehicle-mounted application, score_time_A and 0.1 respectively represent the performance score and weight of the cold start time, score_cpu_A and 0.3 respectively represent the performance score and weight of the CPU occupancy rate, score_mem_A and 0.3 respectively represent the performance score and weight of the memory occupancy, and score_frame_A and 0.3 respectively represent the performance score and weight of the freeze rate of the application display frame.

[0191] In this embodiment, by assigning different weights to different operating indicators (such as cold start time, CPU occupancy, memory occupancy, and display frame freeze rate), and performing weighted summation to obtain the dynamic performance evaluation results of the vehicle-mounted application, the performance of the vehicle-mounted application can be evaluated more comprehensively, thereby improving the reliability of the performance evaluation.

[0192] In an exemplary embodiment, the method described in any one of the above embodiments further includes:

[0193] Based on the evaluation results of each vehicle-mounted application in the vehicle-mounted system and a preset performance level evaluation model, the performance level of each vehicle-mounted application is obtained; and the evaluation results and / or performance levels of multiple vehicle-mounted applications in the vehicle-mounted system are displayed.

[0194] The preset performance level evaluation model may be a performance evaluation result interval range and a level mapping table set based on experience, or a classification model obtained by training a neural network based on historical performance evaluation results.

[0195] Among them, the performance level can be used to characterize the overall performance of the vehicle-mounted application. For example, the performance levels include unqualified, qualified, good and excellent.

[0196] Optionally, the performance evaluation application inputs the evaluation results of each vehicle-mounted application in the vehicle-mounted system into a preset performance level evaluation model to obtain the performance level of each vehicle-mounted application. For example, the performance level evaluation model is: the performance level of applications with a performance score lower than 60 points is unqualified, the performance level of vehicle-mounted applications with a performance evaluation result between [60, 70) is qualified, the performance level of vehicle-mounted applications with a performance evaluation result between [70, 90) is good, and the performance level of vehicle-mounted applications with a performance evaluation result between [90, 100] is excellent. Furthermore, the performance evaluation application integrates the evaluation results and / or performance levels of all vehicle-mounted applications and displays them through the display page of the vehicle-mounted system. It is understandable that the evaluation results and / or performance levels can be displayed directly on the vehicle screen or on the display screen of the external device.

[0197] In this embodiment, the performance results of the application are divided into multiple performance levels through a preset performance level evaluation model. This standardized evaluation method makes the performance evaluation process transparent and easy to understand, which helps the team and decision makers to quickly obtain the performance status of each application and thus formulate specific optimization plans.

[0198] In an exemplary embodiment, Figure 4 As shown, a performance evaluator for vehicle-mounted applications is provided, which is deployed in the vehicle system and includes a static evaluation module, a dynamic evaluation module and a scoring module. Among them:

[0199] Static evaluation modules, such as Figure 5 As shown, a flow chart of static evaluation is provided; it is used to read the in-vehicle applications to be evaluated respectively. The in-vehicle applications to be evaluated are all applications that have been installed in the vehicle system. Take application A.apk as an example. The static evaluation module mainly evaluates the resource usage of the application in the non-running state. The static performance attribute has a smaller impact on the system performance than the running state. According to experience, the proportion is 0.3, the static total score is 100 points, and the total score is 30 points when the application score is finally calculated. Among them, the scores based on the impact on the application volume are 50 points for the APK package size, and the other five static influencing factors (target file information and target resource information), including multi-architecture SO folders (the number of files with the same name in the SO file), multi-resolution image resource folders (the number of images with the same name in the image resource folder), useless resources (the number of resources that are defined in the mapping table but not used in the source code), Layout layout level (layout depth of layout layout file) and frame animation resources (the number of frame animation resource files) are 10 points respectively. The static performance of the in-vehicle application to be evaluated is scored to obtain the static performance score (static performance evaluation result).

[0200] Dynamic evaluation modules, such as Figure 6 As shown in the figure, a flow chart of dynamic evaluation is provided; it is used to evaluate the performance (operation index) of the application at runtime, run the application to be tested through ADB Shell, and perform stress test (stress test) on application A through the Monkey tool. The test results include cold start speed (cold start time), CPU usage (CPU occupancy), memory usage, and the jam rate of application display frames. According to the importance of each performance, the cold start speed accounts for 10 points in the dynamic monitoring module, and the CPU occupancy, memory usage, and the jam rate of application display frames account for 30 points respectively. The template application is tested by mokey to obtain the startup speed, CPU usage, memory usage, and jam rate of the application display frame. The template application uses a thread pool with 5 threads to perform time-consuming tasks, including network requests to load pictures, database operations, and picture list display. The template application is used as a reference application to isolate the impact of the hardware capabilities of the vehicle system. Assume that the values ​​of the four dynamic performances of the template application are time_temp, cpu_temp, mem_temp, and frame_temp; all data of the template application are taken as 80 points to compare the parameter scores of other applications. In this way, the dynamic performance score (dynamic performance evaluation result) is obtained.

[0201] The scoring module is used to obtain the final score of application A by combining the static performance score and the dynamic performance score, and assign corresponding grades such as qualified, unqualified, good and excellent to the application according to the score. Each of the above-mentioned applications to be tested is polled to finally obtain the performance score and performance grade of each application in the vehicle computer, and the application name, performance score and performance grade are displayed.

[0202] In this embodiment, the performance of the application is comprehensively evaluated through multiple performance factors in two dimensions, static and running, so as to comprehensively evaluate the performance of the vehicle system application, so that the application developer or tester can intuitively know the performance and performance level of the application.

[0203] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0204] Based on the same inventive concept, the embodiment of the present application also provides a vehicle-mounted application evaluation device for implementing the vehicle-mounted application evaluation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle-mounted application evaluation device embodiments provided below can refer to the limitations of the vehicle-mounted application evaluation method above, and will not be repeated here.

[0205] In an exemplary embodiment, Figure 7 As shown, a vehicle-mounted application evaluation device 700 is provided, comprising: a first acquisition module 701, a static evaluation module 702, a second acquisition module 703, a dynamic evaluation module 704 and an application evaluation module 705, wherein:

[0206] The first acquisition module 701 is used to acquire multiple resource attributes of the vehicle-mounted application in a non-running state.

[0207] The static evaluation module 702 is used to determine the static performance evaluation result of the vehicle-mounted application based on the resource attributes and at least one evaluation model corresponding to each resource attribute.

[0208] The second acquisition module 703 is used to acquire data of multiple operating indicators of the vehicle-mounted application in the operating state.

[0209] The dynamic evaluation module 704 is used to determine the dynamic performance evaluation result of the vehicle-mounted application based on the data of the operating indicators and at least one evaluation model corresponding to each operating indicator.

[0210] The application evaluation module 705 is used to obtain the vehicle-mounted application evaluation result by fusing the static performance evaluation result and the dynamic performance evaluation result according to their respective corresponding weights.

[0211] Furthermore, in one embodiment, the first acquisition module 701 is also used to obtain the size of the installation package of the vehicle-mounted application; based on the decompilation result of the installation package of the vehicle-mounted application, obtain the target file information and target resource information of the vehicle-mounted application; the target file information is information characterizing the file redundancy of the vehicle-mounted application; the target resource information is information characterizing the resource redundancy and / or the proportion of high-time-consuming resources of the vehicle-mounted application.

[0212] Further, in one embodiment, the static evaluation module 702 is also used to determine the comparison result between the installation package size and at least one scoring threshold based on the evaluation model corresponding to the installation package size, and determine the performance score of the installation package size from the comparison result; determine the comparison result between the target file information and at least one scoring threshold based on the evaluation model corresponding to the target file information, and determine the performance score of the target file information from the comparison result; determine the comparison result between the target resource information and at least one scoring threshold based on the evaluation model corresponding to the target resource information, and determine the performance score of the target resource information from the comparison result; determine the static performance evaluation result of the in-vehicle application based on the performance score of the installation package size, the performance score of the target file information, and the performance score of the target resource information.

[0213] Furthermore, in one embodiment, the second acquisition module 703 is also used to call a preset command line tool to start the vehicle-mounted application and determine the cold start time of the vehicle-mounted application; perform stress testing on the vehicle-mounted application according to a preset stress testing script to obtain multiple stress testing indicator values ​​of the vehicle-mounted application; the stress testing indicator values ​​represent the runtime quality of the vehicle-mounted application under the stress test.

[0214] Furthermore, in one embodiment, the dynamic evaluation module 704 is also used to call a preset stress testing script to perform stress testing on the template application, obtain the cold start time and multiple stress testing indicator values ​​of the template application, respectively as the cold start time reference value and the stress testing indicator reference value of each stress testing indicator; obtain the preset score corresponding to the cold start time reference value of the template application, and the preset score corresponding to each stress testing indicator reference value; determine the cold start score proportional coefficient according to the cold start time reference value and its corresponding preset score, the cold start score threshold and its corresponding cold start time, and construct an evaluation model corresponding to the cold start time based on the cold start score proportional coefficient; determine the stress testing indicator score proportional coefficient according to the stress testing indicator reference value and its corresponding preset score, the stress testing indicator score threshold and its corresponding stress testing indicator value, and construct an evaluation model corresponding to the stress testing indicator value based on the stress testing indicator score proportional coefficient.

[0215] Furthermore, in one embodiment, the dynamic evaluation module 704 is also used to substitute the cold start time into the evaluation model corresponding to the cold start time, and obtain the performance score of the cold start time based on the difference between the cold start time and the cold start score threshold and the cold start score ratio coefficient; substitute the stress test index value into the evaluation model corresponding to the stress test index value, and obtain the performance score of the stress test index value based on the difference between the stress test index value and the stress test index score threshold and the stress test index score ratio coefficient; determine the dynamic performance evaluation result of the vehicle-mounted application based on the performance score of the cold start time and the performance scores of each stress test index value.

[0216] Furthermore, in one embodiment, the dynamic evaluation module 704 is also used to obtain a dynamic evaluation result of the vehicle-mounted application by integrating the performance score of the cold start time and the performance scores of the multiple stress testing indicator values ​​according to their respective corresponding weights.

[0217] Furthermore, in one embodiment, the application evaluation module 705 is also used to obtain the performance level of each vehicle-mounted application based on the evaluation results of each vehicle-mounted application in the vehicle-mounted system and a preset performance level evaluation model; and to display the performance levels of multiple vehicle-mounted applications in the vehicle-mounted system.

[0218] Each module in the vehicle-mounted application evaluation device 700 can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0219] In one embodiment, a new energy vehicle 800 is also provided, whose internal structure is as follows: Figure 8 As shown, it includes a memory 801 and a processor 802. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0220] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0221] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0222] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0223] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0224] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle application evaluation method, characterized in that: The method comprises: Acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources; Determining a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes; Acquire data of multiple operating indicators of the vehicle-mounted application in a running state; Determine the dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on the reference value of the operating indicator of the template application and the preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application; The static performance evaluation result and the dynamic performance evaluation result are fused according to their respective corresponding weights to obtain the evaluation result of the vehicle-mounted application.

2. The method according to claim 1, characterized in that The obtaining of multiple resource attributes of the vehicle-mounted application in a non-operating state includes: Obtaining the installation package size of the in-vehicle application; Based on the decompilation result of the installation package of the in-vehicle application, obtaining target file information and target resource information of the in-vehicle application; The target file information is information characterizing the file redundancy of the in-vehicle application; the target resource information is information characterizing the resource redundancy and / or the proportion of high-time-consuming resources of the in-vehicle application.

3. The method according to claim 2, characterized in that Determining a static performance evaluation result of the in-vehicle application based on at least one evaluation model corresponding to each of the resource attributes includes: Based on the evaluation model corresponding to the installation package size, determining a comparison result between the installation package size and at least one scoring threshold included in the evaluation model, and determining a performance score of the installation package size according to the comparison result; Based on the evaluation model corresponding to the target file information, determining a comparison result between the target file information and at least one scoring threshold included in the evaluation model, and determining a performance score of the target file information according to the comparison result; Based on the evaluation model corresponding to the target resource information, determining a comparison result between the target resource information and at least one scoring threshold included in the evaluation model, and determining a performance score of the target resource information according to the comparison result; Determining a static performance evaluation result of the in-vehicle application based on the performance score of the installation package size, the performance score of the target file information, and the performance score of the target resource information; Among them, the evaluation model corresponding to the installation package size, the evaluation model corresponding to the target file information, and the evaluation model corresponding to the target resource information are different from each other.

4. The method according to claim 1, characterized in that: The data of the operation index includes the cold start time and multiple stress test index values. The data of the multiple operation indexes of the vehicle-mounted application in the running state are obtained, including: Calling a preset command line tool to start the in-vehicle application and determining a cold start time of the in-vehicle application; The vehicle-mounted application is stress-tested according to a preset stress-testing script to obtain multiple stress-testing indicator values ​​of the vehicle-mounted application.

5. The method according to claim 4, characterized in that Before determining the dynamic evaluation result of the vehicle-mounted application based on at least one evaluation model corresponding to each of the operating indicators, the method further includes: Calling the preset command line tool to start the template application, and calling the preset stress testing script to perform stress testing on the template application, to obtain the cold start time and multiple stress testing indicator values ​​of the template application, which are used as reference values ​​of the cold start time and stress testing indicator reference values ​​of various stress testing indicators respectively; Obtaining a preset score corresponding to the cold start time reference value of the template application and a preset score corresponding to each stress testing indicator reference value; Determine a cold start score proportionality coefficient according to a cold start time reference value and its corresponding preset score, a cold start score threshold and its corresponding cold start time, and construct an evaluation model corresponding to the cold start time based on the cold start score proportionality coefficient; According to the stress testing indicator reference value and its corresponding preset score, the stress testing indicator score threshold and its corresponding stress testing indicator value, the stress testing indicator score proportional coefficient of each stress testing indicator is determined, and an evaluation model corresponding to each stress testing indicator is constructed based on the stress testing indicator score proportional coefficient.

6. The method according to claim 5, characterized in that Determining a dynamic evaluation result of the in-vehicle application based on at least one evaluation model corresponding to each of the operating indicators includes: Substituting the cold start time into the evaluation model corresponding to the cold start time, and obtaining a performance score for the cold start time based on a difference between the cold start time and the cold start score threshold and the cold start score proportionality coefficient; Substituting the stress test indicator value into the evaluation model corresponding to the stress test indicator, and obtaining a performance score of the stress test indicator value based on a difference between the stress test indicator value and the stress test indicator scoring threshold and the stress test indicator score proportionality coefficient; Determining a dynamic performance evaluation result of the in-vehicle application based on the performance score of the cold start time and the performance scores of each of the stress test indicator values; The evaluation model corresponding to the stress testing indicator is different from the evaluation model corresponding to the cold start time.

7. The method according to claim 6, characterized in that Determining a dynamic performance evaluation result of the vehicle-mounted application based on the performance score of the cold start time and the performance scores of each of the stress test indicator values ​​includes: According to the weights corresponding to the performance score of the cold start time and the performance scores of the multiple stress measurement indicator values, the performance score of the cold start time and the performance scores of the multiple stress measurement indicator values ​​are integrated to obtain a dynamic evaluation result of the in-vehicle application.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: Based on the evaluation results of each of the in-vehicle applications in the vehicle system and a preset performance level evaluation model, the performance level of each of the in-vehicle applications is obtained; The evaluation results and / or performance levels of the plurality of vehicle-mounted applications in the vehicle-mounted system are displayed.

9. A vehicle-mounted application evaluation device, characterized in that: The device comprises: A first acquisition module is used to acquire multiple resource attributes of the vehicle-mounted application in a non-operating state; the resource attributes include at least two of the size of the installation package, the number of redundant resources, the number of redundant files, and the proportion of high-time-consuming resources; A static evaluation module, configured to determine a static performance evaluation result of the in-vehicle application based on the resource attributes and at least one evaluation model corresponding to each of the resource attributes; A second acquisition module is used to acquire data of multiple operating indicators of the vehicle-mounted application in a running state; a dynamic evaluation module, configured to determine a dynamic performance evaluation result of the in-vehicle application based on the data of the operating indicators and at least one evaluation model corresponding to each of the operating indicators; the evaluation model corresponding to each of the operating indicators is constructed based on a reference value of the operating indicator of the template application and a preset score corresponding to the reference value; the test environment of the reference value of the operating indicator of the template application is the same as the test environment of the in-vehicle application; The application evaluation module is used to obtain the evaluation result of the vehicle-mounted application by fusing the static performance evaluation result and the dynamic performance evaluation result according to the weights corresponding to the static performance evaluation result and the dynamic performance evaluation result.

10. 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 8 are implemented.

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