CN117076316A - Vehicle-mounted application testing method, system, electronic equipment and storage medium - Google Patents
Vehicle-mounted application testing method, system, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a vehicle-mounted application testing method, a system, electronic equipment and a storage medium, wherein the method comprises the steps of obtaining interface element information of different vehicle-mounted applications, wherein the interface element information comprises a plurality of interaction elements, generating a plurality of operation data based on the plurality of interaction elements and a trained operation model, generating at least one test scene by using the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relation with the interaction elements, the trained operation model is obtained by training based on historical operation scenes of a vehicle machine, compiling each test scene to obtain a test case set corresponding to each test scene, and testing the vehicle-mounted application of a vehicle to be tested; the automatic generation of the test scene and the automatic compiling of the test case set can be realized, and manual writing is replaced by automatic operation, so that the coverage rate of the test scene and the quality of the test case are improved, the test efficiency and the automation degree are improved, and the labor cost is reduced.
Description
Technical Field
The application relates to the technical field of vehicle testing, in particular to a vehicle-mounted application testing method, a vehicle-mounted application testing system, electronic equipment and a storage medium.
Background
At present, with the development of intelligent automobiles, an in-vehicle information entertainment system is also called an intelligent cabin system, a car machine or a car machine system is an important component part of interaction between a user and a vehicle, and is a multimedia product integrating in-vehicle navigation, bluetooth, wi-Fi (wireless network), radio, audio and video, intelligent voice prompt and the like, and the multimedia product is called an in-vehicle application, comprises a system application and a third party application, is used as an important entrance of the automobile as the information entertainment system tends to be intelligent, the functional complexity of the information entertainment system is synchronously increased, and the requirement of the user on the in-vehicle information entertainment system is also higher and higher, not only is the diversification of basic functions of the information entertainment system, but also the requirement on the stability and the accuracy of the whole system is embodied. Therefore, testing of in-vehicle infotainment systems is particularly important. In-vehicle infotainment system testing is also known as in-vehicle application testing, or intelligent cabin automation testing. The existing vehicle-mounted application testing method has the problems of lagging testing method, low intelligent degree, low automatic execution duty ratio and the like.
Chinese patent CN111737153B discloses an automated testing method and system for a vehicle machine, which uses a developer to design test cases in advance or create test cases according to test requirements, and then converts the test cases into a case set identifiable by the machine, thus having large time consumption, low efficiency and high labor cost. Chinese patent CN112241361A discloses a test case generation method and device, which are used for generating a test case set by acquiring elements of a user interface to be tested during each test, and have the problems of slow test, low test efficiency and the like.
Disclosure of Invention
In view of the above drawbacks of the prior art, the present application provides a vehicle-mounted application testing method, a system, an electronic device and a storage medium, so as to solve the technical problems of low automation degree, slow testing and low testing efficiency of the testing method.
The application provides a vehicle-mounted application testing method, which comprises the following steps: acquiring interface element information of different vehicle-mounted applications, wherein the interface element information comprises a plurality of interaction elements; generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, generating at least one test scene by utilizing the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relation with the interaction elements, and the trained operation model is obtained based on historical operation scene training of the vehicle and the machine; compiling the test scenes to obtain a test case set corresponding to each test scene so as to test the vehicle-mounted application of the vehicle to be tested.
In an embodiment of the present application, generating a plurality of operation data based on the plurality of interaction elements and the trained operation model includes: establishing a classification model based on different element attributes, so that the classification model classifies the plurality of interaction elements to obtain different interaction element classes, wherein each interaction element class comprises a plurality of interaction elements with the same element attributes, and the interaction elements have corresponding element attributes; and sequentially inputting the interactive elements in all the interactive element classes into the trained operation model to obtain the plurality of operation data.
In an embodiment of the present application, generating at least one test scenario using the plurality of interaction elements and the plurality of operation data includes: determining a plurality of target interaction elements from the plurality of interaction elements according to each preset scene generation condition, and determining operation data corresponding to each target interaction element as target operation data; combining target operation data corresponding to each target interaction element according to an element level to generate each test scene, wherein the interaction elements also have corresponding element levels; or inputting the plurality of interaction elements and the plurality of operation data into a preset scene generation model, so that the preset scene generation model determines a plurality of target interaction elements and target operation data corresponding to each target interaction element according to each preset scene generation condition to generate each test scene, and the preset scene generation model is obtained based on the historical operation scene training of the vehicle.
In an embodiment of the present application, compiling each test scenario to obtain a test case set corresponding to each test scenario includes: performing language identification on the test scene, compiling a plurality of test scripts and assertions corresponding to each test script according to identification results, wherein the test scripts are obtained based on operation processes in the target operation data, and the assertions are obtained based on operation results in the target operation data; generating test cases based on the test scripts and assertions corresponding to the test scripts to obtain a plurality of test cases; and configuring a hierarchical relationship for each test case according to the element hierarchy to obtain the test case set, wherein the test cases have a corresponding relationship with the target interaction elements.
In an embodiment of the present application, after compiling each test scenario to obtain a test case set corresponding to each test scenario, the vehicle-mounted application testing method includes: acquiring test requirement information, generating a target task according to the test requirement information, wherein the test requirement information is determined based on an updated function or version of the vehicle-mounted application; determining a target test case set corresponding to the target task according to a preset task-test case set association condition, wherein the target test case set comprises a plurality of target test cases; and generating a test instruction based on the target test case and sending the test instruction to the to-be-tested vehicle to perform vehicle-mounted application test.
In an embodiment of the present application, after performing the vehicle application test, the vehicle application test method includes: receiving a test result corresponding to each target test case returned by the vehicle to be tested; and generating a test report based on the target task, the identification information of the to-be-tested vehicle and the test result corresponding to each target test case.
In an embodiment of the present application, after generating a test report based on the target task, the identification information of the vehicle to be tested, and the test result corresponding to each target test case, the vehicle-mounted application test method includes: acquiring a plurality of test reports; counting the test results corresponding to different target test cases based on the plurality of test reports to obtain a passing ratio of the test results corresponding to each target test case; if the passing ratio is greater than or equal to a preset threshold, the priority of the target test case corresponding to the passing ratio is reduced, and each test case is configured with priority; and if the passing ratio is smaller than the preset threshold, the priority of the target test case corresponding to the passing ratio is improved.
In an embodiment of the present application, obtaining interface element information of different vehicle applications includes: acquiring user interface images of each level of different vehicle-mounted applications; identifying the user interface image of each level to obtain a plurality of interface elements and element attributes of each interface element; screening out the plurality of interactive elements from all interface elements according to the element attributes, and determining an element level corresponding to each interactive element according to the level of the user interface image where each interactive element is located; and determining the plurality of interaction elements and the element attribute and the element level corresponding to each interaction element as the interface element information.
In an embodiment of the present application, before generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, the vehicle-mounted application testing method includes: acquiring the history operation scene of the vehicle machine; determining a plurality of interactive element samples according to the history operation scene of the vehicle and machine, and compiling an operation process sample and an operation result sample corresponding to each interactive element sample to generate a training sample set; and training the operation model through the training sample set to obtain the trained operation model.
In an embodiment of the present application, there is also provided a vehicle-mounted application test system, including: the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring interface element information of different vehicle-mounted applications, and the interface element information comprises a plurality of interaction elements; the scene generation module is used for generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, generating at least one test scene by utilizing the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relation with the interaction elements, and the trained operation model is obtained based on historical operation scene training of the vehicle and the machine; the case generation module is used for compiling each test scene to obtain a test case set corresponding to each test scene so as to test the vehicle-mounted application of the vehicle to be tested.
In an embodiment of the present application, there is also provided an electronic device including: one or more processors; and a storage means for storing one or more programs which, when executed by the one or more processors, cause the electronic device to implement the vehicle-mounted application testing method as described above.
In an embodiment of the present application, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to execute the in-vehicle application test method as described above.
The application has the beneficial effects that: the application provides a vehicle-mounted application testing method, a system, electronic equipment and a storage medium, wherein the vehicle-mounted application testing method automatically generates operation data and generates a testing scene according to interactive elements and operation models of different vehicle-mounted applications, compiles the testing scene to obtain a testing case set, further tests the vehicle-mounted application of a vehicle to be tested, can automatically generate the testing scene, automatically compiles the testing case set, replaces manual writing with automatic operation, improves the coverage rate of the testing scene and the quality of the testing case, improves the testing efficiency and the degree of automation, and reduces the labor cost.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:
FIG. 1 is a schematic illustration of an environment in which a vehicle-mounted application testing method is implemented, according to an exemplary embodiment of the present application;
FIG. 2 is a flow chart illustrating a method of testing an in-vehicle application in accordance with an exemplary embodiment of the present application;
FIG. 3 is a flow chart illustrating another vehicle application testing method according to an embodiment of the present application;
FIG. 4 is a block diagram of an in-vehicle application testing system shown in accordance with an exemplary embodiment of the present application;
FIG. 5 is a system architecture diagram of another vehicle application testing system, in accordance with an embodiment of the present application;
fig. 6 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
Detailed Description
Further advantages and effects of the present application will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
It should be noted that, in the present application, "first", "second", and the like are merely distinguishing between similar objects, and are not limited to the order or precedence of similar objects. The description of variations such as "comprising," "having," etc., means that the subject of the word is not exclusive, except for the examples shown by the word.
It should be understood that the various numbers and steps described in this disclosure are for convenience of description and are not to be construed as limiting the scope of the application. The magnitude of the present application reference numerals does not mean the order of execution, and the order of execution of the processes should be determined by their functions and inherent logic.
In the following description, numerous details are set forth in order to provide a more thorough explanation of embodiments of the present application, it will be apparent, however, to one skilled in the art that embodiments of the present application may be practiced without these specific details, in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the embodiments of the present application.
It should be noted that, in most conventional automatic testing methods, a test accompanying device is used instead of manual operation, judgment, and the like, for example: the automatic test method has the advantages that a mechanical arm is used for replacing a human to control a vehicle, a manual nozzle is used for replacing voice interaction between a human and the vehicle, a pickup is used for receiving and asserting, a high-definition camera is used for shooting a center screen image and asserting, a high-frame camera is used for capturing abnormity and test performance and the like, but the test execution period of the automatic test method is long, and when the version of the vehicle-mounted application iterates, the specific operation of the test also needs to be correspondingly adjusted, so that the version iterating test is slow.
To solve the above problems, embodiments of the present application respectively propose a vehicle-mounted application testing method, a vehicle-mounted application testing system, an electronic device, a computer-readable storage medium, and a computer program product, and these embodiments will be described in detail below.
Referring to fig. 1, fig. 1 is a schematic view of an implementation environment of a vehicle application testing method according to an exemplary embodiment of the application.
As shown in fig. 1, an implementation environment may include an acquisition device 101 and a computer device 102. The collection device may be at least one of a screenshot tool, a camera, a video camera, etc., and the computer device 102 may be one or more of a microcomputer, an embedded computer, a neural network computer, etc. The computer device 102 can be used for automatically generating operation data based on a plurality of interaction elements and generating a test scene, and automatically compiling a test case set so as to test the vehicle-mounted application of the vehicle to be tested. The collection device 101 is configured to collect UI (User Interface) images of different vehicle-mounted applications, provide the UI images to the computer device 102 for processing, and identify the UI images by the computer device 102 to obtain Interface element information of the different vehicle-mounted applications, so as to process the Interface element information.
The method includes the steps that a plurality of operation data are generated based on a plurality of interaction elements in interface element information and a trained operation model, at least one test scene is generated by utilizing the plurality of interaction elements and the plurality of operation data, the operation data have a corresponding relation with the interaction elements, the trained operation model is obtained based on historical operation scene training of a vehicle machine, each test scene is compiled to obtain a test case set corresponding to each test scene, and vehicle-mounted application testing is conducted on a vehicle to be tested. Therefore, the technical scheme of the embodiment of the application can realize automatic generation of the test scene and automatic compiling of the test case set, replaces manual writing with automatic operation, improves the test efficiency and the automation degree, and reduces the labor cost.
It should be noted that, the vehicle-mounted application testing method provided in the embodiment of the present application is generally executed by the computer device 102, and accordingly, the vehicle-mounted application testing system is generally disposed in the computer device 102.
Referring to fig. 2, fig. 2 is a flowchart illustrating a vehicle-mounted application testing method according to an exemplary embodiment of the application. The method may be applied to the implementation environment shown in fig. 1 and executed in particular by the computer device 102 in the implementation environment. It should be understood that the method may be applied to other exemplary implementation environments and be specifically executed by devices in other implementation environments, and the implementation environments to which the method is applied are not limited by the present embodiment.
As shown in fig. 2, in an exemplary embodiment, the vehicle application testing method at least includes steps S210 to S230, which are described in detail below:
step S210, interface element information of different vehicle-mounted applications is obtained.
In one embodiment of the application, the vehicle-mounted application comprises a system application of a vehicle-mounted system and a third party application developed by a third party platform, and interface element information of each vehicle-mounted application can be captured through the combination of the acquisition equipment and the artificial intelligence software, wherein the interface element information comprises a plurality of interaction elements, and element attributes and element levels of each interaction element. The interactive element refers to an element with an operation attribute, feedback such as a button, a sliding bar, a text editing box and the like is provided after clicking, the element attribute can be identified by artificial intelligence software, and the element level is determined based on the level of a user interface where the interactive element is located.
In one embodiment of the present application, step S210 includes: acquiring user interface images of each level of different vehicle-mounted applications; identifying the user interface image of each level to obtain a plurality of interface elements and element attributes of each interface element; screening a plurality of interactive elements from all interface elements according to element attributes, and determining an element level corresponding to each interactive element according to the level of the user interface image where each interactive element is located; and determining a plurality of interaction elements and element attributes and element levels corresponding to each interaction element as interface element information.
In this embodiment, the user interface image of each level of each in-vehicle application may be acquired by an acquisition device, for example: the UI interface of the vehicle-mounted application can be subjected to screenshot through a screenshot tool, or the UI interface of the vehicle-mounted application can be subjected to shooting through a camera or a video camera and the like, so that the user interface image can be obtained. Then, by artificial intelligence software, for example: gu Geyun visual API (Application Programming Interface ), microsoft computer visual API, amazon Rekognition (amazon image recognition system), hundred degree AI (Artificial Intelligence ) open platform, tencel AI open platform, etc., image recognition, ORC (Optical Character Recognition ) text recognition, capturing UI elements (interface elements, abbreviated as elements) of various levels of UI interface for vehicle applications in a vehicle system, including: buttons, sliders, text edit boxes, still pictures, album art, car control icons, status bars, etc., and identify element attributes of the elements. Extracting an element with operability according to element attributes, while an element without operability refers to an element without feedback after clicking, for example, a still picture, and may be referred to as a display class element. And taking the element with operability as an interactive element, naming the interactive element according to the hierarchy of the user interface image where the interactive element is positioned, and storing the interactive element into a database, if the interactive element is named to meet the element with the same shape, naming the interactive element by using the name of the element, and adding Arabic numerals for subscripts to the naming according to the sequence from top to bottom and from left to right. The name is part of the attribute that the element carries.
Step S220, generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, and generating at least one test scene by using the plurality of interaction elements and the plurality of operation data.
In one embodiment of the application, the extracted interactive elements are input into a pre-trained operation model so that the operation model outputs operation data, thereby obtaining operation data corresponding to different interactive elements, and one or more test scenes are generated by using the different interactive elements and the operation data corresponding to each interactive element to establish a scene database. The operation data and the interaction elements have a corresponding relation, the trained operation model is obtained based on the vehicle history operation scene, the operation model can be a neural network model or other deep learning models, the vehicle history operation scene is not limited here, the vehicle history operation scene can be an intelligent cabin historic vehicle operation scene of a user or an intelligent cabin history test operation scene of a tester, and the vehicle history operation scene is not limited here.
In one embodiment of the present application, before generating a plurality of operation data based on a plurality of interaction elements and a trained operation model, the in-vehicle application test method includes: acquiring a historical operation scene of the vehicle; determining a plurality of interactive element samples according to a history operation scene of the vehicle and writing an operation process sample and an operation result sample corresponding to each interactive element sample to generate a training sample set; and training the operation model through the training sample set to obtain a trained operation model.
In this embodiment, the historical real vehicle operation scene data of the intelligent cabin can be obtained as a plurality of vehicle history operation scenes, common elements with operation attributes of the intelligent cabin are extracted from the plurality of vehicle history operation scenes to be used as interactive element samples, common steps of writing the intelligent cabin according to the interactive element samples are used as operation process samples, expected values after the steps are executed are written to be used as operation result samples, and therefore the operation process samples and the operation result samples corresponding to the plurality of interactive element samples and each interactive element sample are used as training sample sets. Among the usual steps include, but are not limited to: clicking buttons, clicking pictures, sliding buoys, inputting texts, searching, opening applications, closing, pulling down menus and the like, wherein expected values executed by each step are unique and can be pictures, texts, position changes and the like; the interactive element samples and the corresponding operation process samples and operation result samples are stored in a one-to-one correspondence mode. The neural network model can be established as an initial operation model, the interactive element sample in the training sample set is used as the input of the operation model, and the operation process sample and the operation result sample corresponding to the interactive element sample in the training sample set are used as the output of the operation model, so that the operation model is trained, and the trained operation model is obtained and stored in the database.
In one embodiment of the application, generating a plurality of operational data based on a plurality of interactive elements and a trained operational model includes: establishing a classification model based on different element attributes, so that the classification model classifies a plurality of interaction elements to obtain different interaction element classes, wherein each interaction element class comprises a plurality of interaction elements with the same element attributes, and each interaction element has a corresponding element attribute; and sequentially inputting the interactive elements in all the interactive element classes into the trained operation model to obtain a plurality of operation data.
In this embodiment, the classification model is modeled based on element attributes carried by the interactive element, where the element attributes include, but are not limited to, parameters such as type (element type), name (element name), position (element position), size (element size), event (element event), etc., and event includes click, long press, etc. The classification model may be trained by using a plurality of interactive element samples, the classification model is evaluated according to the operation model, the classified interactive element samples are input into the operation model, the classification model is evaluated based on operation data corresponding to the same type of interactive element samples, and the evaluation index may be at least one of accuracy, error rate, sensitivity, specificity, precision, recall rate, and the like, for example: when the accuracy in the evaluation index of the classification model reaches the preset accuracy, the classification model can be applied, wherein the accuracy refers to the proportion of the number of all predicted correct predictions to the total number, and the calculation mode is as follows:
Accuracy= (TP+TN)/(TP+FP+TN+FN) formula (1),
here, accuracy is an Accuracy rate, TP (True positive) is the number of correctly divided positive examples, TN (True negative) is the number of correctly divided negative examples, FP (False positive) is the number of incorrectly divided positive examples, and FN (False negative) is the number of incorrectly divided negative examples. Illustratively, the preset accuracy may be 95%, or other values, without limitation.
Taking a cool dog music playing interface as an example, the operation class elements that can be captured by the page include last song, next song, play/pause, song list, lyric switch, circulation mode, etc., and the display class elements that can be captured include singer name, song name, album picture, etc. An operation data may be recorded, for example: clicking the next song icon button changes the song name, artist name, cover picture, lyrics, etc. Searching the database for all interactive element classes at a level above the next song icon button, for example: cool dogs, fun, bluetooth music, local music, himalaya, sergey, etc., find interactive elements with name attribute of next song, automatically generate operation process and corresponding operation result, and store in classification.
In one embodiment of the application, generating at least one test scenario using a plurality of interactive elements and a plurality of operational data comprises: determining a plurality of target interaction elements from the plurality of interaction elements according to each preset scene generation condition, and determining operation data corresponding to each target interaction element as target operation data; and combining the target operation data corresponding to each target interaction element according to the element level to generate each test scene, wherein the interaction elements also have corresponding element levels.
In this embodiment, the preset scene generating condition may be HOME page scene, application list page scene, APP page scene, sub page scene, or the like, or other one-dimensional or multidimensional page scene, which is not limited herein. The target interaction element and the corresponding target operation data can be selected according to the preset scene generation condition, and the target operation data corresponding to the target interaction element is combined according to the element level to obtain a one-dimensional or multi-dimensional test scene. The one-dimensional test scene comprises a multimedia scene, a navigation scene, a setting scene and the like, and the generated one-dimensional test scene has uniqueness; the two-dimensional test scene comprises application switching, entertainment navigation interaction and the like, and is formed by combining one-dimensional test scenes; the multidimensional test scenario may define an upper dimension limit for the generated test scenario, e.g. setting up five dimensions at most, e.g. setting up connection bluetooth-play bluetooth music-browse consultation-background navigation, etc.
In another embodiment of the present application, generating at least one test scenario using a plurality of interactive elements and a plurality of operational data, comprises: inputting the interaction elements and the operation data into a preset scene generation model, so that the preset scene generation model determines the target interaction elements and the target operation data corresponding to the target interaction elements according to each preset scene generation condition, each test scene is generated, and the preset scene generation model is obtained based on historical operation scene training of the vehicle.
In this embodiment, a scene generating model may be pre-established as a preset scene generating model, and the intelligent cabin calendar smith vehicle operation scene of the user is collected as a vehicle history operation scene, and the preset scene generating model learns the vehicle history operation scene, so that a plurality of target interaction elements and corresponding target operation data can be automatically determined according to preset scene generating conditions, multi-dimensional combination is automatically performed, a plurality of test scenes are generated, the test scenes are automatically generated through the preset scene generating model after machine learning, the efficiency of scene generation can be improved, and the time cost is saved.
In addition, the real business scene data (history operation scene of the vehicle machine) of the user can also be used as an input mode of the operation process, namely, the operation data obtained by the big data embedded point can be directly converted into a test scene, which is the real behavior of the user and does not need to be evaluated.
And step S230, compiling according to the test scene to obtain a test case set so as to test the vehicle-mounted application of the vehicle to be tested.
In one embodiment of the application, a scene database can be imported into LLM (Large Language Model ) large language model software, a plurality of test scripts and corresponding assertions are automatically generated by utilizing the LLM large language model software according to the test scenes in the scene database, the test cases are automatically generated according to each test script and assertions, and a plurality of test cases are obtained to form a test case set and are stored in the database. When a test requirement exists, a task is created, a test case set is automatically called according to the task, and a test instruction is automatically issued to the vehicle to be tested according to the called test case set so as to test the vehicle to be tested. The number of the machine to be tested may be one or more, and is not limited herein.
In one embodiment of the present application, compiling each test scenario to obtain a test case set corresponding to each test scenario includes: performing language identification on the test scene, compiling a plurality of test scripts and assertions corresponding to each test script according to the identification result, wherein the test scripts are obtained based on the operation process in the target operation data, and the assertions are obtained based on the operation result in the target operation data; generating test cases based on the test scripts and assertions corresponding to the test scripts to obtain a plurality of test cases; and configuring a hierarchical relationship for each test case according to the element hierarchy to obtain a test case set, wherein the test case has a corresponding relationship with the target interaction element.
In this embodiment, the scene database may be imported into a LLM large language model software platform, and the test scenes in the scene database may be automatically compiled into a plurality of test cases and configured in a hierarchical relationship through natural language recognition to form a test case set. The LLM large language model software platform may be at least one of GTP-4 (a language model), BERT (a pre-trained language characterization model), CHAT-GTP (a natural language processing tool), a dialect-core (a large language model), and the like. After a plurality of test cases are obtained, the corresponding test cases are automatically classified and sorted according to element levels, and the hierarchical relation of each test case is configured to obtain a test case set. One test scene corresponds to one test case set, so that a plurality of test case sets are obtained, each test case set is stored in a modularized mode according to the hierarchy classification of the corresponding test scene, and is stored in a database, namely, one test case set is stored in one case module, each case module configures different hierarchies according to the dimension of the corresponding test scene of the stored test case set, and the test case set is conveniently called according to the hierarchy. Each lowest-level use case module can be independently called, and the operation of the previous level can be automatically associated after the calling, and each use case module has the element attribute of the previous level.
In one embodiment of the present application, after compiling each test scenario to obtain a test case set corresponding to each test scenario, the vehicle-mounted application testing method includes: acquiring test requirement information, generating a target task according to the test requirement information, and determining the test requirement information based on the updated function or version of the vehicle-mounted application; determining a target test case set corresponding to the target task according to a preset task-test case set association condition, wherein the target test case set comprises a plurality of target test cases; and generating a test instruction based on the target test case and sending the test instruction to the to-be-tested vehicle to perform vehicle-mounted application test.
In this embodiment, an association rule between a task and a test case set may be preset as a preset task-test case set association condition. When the vehicle-mounted application develops a new function or a new version, a developer can input test requirement information according to the updated function or version, after receiving the test requirement information, the computer equipment creates a target task according to the test requirement information, and automatically imports a target test case set required by the target task according to a preset task-test case set association condition. And generating a test instruction according to the test cases in the target test case set, and transmitting the test instruction to the to-be-tested vehicle machine so that the to-be-tested vehicle machine executes corresponding actions according to the test instruction to complete vehicle-mounted application test. The machine to be tested can be one or more machines for respectively executing parallel test instructions or serial test instructions. Illustratively, the computer device may be an automated test software platform, which may act as a client or cloud, without limitation.
In one embodiment of the present application, after performing the vehicle-mounted application test, the vehicle-mounted application test method includes: receiving a test result corresponding to each target test case returned by the vehicle to be tested; and generating a test report based on the target task, the identification information of the vehicle to be tested and the test result corresponding to each target test case.
In this embodiment, the identification information of the machine to be tested may be a machine name, a machine number, or other identification information of the machine to be tested. After the execution of the test instruction is completed, the to-be-tested vehicle machine feeds back the test result corresponding to the test instruction, namely the test result and the target test case have a corresponding relation. The method can determine the projects of the vehicle type or the vehicle system according to the test requirement information, aggregate reports according to rules such as the vehicle name, the target task, the projects and the like, automatically generate a test report corresponding to the test result, and the format of the test report is not limited, and can be a web report, an excel report or a world report and the like.
In one embodiment of the present application, after generating a test report based on a target task, identification information of a vehicle to be tested, and a test result corresponding to each target test case, the vehicle-mounted application test method includes: acquiring a plurality of test reports; counting the test results corresponding to different target test cases based on a plurality of test reports to obtain a passing ratio of the test results corresponding to each target test case to pass; if the passing ratio is greater than or equal to a preset threshold, the priority of the target test cases corresponding to the passing ratio is reduced, and each test case is configured with the priority; if the passing ratio is smaller than the preset threshold, the priority of the target test case corresponding to the passing ratio is improved.
In this embodiment, the same priority may be configured for each test case after the test case is generated. The period may be preset, all test reports within the period are acquired every one period, or the reference number may be preset, and all test reports are acquired when the number of test reports reaches the reference number. Taking the target test case A as an example, counting test results corresponding to the target test case A in each test report, obtaining the passing number of the test results corresponding to the target test case A and the total number of the test results corresponding to the target test case A, and calculating the ratio of the passing number to the total number as the passing ratio. Comparing the passing ratio with a preset threshold, if the passing ratio is larger than or equal to the preset threshold, the function of the interaction element corresponding to the target test case A is not easy to leak, and the testing workload can be simplified and the testing efficiency can be further improved by reducing the priority of the target test case A. If the ratio is smaller than the preset threshold value, the function of the interaction element corresponding to the target test case A is easy to leak, and the abnormal problem of the vehicle-mounted application can be timely and effectively detected by improving the priority of the target test case A, so that a basis is provided for subsequent improvement.
Referring to fig. 3, fig. 3 is a flowchart illustrating another vehicle application testing method according to an embodiment of the application. As shown in fig. 3, the flow of the vehicle-mounted application test includes:
1. capturing interactive elements of each level of vehicle-mounted application in a vehicle-mounted system and storing the interactive elements in a database;
2. training an operation model according to the operation process and the operation result of the vehicle and storing the operation model into a database;
3. generating a test scene by using the acquired interactive elements and the trained operation model, obtaining a scene database, and storing the scene database into the database;
4. automatically generating a test script and assertion according to a test scene in a scene database;
5. generating test cases according to the test scripts and the assertions to obtain a plurality of test cases, forming a test case set based on the plurality of test cases, and storing the test case set in a database;
6. creating a target task, automatically calling a test case set according to the target task to automatically issue a test instruction for execution, and generating a test report according to a returned test result.
The detailed calculation process in the flow chart of fig. 3 is referred to the descriptions in the foregoing embodiments, and will not be repeated here.
Referring to fig. 4, fig. 4 is a block diagram illustrating an in-vehicle application testing system according to an exemplary embodiment of the present application. The system may be applied to the implementation environment shown in fig. 4 and is specifically configured in the computer device 102. The system may be adapted to other exemplary implementation environments and may be specifically configured in other devices, and the present embodiment is not limited to the implementation environments to which the system is adapted.
As shown in fig. 4, the exemplary in-vehicle application test system includes:
the acquiring module 410 is configured to acquire interface element information of different vehicle-mounted applications, wherein the interface element information comprises a plurality of interaction elements; the scene generating module 420 is configured to generate a plurality of operation data based on the plurality of interaction elements and the trained operation model, generate a test scene by using the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relationship with the interaction elements, and the trained operation model is obtained based on the historical operation scene training of the vehicle and the machine; the case generation module 430 is configured to compile the test scenario to obtain a test case set, so as to test the vehicle-mounted application of the vehicle to be tested.
Referring to fig. 5, fig. 5 is a schematic diagram of a system architecture of another vehicle-mounted application testing system according to an embodiment of the present application, and as shown in fig. 5, the vehicle-mounted application testing system includes a scenario automation generating platform, an LLM large language model, automation testing software and a vehicle to be tested. The system has the following functions:
1. the scene automation generation platform is used for generating a test scene to obtain a scene database.
The scene automation generation platform automatically grabs interactive elements of all levels of a UI interface in the vehicle machine through AI (Artificial Intelligence ), each interactive element carries element attributes, and stores the elements according to the levels, wherein the stored data are used as real scene data; operating data such as clicking buttons, clicking pictures, sliding buoys, inputting texts, searching, opening applications and the like which are commonly used in the intelligent cabin are written, and an operating model is trained by utilizing the operating data; the trained operation model is deployed in a big data model (a preset scene generation model), the big data model applies interactive elements in the operation model and the real scene data, a test scene is automatically built through training, and a database is stored, so that a scene database is obtained.
2. The LLM large language model is used for generating test scripts and assertions according to test scenes, generating test cases according to the test scripts and assertions, and configuring hierarchical relations for each test case to obtain a test case set.
Connecting the scene database to a LLM large language model such as: GTP-4, BERT and the like are automatically compiled into a plurality of test cases according to natural language input of a scene database, test case sets are obtained, and the test case sets are stored in the database according to a hierarchy.
3. The automatic test software is used for test management and comprises the steps of creating a target task, exporting a target test case set corresponding to the target task and issuing a test instruction.
The automatic test software can be configured in the upper computer, the upper computer is connected with the vehicle machine through a USB (Universal Serial Bus ) cable, the vehicle machine opens USB for debugging, the automatic test software imports test cases from the database according to the need, generates test instructions and issues the test instructions to the vehicle machine to be tested to execute the test instructions, and after the test instructions are completed, an aggregate test report (test report) is generated according to the test results returned by the vehicle machine to be tested.
4. The vehicle to be tested is used for executing the test instruction and returning the test result.
The embodiment is based on a big data model and an operation model, and can automatically generate scene databases compatible with different vehicle types by combining with the UI element database, and finally generates the test case database through the LLM large language model software platform, thereby improving the quality of the test case, improving the scene coverage rate of the test case, improving the test efficiency and facilitating the acquisition of a reliable intelligent cabin system.
It should be noted that, the vehicle-mounted application testing system provided by the above embodiment and the vehicle-mounted application testing method provided by the above embodiment belong to the same concept, and the specific manner in which each module and unit perform the operation has been described in detail in the method embodiment, which is not repeated here. In practical application, the vehicle-mounted application test system provided in the above embodiment may distribute the functions to be completed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above, which is not limited herein.
The embodiment of the application also provides electronic equipment, which comprises: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic equipment realizes the vehicle-mounted application testing method provided in each embodiment.
Referring to fig. 6, fig. 6 is a schematic diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present application. It should be noted that, the computer system 600 of the electronic device shown in fig. 6 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a central processing unit (Central Processing Unit, CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 602 or a program loaded from a storage section 608 into a random access Memory (Random Access Memory, RAM) 603, for example, performing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and a speaker, etc.; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. When executed by a Central Processing Unit (CPU) 601, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
Another aspect of the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the vehicle-mounted application testing method as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions so that the computer device executes the vehicle-mounted application testing method provided in the above-described respective embodiments.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. It is therefore intended that all equivalent modifications and changes made by those skilled in the art without departing from the spirit and technical spirit of the present application shall be covered by the appended claims.
Claims (12)
1. The vehicle-mounted application testing method is characterized by comprising the following steps of:
acquiring interface element information of different vehicle-mounted applications, wherein the interface element information comprises a plurality of interaction elements;
generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, generating at least one test scene by utilizing the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relation with the interaction elements, and the trained operation model is obtained based on historical operation scene training of the vehicle and the machine;
compiling each test scene to obtain a test case set corresponding to each test scene so as to test the vehicle-mounted application of the vehicle to be tested.
2. The vehicle-mounted application testing method of claim 1, wherein generating a plurality of operational data based on the plurality of interactive elements and the trained operational model comprises:
establishing a classification model based on different element attributes, so that the classification model classifies the plurality of interaction elements to obtain different interaction element classes, wherein each interaction element class comprises a plurality of interaction elements with the same element attributes, and the interaction elements have corresponding element attributes;
And sequentially inputting the interactive elements in all the interactive element classes into the trained operation model to obtain the plurality of operation data.
3. The vehicle-mounted application testing method of claim 2, wherein generating at least one test scenario using the plurality of interactive elements and the plurality of operational data comprises:
determining a plurality of target interaction elements from the plurality of interaction elements according to each preset scene generation condition, and determining operation data corresponding to each target interaction element as target operation data; combining target operation data corresponding to each target interaction element according to an element level to generate each test scene, wherein the interaction elements also have corresponding element levels;
or alternatively, the first and second heat exchangers may be,
inputting the interaction elements and the operation data into a preset scene generation model, so that the preset scene generation model determines target interaction elements and target operation data corresponding to the target interaction elements according to each preset scene generation condition, each test scene is generated, and the preset scene generation model is obtained based on historical operation scene training of the vehicle.
4. The vehicle-mounted application testing method according to claim 3, wherein compiling each test scenario to obtain a test case set corresponding to each test scenario comprises:
Performing language identification on the test scene, compiling a plurality of test scripts and assertions corresponding to each test script according to identification results, wherein the test scripts are obtained based on operation processes in the target operation data, and the assertions are obtained based on operation results in the target operation data;
generating test cases based on the test scripts and assertions corresponding to the test scripts to obtain a plurality of test cases;
and configuring a hierarchical relationship for each test case according to the element hierarchy to obtain the test case set, wherein the test cases have a corresponding relationship with the target interaction elements.
5. The method for testing the vehicle-mounted application according to claim 4, wherein after compiling each test scenario to obtain the test case set corresponding to each test scenario, the method for testing the vehicle-mounted application comprises:
acquiring test requirement information, generating a target task according to the test requirement information, wherein the test requirement information is determined based on an updated function or version of the vehicle-mounted application;
determining a target test case set corresponding to the target task according to a preset task-test case set association condition, wherein the target test case set comprises a plurality of target test cases;
And generating a test instruction based on the target test case and sending the test instruction to the to-be-tested vehicle to perform vehicle-mounted application test.
6. The vehicle-mounted application testing method according to claim 5, wherein after the vehicle-mounted application testing is performed, the vehicle-mounted application testing method comprises:
receiving a test result corresponding to each target test case returned by the vehicle to be tested;
and generating a test report based on the target task, the identification information of the to-be-tested vehicle and the test result corresponding to each target test case.
7. The vehicle-mounted application testing method according to claim 6, wherein after generating a test report based on the target task, the identification information of the vehicle to be tested, and the test result corresponding to each target test case, the vehicle-mounted application testing method comprises:
acquiring a plurality of test reports;
counting the test results corresponding to different target test cases based on the plurality of test reports to obtain a passing ratio of the test results corresponding to each target test case;
if the passing ratio is greater than or equal to a preset threshold, the priority of the target test case corresponding to the passing ratio is reduced, and each test case is configured with priority;
And if the passing ratio is smaller than the preset threshold, the priority of the target test case corresponding to the passing ratio is improved.
8. The method for testing an in-vehicle application according to any one of claims 1 to 7, wherein obtaining interface element information of different in-vehicle applications includes:
acquiring user interface images of each level of different vehicle-mounted applications;
identifying the user interface image of each level to obtain a plurality of interface elements and element attributes of each interface element;
screening out the plurality of interactive elements from all interface elements according to the element attributes, and determining an element level corresponding to each interactive element according to the level of the user interface image where each interactive element is located;
and determining the plurality of interaction elements and the element attribute and the element level corresponding to each interaction element as the interface element information.
9. The in-vehicle application testing method according to any one of claims 1 to 7, characterized in that before generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, the in-vehicle application testing method comprises:
acquiring the history operation scene of the vehicle machine;
determining a plurality of interactive element samples according to the history operation scene of the vehicle and machine, and compiling an operation process sample and an operation result sample corresponding to each interactive element sample to generate a training sample set;
And training the operation model through the training sample set to obtain the trained operation model.
10. An in-vehicle application testing system, comprising:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring interface element information of different vehicle-mounted applications, and the interface element information comprises a plurality of interaction elements;
the scene generation module is used for generating a plurality of operation data based on the plurality of interaction elements and the trained operation model, generating at least one test scene by utilizing the plurality of interaction elements and the plurality of operation data, wherein the operation data has a corresponding relation with the interaction elements, and the trained operation model is obtained based on historical operation scene training of the vehicle and the machine;
the case generation module is used for compiling each test scene to obtain a test case set corresponding to each test scene so as to test the vehicle-mounted application of the vehicle to be tested.
11. An electronic device, the electronic device comprising:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the electronic device to implement the in-vehicle application testing method of any of claims 1-9.
12. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the vehicle-mounted application testing method of any of claims 1-9.
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