Interface anomaly detection method and device, electronic equipment, storage medium and chip

Abstract

The present disclosure relates to an interface exception detection method and device, electronic equipment, storage medium and chip, and relates to the field of device detection. The method comprises: acquiring a plurality of user interfaces displayed by a target application on a plurality of terminal devices, and acquiring vertex coordinate information of each object in each user interface; comparing the vertex coordinate information of each object in each user interface to determine whether each user interface is displayed abnormally. Through the above technical solution, when the vertex coordinate information of each object in each user interface is compared, the terminal device with more differences in the vertex coordinate information of each object in the user interface of other terminal devices may have a user interface display exception, which can improve the accuracy of detecting user interface exceptions to a certain extent.

Description

Technical Field

[0001] This disclosure relates to the field of equipment testing, specifically to a method, apparatus, electronic device, storage medium, and chip for detecting interface anomalies. Background Technology

[0002] With the continuous development of terminal devices, a wide variety of devices are emerging in the market. Due to differences in brand, model, system version, and screen design, applications may exhibit interface anomalies on different devices. Therefore, application developers conduct compatibility testing during development. Compatibility testing refers to testing whether the application can be installed and launched successfully, and whether the user interface (UI) displays correctly, on terminal devices (such as mobile phones, tablets, or other devices) of different manufacturers, models, system versions, and screens. However, current technologies typically only detect severe anomalies such as black screens, white screens, or distorted screens. Detecting other types of anomalies requires maintaining a large number of benchmark images, resulting in high maintenance costs. Therefore, improving the applicability of user interface anomaly detection without increasing costs is a pressing issue that needs to be addressed. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides an interface anomaly detection method, apparatus, electronic device, storage medium, and chip.

[0004] According to a first aspect of the present disclosure, a method for detecting interface anomalies is provided, applied to an electronic device, the method comprising:

[0005] Obtain multiple user interfaces displayed by the target application on multiple terminal devices;

[0006] Obtain the vertex coordinate information of each object in each of the multiple user interfaces;

[0007] The objects are compared based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly.

[0008] Optionally, obtaining the vertex coordinate information of each object in each of the plurality of user interfaces includes:

[0009] Based on the feature information of each user interface, obtain the vertex coordinate information of each object in each user interface; wherein, the feature information includes the code of the user interface and / or a screenshot of the user interface.

[0010] Optionally, the step of comparing objects based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly includes:

[0011] Based on the first vertex coordinate information of each object in the user interface, and / or the second vertex coordinate information of each object in the user interface, the objects are compared to determine whether each user interface displays an abnormality;

[0012] The first vertex coordinate information is determined based on the code of the user interface, and the second vertex coordinate information is determined based on the screenshot of the user interface.

[0013] Optionally, the feature information is the code of the user interface, and the step of obtaining the vertex coordinate information of each object in each user interface based on the feature information of each user interface includes:

[0014] Obtain the code for each user interface;

[0015] The code retrieves the first vertex coordinates of each object in each user interface.

[0016] Optionally, the feature information is a screenshot of the user interface, and the step of obtaining the vertex coordinate information of each object in each user interface based on the feature information of each user interface includes:

[0017] Obtain a screenshot of each user interface;

[0018] The screenshots are identified using an edge detection algorithm to obtain the second vertex coordinates of each object in each user interface.

[0019] Optionally, the step of comparing objects based on the first vertex coordinate information and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly includes:

[0020] Based on the first vertex coordinate information of each object in each user interface, the coordinate range of each object in each user interface is compared to determine whether each user interface is abnormal.

[0021] Optionally, the step of comparing objects based on the first vertex coordinate information and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly includes:

[0022] Based on the second vertex coordinate information of each object in each user interface, the degree of matching between each object in each user interface and each object in other interfaces is obtained, so as to determine whether each user interface is abnormal based on the degree of matching.

[0023] Optionally, the step of comparing objects based on the first vertex coordinate information and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly includes:

[0024] Based on the first vertex coordinate information of each object in each user interface, the coordinate range of each object in each user interface is compared to determine whether each user interface displays an anomaly, and the first identification result of each user interface is obtained;

[0025] Based on the second vertex coordinate information of each object in each user interface, the matching degree of each object in each user interface with each object in other interfaces is obtained, so as to determine whether each user interface displays an anomaly based on the matching degree, and obtain the second identification result of each user interface;

[0026] Based on the first identification result and the second identification result of each user interface, it is determined whether each user interface displays an anomaly.

[0027] Optionally, the step of comparing the coordinate ranges of each object in each user interface based on the first vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly includes:

[0028] Based on the first vertex coordinate information of each object in each user interface, obtain the coordinate range of each object in each user interface;

[0029] The coordinate ranges of each object in each user interface are compared to determine whether there are any abnormal objects with intersecting coordinate ranges in each user interface. Intersecting coordinate ranges refer to the coordinates of one or more vertices of one object being within the coordinate range of another object.

[0030] In the case of an abnormal object with intersecting coordinate ranges in the first user interface, it is determined whether the same object in other user interfaces also has intersecting coordinate ranges, so as to obtain a first number of user interfaces with intersecting coordinate ranges; the first user interface is any one of the plurality of user interfaces, and the same object is an object in the other user interfaces with the same coordinate information as the abnormal object;

[0031] If the first quantity is greater than or equal to the set quantity, it is determined that the first user interface is displayed normally;

[0032] If the first quantity is less than the set quantity, it is determined that the first user interface display is abnormal.

[0033] Optionally, the step of obtaining the matching degree of each object in each user interface with each object in other interfaces based on the second vertex coordinate information of each object in each user interface, and determining whether each user interface displays an anomaly based on the matching degree, includes:

[0034] The number of objects in each user interface is determined based on the second vertex coordinate information of each object in each user interface;

[0035] Based on the number of objects in each user interface, a reference value for the number of objects is obtained, and the reference value is determined based on the average number of objects in the multiple user interfaces;

[0036] The number of objects in each user interface is compared with the reference value;

[0037] If the number of objects in the second user interface is less than the reference value, it is determined that the second user interface is displaying abnormally; the second user interface is any one of the plurality of user interfaces;

[0038] If the number of objects in the second user interface is greater than or equal to the reference value, obtain the image vector of each object in the second user interface, and determine whether the second user interface is displaying abnormally based on the image vector.

[0039] Optionally, obtaining the image vectors of each object in the second user interface, and determining whether the second user interface displays abnormally based on the image vectors, includes:

[0040] Vectorize the object images in each of the second user interfaces to obtain the image vectors of each object in each of the second user interfaces;

[0041] Based on the image vectors of each object in each of the second user interfaces, determine whether the image vectors with the same image number in each of the second user interfaces match each other;

[0042] If the first image vectors in each of the second user interfaces match, it is determined that the first image vectors in each of the second user interfaces are normal; the first image vectors are image vectors with the same image number in each of the second user interfaces.

[0043] If there is a mismatch between the first image vectors in each of the second user interfaces, obtain the matching rate of the first image vectors in each of the second user interfaces;

[0044] If the matching rate is greater than or equal to a set threshold, the second user boundaries in which the first image vectors do not match are determined to be display abnormal.

[0045] If the matching rate is less than the set threshold, the first image vector in each of the second user interfaces will be displayed normally;

[0046] If the image vectors of all objects in any second user area are displayed correctly, then the second user area is determined to be displayed correctly.

[0047] Optionally, determining whether each user interface displays an anomaly based on the first identification result and the second identification result of each user interface includes:

[0048] For any user interface, if both the first identification result and the second identification result of the user interface indicate that the user interface is displaying abnormally, then the user interface is determined to be displaying abnormally.

[0049] If both the first and second identification results of the user interface indicate that the user interface is displayed normally, then the user interface is determined to be displayed normally.

[0050] If one of the first identification result and the second identification result of the user interface indicates that the user interface is displayed normally, and the other indicates that the user interface is displayed abnormally, then the user interface is determined to be displayed abnormally.

[0051] According to a second aspect of the present disclosure, an interface anomaly detection device is provided, applied to an electronic device, the device comprising:

[0052] The interface acquisition module is used to acquire multiple user interfaces displayed by the target application on multiple terminal devices;

[0053] The information acquisition module is used to acquire the vertex coordinate information of each object in each of the multiple user interfaces;

[0054] The anomaly determination module is used to compare objects based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly.

[0055] According to a third aspect of the present disclosure, a screen anomaly detection device is provided, applied to an electronic device, comprising: a processor; and a memory for storing processor-executable instructions;

[0056] The processor is configured to: execute the executable instructions to implement the screen anomaly detection method according to any embodiment of the first aspect above.

[0057] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, having stored thereon computer program instructions that, when executed by a processor, implement the steps of the screen anomaly detection method described in the first aspect of the present disclosure.

[0058] According to a fifth aspect of the present disclosure, a chip is provided, including a processor and an interface; the processor is configured to read instructions to execute the steps of the screen anomaly detection method described in the first aspect of the present disclosure.

[0059] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:

[0060] In the above technical solution, multiple user interfaces displayed by the target application on multiple terminal devices are acquired, and the vertex coordinate information of each object in each user interface is obtained. The objects are compared based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly. By comparing the vertex coordinate information of each object in each user interface, this technical solution can determine whether the user interface displays anomalies by identifying differences between objects in the user interface. It eliminates the need to maintain a large number of reference images and is applicable to detecting various anomalies in the user interface, thus improving the accuracy of user interface anomaly detection to a certain extent.

[0061] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0062] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0063] Figure 1 This is a flowchart illustrating an interface anomaly detection method according to an exemplary embodiment.

[0064] Figure 2 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0065] Figure 3 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0066] Figure 4This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0067] Figure 5 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0068] Figure 6 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0069] Figure 7 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment.

[0070] Figure 8 This is a flowchart illustrating yet another interface anomaly detection method according to an exemplary embodiment.

[0071] Figure 9 This is a block diagram illustrating an interface anomaly detection device according to an exemplary embodiment.

[0072] Figure 10 This is a block diagram illustrating an electronic device for an interface anomaly detection method according to an exemplary embodiment.

[0073] Figure 11 This is a block diagram of an electronic device for an interface anomaly detection method, according to an exemplary embodiment. Detailed Implementation

[0074] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0075] It is understood that in this disclosure, "multiple" refers to two or more, and other quantifiers are similar. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. The singular forms "a," "the," and "the" are also intended to include the plural forms unless the context clearly indicates otherwise.

[0076] It is further understood that the terms "first," "second," etc., are used to describe various types of information, but this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another, and do not indicate a specific order or degree of importance. In fact, the expressions "first," "second," etc., are completely interchangeable. For example, without departing from the scope of this disclosure, a first identification result can also be referred to as a second identification result, and similarly, a second identification result can also be referred to as a first identification result.

[0077] It is understood that although operations are described in a specific order in the accompanying drawings in the embodiments of this disclosure, this should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all of the shown operations to be performed to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0078] It should be noted that all actions involving the acquisition of signals, information, or data in this application are carried out in compliance with the relevant data protection laws and policies of the country where the application is located, and with the authorization granted by the owner of the relevant device.

[0079] Currently, the market offers a wide variety of terminal devices, with multiple models even within the same brand, and various system versions available for the same model. Different system versions may also result in interface changes, permission adjustments, and other variations. Furthermore, different terminal devices may have different screen sizes and resolutions. In addition, screen designs have evolved to meet user needs, with various screen types such as curved screens, notch screens, and punch-hole screens. Therefore, with the continuous development of various terminal devices, the problem of abnormal user interface display in applications has also arisen. Due to the differences between different mobile terminals, some applications may exhibit interface abnormalities such as black screens, white screens, and overlapping controls on certain mobile devices. Therefore, this solution proposes an interface abnormality detection method to address this technical problem.

[0080] Figure 1 This is a flowchart illustrating an interface anomaly detection method according to an exemplary embodiment, such as... Figure 1 As shown, this method is used in a terminal device and includes the following steps.

[0081] In step S101, multiple user interfaces displayed by the target application on multiple terminal devices are obtained.

[0082] For example, the target application is any application to be tested for compatibility. This target application can be installed on multiple different terminal devices, and each terminal device with the target application installed will access the application's user interface (UI), resulting in multiple user interfaces. Each user interface corresponds one-to-one with one of the multiple terminal devices, thus using the user interfaces displayed on different terminal devices as the basis for testing. The aforementioned multiple different terminal devices can be different models or system versions of the same brand or multiple brands, and can include various types of terminal devices. For example, the multiple terminal devices can include mobile phones of different brands, models, and system versions, and / or tablet computers of different brands, models, and system versions. An automated script can be prepared and distributed to each terminal device participating in the compatibility test to progressively execute the interface anomaly detection method provided in this disclosure.

[0083] In step S102, the vertex coordinate information of each object in each user interface in the multiple user interfaces is obtained.

[0084] It is understandable that many objects exist within each user interface. At the user level (i.e., the content displayed on the user interface, i.e., the image of the user interface), these objects include elements such as icons, buttons, and images. At the code level, these objects can be the code corresponding to the icons, buttons, and images in the user interface; this code can be the source code of the user interface. Regardless of whether it is based on the image or the code of the user interface, the vertices of the aforementioned objects and their corresponding vertex coordinates can be determined.

[0085] In step S103, the objects are compared based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly.

[0086] For example, based on the vertex coordinate information of each object, each object in a user interface can be compared with other objects in the same user interface to determine whether there is any overlap in object ranges. Alternatively, each object in a user interface can be compared with other user interfaces one by one to determine the degree of matching between the user interface and other user interfaces, thereby determining whether there are one or more user interfaces displaying abnormalities.

[0087] In the above technical solution, multiple user interfaces displayed by the target application on multiple terminal devices are acquired. The vertex coordinate information of each object in each user interface is obtained, and the objects are compared based on this vertex coordinate information to determine whether each user interface displays an anomaly. By comparing the vertex coordinate information of each object in each user interface, this technical solution can determine whether the user interface displays anomalies by identifying differences between objects. It eliminates the need to maintain a large number of reference images and is applicable to detecting various anomalies in the user interface, thus improving the accuracy of user interface anomaly detection to a certain extent.

[0088] Optionally, step S102 above may include:

[0089] Based on the feature information of each user interface, obtain the vertex coordinate information of each object in each user interface; wherein, the feature information includes the code of the user interface and / or a screenshot of the user interface.

[0090] Optionally, step S103 above may include:

[0091] The objects are compared based on the first vertex coordinates and / or the second vertex coordinates of each object in the user interface to determine whether each user interface displays an anomaly; the first vertex coordinates are determined based on the user interface code, and the second vertex coordinates are determined based on the screenshot of the user interface.

[0092] Alternatively, in one implementation, the aforementioned feature information is the code of the user interface, meaning that anomaly detection can be performed based on the user interface code. Figure 2 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 2 As shown, obtaining the vertex coordinate information of each object in each user interface based on the feature information of each user interface in step S102 may include the following steps.

[0093] In step S1021, the code for each user interface is obtained.

[0094] In step S1022, the first vertex coordinate information of each object in each user interface is obtained according to the code.

[0095] It is understandable that steps S1021 to S1022 are for detecting objects at the code level of the user interface, such as source code. Since each object in the user interface has corresponding code at the source code level, for example, the source code of an object can be: [0]android.widget.Image Button[193,350][526,470], where “[0]android.widget.ImageButton” represents the object, and “[193,350][526,470]” is the coordinate information of the first vertex of the object in the user interface.

[0096] Optionally, if the first vertex coordinate information of each object in each user interface is obtained based on the code, the step S103 above, which compares the objects based on the first vertex coordinate information and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly, may include:

[0097] Based on the first vertex coordinates of each object in each user interface, the coordinate ranges of each object in each user interface are compared to determine whether each user interface is abnormal.

[0098] It's understandable that in any user interface, some objects might have vertices within the coordinate range of other objects, potentially resulting in object overlap or a normal interface where the corresponding image is a floating image. Therefore, it's necessary to compare the coordinate ranges of each object in each user interface to determine if object overlap occurs.

[0099] Optionally, Figure 3 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 3 As shown, the above-mentioned method of comparing the coordinate ranges of each object in each user interface based on the first vertex coordinate information of each object in each user interface to determine whether each user interface is abnormal may include the following steps.

[0100] In step S1031, the coordinate range of each object in each user interface is obtained based on the first vertex coordinate information of each object in each user interface.

[0101] In step S1032, the coordinate ranges of each object in each user interface are compared to determine whether there are any abnormal objects with intersecting coordinate ranges in each user interface. The intersecting coordinate ranges refer to the coordinates of one or more vertices of one object being located within the coordinate range of another object.

[0102] The aforementioned "one or more vertices" can be, for example, a single vertex (the actual value of the vertex can be set as needed). That is, if an object has more than one vertex within the coordinate range of another object, then the coordinate ranges of the two objects can be considered to intersect. If an object has no vertices within the coordinate range of another object, then it can be determined that the coordinate ranges of the two objects do not intersect. It can be understood that if the coordinate ranges of at least one object in any user interface intersect, it can be determined that there is object overlap in the user interface. In the source code of the user interface, each object in the user interface has a corresponding source code. For example, the source code of one object can be: [0]android.widget.ImageButton[0,1115][231,1208], and the source code of another object can be: [0]android.widget.ImageButton[193,350][526,470]. According to the source code of the object in the user interface, the coordinate information of its corresponding first vertex can be obtained. According to the first vertex coordinate information of each vertex of the object, the coordinate range of the object can be obtained. Thus, it can be determined whether there are abnormal objects with intersecting coordinate ranges based on the coordinate ranges of each object.

[0103] In step S1033, if there are abnormal objects with intersecting coordinate ranges in the first user interface, it is determined whether the same objects in other user interfaces also have intersecting coordinate ranges, so as to obtain a first number of user interfaces with intersecting coordinate ranges.

[0104] The first user interface is any one of the multiple user interfaces, and the same object is an object in other user interfaces that has the same coordinate information as the abnormal object.

[0105] In step S1034, if the first quantity is greater than or equal to the set quantity, it is determined that the first user interface is displayed normally.

[0106] In step S1035, if the first quantity is less than the set quantity, it is determined that the first user interface display is abnormal.

[0107] Understandably, when an abnormal object with intersecting coordinate ranges appears in any user interface, it's not possible to directly determine whether the user interface is displaying abnormally. It's necessary to compare it with other user interfaces to determine if the same object with intersecting coordinate ranges exists in the user interfaces displayed on other terminal devices. For example, a set number can be set to determine whether the user interface displays abnormally when intersecting coordinate ranges occur. For instance, if the number of terminal devices is 20, this set number can be set to 15. Assuming that object A and object B have intersecting coordinate ranges in user interface 1 of terminal device 1, it can be checked whether object A and object B also exhibit this phenomenon in the user interfaces of the other 19 terminal devices. If it's detected that object A and object B also have intersecting coordinate ranges in the user interfaces of 16 other terminal devices, then user interface 1 of terminal device 1 is considered to be displaying normally, such as in the case of a floating image. If it's detected that object A and object B also have intersecting coordinate ranges in the user interfaces of only 2 terminal devices, then user interface 1 is considered to be displaying abnormally, such as in the case of overlapping objects.

[0108] Alternatively, in another implementation, the aforementioned feature information can be a screenshot of the user interface; that is, anomaly detection can be performed based on the image of the user interface, which can be obtained by taking a screenshot. Figure 4 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 4 As shown, the step S102 above, which involves obtaining the vertex coordinate information of each object in each user interface based on the feature information of each user interface, may include the following steps.

[0109] In step S1023, a screenshot of each user interface is obtained.

[0110] In step S1024, the screenshot of the interface is identified by an edge detection algorithm to obtain the second vertex coordinate information of each object in each user interface.

[0111] Understandably, a screenshot of a user interface can contain multiple objects and their information. For example, when using an application, the user interface may contain multiple clickable buttons, icons, text descriptions, images, and other objects. Since each object in the screenshot is in image form, edge detection algorithms can be used to obtain the coordinates of the second vertex of each object in the screenshot. Edge detection algorithms can include, for example, the Holistically-Nested Edge Detection (HED) algorithm and the Canny edge detection operator.

[0112] Optionally, if the second vertex coordinate information of each object in each user interface is obtained from the screenshot of the user interface, the step S103 above, which compares the objects based on the first vertex coordinate information and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly, may include:

[0113] Based on the second vertex coordinates of each object in each user interface, the degree of matching between each object in each user interface and each object in other interfaces is obtained, so as to determine whether each user interface is abnormal based on the degree of matching.

[0114] Understandably, by obtaining the second vertex coordinates of each object through edge detection algorithms, the number of objects in the screenshot can be determined. However, the number of objects in the screenshot of the same application may differ across different terminal devices, and the objects corresponding to the same second vertex coordinates may also differ. For example, at a certain second vertex coordinate, the object corresponding to the second vertex coordinate might be a "Confirm" button on terminal device A, while on terminal device B it might be a "Cancel" button.

[0115] Optionally, Figure 5 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 5 As shown, the above-mentioned method of obtaining the matching degree of each object in each user interface with each object in other interfaces based on the second vertex coordinate information of each object in each user interface, and determining whether each user interface is abnormal based on the matching degree, may include the following steps.

[0116] In step S1036, the number of objects in each user interface is determined based on the second vertex coordinate information of each object in each user interface.

[0117] In step S1037, a reference value for the number of objects is obtained based on the number of objects in each user interface. This reference value is determined based on the average number of objects in multiple user interfaces.

[0118] In step S1038, the number of objects in each user interface is compared with a reference value.

[0119] In step S1039, if the number of objects in the second user interface is less than the reference value, it is determined that the second user interface is displaying abnormally; the second user interface is any one of multiple user interfaces.

[0120] In step S10310, if the number of objects in the second user interface is greater than or equal to the reference value, the image vector of each object in the second user interface is obtained, so as to determine whether the second user interface is displaying abnormally based on the image vector.

[0121] Understandably, after obtaining the number of objects in the user interface, the number of objects in each user interface can be compared with a reference value. This reference value is determined based on the average number of objects in multiple user interfaces, for example, it could be 60% of the average number of objects in multiple user interfaces. When the number of objects in a certain user interface is less than the set reference value, the user interface can be considered to be displaying abnormally, such as a black screen, a white screen, or incomplete loading. When the number of objects in a certain user interface is greater than or equal to the set reference value, it cannot be determined whether the user interface is displaying abnormally. It is necessary to vectorize the images of each object in the screenshot of the user interface to further confirm whether the user interface is displaying abnormally.

[0122] Optionally, Figure 6 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 6 As shown, the step S1039 above, which involves obtaining the image vectors of each object in the second user interface to determine whether the second user interface is displaying abnormally based on the image vectors, may include the following steps.

[0123] In step S10391, the object images in each second user interface are vectorized to obtain the image vectors of each object in each second user interface.

[0124] In step S10392, based on the image vectors of each object in each second user interface, it is determined whether the image vectors with the same image number in each second user interface match each other.

[0125] In step S10393, if the first image vectors in each second user interface match, it is determined that the first image vectors in each second user interface are normal; the first image vectors are image vectors with the same image number in each second user interface.

[0126] In step S10394, if there is a mismatch between the first image vectors in each second user interface, the matching rate of the first image vectors in each second user interface is obtained.

[0127] In step S10395, if the matching rate is greater than or equal to a set threshold, the second user boundaries in which the first image vectors do not match are determined to be display abnormal.

[0128] In step S10396, if the matching rate is less than a set threshold, the first image vector in each second user interface is displayed normally.

[0129] In step S10397, if the image vectors of all objects in any second user area are displayed normally, the second user area is determined to be displayed normally.

[0130] Understandably, the vectorization of each element in a screenshot of the user interface can be achieved using the VGG (Visual Geometry Group, also known as super-resolution test sequence) model. The VGG model, or VGGNet, is a deep convolutional neural network. After obtaining the object image for each object, the object images can be numbered. During this numbering process, objects nested within other objects can be ignored. Each object image is numbered according to its horizontal and vertical position within the user interface. This method is used to obtain the object image numbers for each terminal device's user interface, and these numbers represent the object image's position within the user interface.

[0131] The acquired object images can then be vectorized to obtain image vectors for each object in each second user interface. It can be understood that the object image number can also be used as the image vector number. After obtaining the image vectors for each object, for any image vector in any user interface, vector retrieval can be performed in other user interfaces. For example, in one implementation, each image vector in any user interface can be compared with image vectors of object images with the same number in other user interfaces to determine if they match. If they all match, the image vector is considered normal; if there is a mismatch, the matching rate of the image vector in each user interface is obtained.

[0132] For example, if the matching rate threshold is set to 60%, after the judgment in step S1037, assuming there are 20 terminal devices with the aforementioned second interface (i.e., 20 second interfaces), and assuming that the image vectors with the same number in the user interfaces of terminal devices C and D do not match each other, while the image vectors with the same number in the user interfaces of the remaining terminal devices match each other, then the matching rate of the image vector with that number is (20-2) / 20 = 90%, which is greater than the set threshold of 60%. Therefore, the user interfaces of terminal devices C and D are considered to be displaying abnormally, while the image vectors of the other terminal devices are determined to be displaying normally. If, among the aforementioned 20 terminal devices, the user interface of each terminal device does not match the image vectors with the same number in the user interfaces of other terminal devices, then the matching rate is 0%, which is less than the set threshold of 60%, and the 20 terminal devices can be considered to be displaying normally in this object, such as random data in a food delivery platform application. If all image vectors of a certain user interface are displayed normally, then the user interface is determined to be displaying normally.

[0133] Alternatively, in another implementation, code-based detection methods and screenshot-based detection methods can be combined to jointly determine whether the user interface is abnormal based on the detection results of the two methods. Figure 7 This is a flowchart illustrating another interface anomaly detection method according to an exemplary embodiment, such as... Figure 7 As shown, the step S103 described above, which compares the objects based on the first vertex coordinate information of each object in the user interface and / or the second vertex coordinate information of each object in the user interface to determine whether each user interface displays an anomaly, may include the following steps.

[0134] In step S201, the coordinate ranges of each object in each user interface are compared based on the first vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly, and the first identification result of each user interface is obtained.

[0135] The coordinate information of the first vertex of each object in each user interface is obtained based on the object's code. The method of obtaining this information is the same as that shown in steps S1021 and S1022 above, and will not be described again.

[0136] In step S202, based on the second vertex coordinate information of each object in each user interface, the matching degree of each object in each user interface with each object in other interfaces is obtained, so as to determine whether each user interface displays an anomaly based on the matching degree, and obtain the second recognition result of each user interface.

[0137] The second vertex coordinate information of each object in each user interface is obtained from a screenshot of the user interface. The method of obtaining this information is the same as that shown in steps S1023 and S1024 above, and will not be described again.

[0138] In step S203, it is determined whether each user interface displays an anomaly based on the first and second identification results of each user interface.

[0139] It is understandable that step S201 obtains the first recognition result based on the first vertex coordinate information of each object determined by the code. The method can refer to steps S1030 to S1034 above, and will not be repeated here. Step S202 obtains the second recognition result based on the second vertex coordinate information of each object determined by the screenshot of the interface. The method can refer to steps S1035 to S1039 above, and will not be repeated here. Determining whether each user interface displays abnormalities through the first recognition result and the second recognition result can increase the recognition range and recognition accuracy of interface abnormality detection.

[0140] Optionally, Figure 8 This is a flowchart illustrating yet another interface anomaly detection method according to an exemplary embodiment, such as... Figure 8 As shown, for any user interface, step S201 may include the following steps.

[0141] In step S2011, if both the first and second identification results of the user interface indicate that the user interface is displaying abnormally, the user interface is determined to be displaying abnormally.

[0142] In step S2012, if both the first and second recognition results of the user interface indicate that the user interface is displayed normally, it is determined that the user interface is displayed normally.

[0143] In step S2013, if one of the first recognition result and the second recognition result of the user interface indicates that the user interface is displayed normally, and the other indicates that the user interface is displayed abnormally, then the user interface is determined to be displayed abnormally.

[0144] It is understood that the first identification result is based on the code of the user interface, and the second identification result is based on the screenshot of the user interface. Therefore, the identification results obtained by different detection methods may differ. Thus, if at least one of the first and second identification results indicates an abnormal user interface display, the user interface can be considered abnormal. If both the first and second identification results indicate a normal user interface display, the user interface can be considered normal. Optionally, any one of steps S2011 and S2013 can be executed, or both can be executed. It is understood that if only step S2011 is executed, i.e., an abnormality is determined only when both the first and second identification results indicate an abnormal user interface display, the accuracy of interface anomaly detection can be improved. If only step S2013 is executed, or if steps S2011 and S2013 are executed simultaneously, an abnormality is determined as long as at least one of the first and second identification results indicates an abnormal user interface display, which can increase the detection range of interface anomaly detection.

[0145] In the above technical solution, multiple user interfaces displayed by the target application on multiple terminal devices are acquired, and the vertex coordinate information of each object in each user interface is obtained. The objects are compared based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly. By comparing the vertex coordinate information of each object in each user interface, this technical solution can determine whether the user interface displays anomalies by identifying differences between objects in the user interface. It eliminates the need to maintain a large number of reference images and is applicable to detecting various anomalies in the user interface, thus improving the accuracy of user interface anomaly detection to a certain extent.

[0146] Figure 9 This is a block diagram illustrating an interface anomaly detection device according to an exemplary embodiment. The device is used in an electronic device, see reference... Figure 9 The interface anomaly detection device 900 may include:

[0147] The interface acquisition module 901 is used to acquire multiple user interfaces displayed by the target application on multiple terminal devices.

[0148] The information acquisition module 902 is used to acquire the vertex coordinate information of each object in each user interface in multiple user interfaces.

[0149] The anomaly determination module 903 is used to compare objects based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly.

[0150] Optionally, the information acquisition module 902 can be used for:

[0151] Based on the feature information of each user interface, obtain the vertex coordinate information of each object in each user interface; wherein, the feature information includes the code of the user interface and / or a screenshot of the user interface.

[0152] Optionally, the exception determination module 903 can be used for:

[0153] Based on the first vertex coordinate information of each object in the user interface, and / or the second vertex coordinate information of each object in the user interface, the objects are compared to determine whether each user interface displays an anomaly; wherein, the first vertex coordinate information is determined based on the code of the user interface, and the second vertex coordinate information is determined based on the screenshot of the user interface.

[0154] Alternatively, in one implementation, the feature information is user interface code, and the information acquisition module 902 can be used for:

[0155] Obtain the code for each user interface. This code can be the source code of the user interface.

[0156] Obtain the first vertex coordinates of each object in the user interface based on the code.

[0157] Alternatively, in another implementation, the feature information is a screenshot of the user interface, and the information acquisition module 902 can be used for:

[0158] Get screenshots of each user interface.

[0159] Edge detection algorithms are used to identify screenshots of the interface to obtain the second vertex coordinates of each object in each user interface.

[0160] Optionally, in one implementation, the anomaly determination module 903 includes: a first determination submodule, which can be used to: compare the coordinate ranges of each object in each user interface based on the first vertex coordinate information of each object in each user interface, so as to determine whether each user interface is abnormal.

[0161] Alternatively, in another implementation, the anomaly determination module 903 includes: a second determination submodule, which can be used to: obtain the matching degree of each object in each user interface with each object in other interfaces based on the second vertex coordinate information of each object in each user interface, so as to determine whether each user interface is abnormal based on the matching degree.

[0162] Alternatively, in another implementation, the exception determination module 903 further includes: a third determination submodule;

[0163] The first determining submodule can be used to: compare the coordinate range of each object in each user interface based on the first vertex coordinate information of each object in each user interface, in order to determine whether each user interface displays an anomaly, and obtain the first identification result of each user interface.

[0164] The second determining submodule can be used to: obtain the matching degree of each object in each user interface with each object in other interfaces based on the second vertex coordinate information of each object in each user interface, so as to determine whether each user interface displays an anomaly based on the matching degree, and obtain the second recognition result of each user interface; wherein, the first recognition result mentioned above is the recognition result obtained based on the code of the user interface, and the second recognition result is the recognition result obtained based on the screenshot of the user interface.

[0165] The third determination submodule can be used to: determine whether each user interface displays an anomaly based on the first and second identification results of each user interface.

[0166] Optionally, the first determining submodule can be used for:

[0167] Based on the first vertex coordinates of each object in each user interface, obtain the coordinate range of each object in each user interface.

[0168] The coordinate ranges of each object in each user interface are compared to determine whether there are any abnormal objects with intersecting coordinate ranges in each user interface. An intersecting coordinate range means that the coordinates of one or more vertices of one object are within the coordinate range of another object.

[0169] In the case of an abnormal object with intersecting coordinate ranges in the first user interface, determine whether the same object in other user interfaces also has intersecting coordinate ranges to obtain a first number of user interfaces with intersecting coordinate ranges; the first user interface is any one of multiple user interfaces, and the same object is an object in other user interfaces with the same coordinate information as the abnormal object.

[0170] If the first quantity is greater than or equal to the set quantity, the first user interface is confirmed to be displayed normally.

[0171] If the first quantity is less than the set quantity, it is determined that the first user interface is displaying abnormally.

[0172] Optionally, the second determining submodule can be used for:

[0173] The number of objects in each user interface is determined based on the second vertex coordinates of each object in each user interface.

[0174] A reference value for the number of objects is obtained based on the number of objects in each user interface, which is determined by the average number of objects in multiple user interfaces.

[0175] Compare the number of objects in each user interface with a reference value.

[0176] If the number of objects in the second user interface is less than the reference value, it is determined that the second user interface is displaying abnormally; the second user interface is any one of multiple user interfaces.

[0177] If the number of objects in the second user interface is greater than or equal to the reference value, obtain the image vector of each object in the second user interface, and determine whether the second user interface is displaying abnormally based on the image vector.

[0178] Optionally, the second determining submodule can be used for:

[0179] Vectorize the object images in each second user interface to obtain the image vectors of each object in each second user interface.

[0180] Based on the image vectors of each object in each second user interface, determine whether the image vectors with the same image number in each second user interface match each other.

[0181] If the first image vectors in each second user interface match, it is determined that the first image vectors in each second user interface are normal; the first image vectors are image vectors with the same image number in each second user interface.

[0182] If there is a mismatch between the first image vectors in each second user interface, obtain the matching rate of the first image vectors in each second user interface.

[0183] If the matching rate is greater than or equal to a set threshold, the second user boundary in which the first image vector does not match is determined to be a display anomaly.

[0184] If the matching rate is less than the set threshold, the first image vector in each second user area will be displayed normally;

[0185] If the image vectors of all objects in any second user area are displayed correctly, then the second user area is determined to be displayed correctly.

[0186] Optionally, this third determining submodule can be used for:

[0187] For any user interface, if both the first and second identification results indicate that the user interface is displaying abnormally, then the user interface is determined to be displaying abnormally.

[0188] If both the first and second recognition results of the user interface indicate that the user interface is displayed normally, then the user interface is determined to be displayed normally.

[0189] If one of the first and second recognition results of the user interface indicates that the user interface is displayed normally, and the other indicates that the user interface is displayed abnormally, then the user interface is determined to be displayed abnormally.

[0190] In the above technical solution, multiple user interfaces displayed by the target application on multiple terminal devices are acquired, and the vertex coordinate information of each object in each user interface is obtained. The objects are compared based on the vertex coordinate information of each object in each user interface to determine whether each user interface displays an anomaly. By comparing the vertex coordinate information of each object in each user interface, this technical solution can determine whether the user interface displays anomalies by identifying differences between objects in the user interface. It eliminates the need to maintain a large number of reference images and is applicable to detecting various anomalies in the user interface, thus improving the accuracy of user interface anomaly detection to a certain extent.

[0191] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0192] This disclosure also provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the interface anomaly detection method provided in this disclosure.

[0193] Figure 10 This is a block diagram illustrating an electronic device 1000 according to an exemplary embodiment. For example... Figure 10 As shown, the electronic device 1000 may include: a processor 1001 and a memory 1002. The electronic device 1000 may also include one or more of a multimedia component 1003, an input / output (I / O) interface 1004, and a communication component 1005.

[0194] The processor 1001 controls the overall operation of the electronic device 1000 to complete all or part of the steps in the interface anomaly detection method described above. The memory 1002 stores various types of data to support the operation of the electronic device 1000. This data may include, for example, instructions for any application or method operating on the electronic device 1000, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1002 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1003 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1002 or transmitted via communication component 1005. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1004 provides an interface between processor 1001 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1005 is used for wired or wireless communication between the electronic device 1000 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 1005 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0195] In an exemplary embodiment, the electronic device 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the interface anomaly detection method described above.

[0196] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the interface anomaly detection method described above. For example, the computer-readable storage medium may be the memory 1002 including the program instructions described above, which may be executed by the processor 1001 of the electronic device 1000 to complete the interface anomaly detection method described above.

[0197] Figure 11 This is a block diagram illustrating an electronic device 1100 according to an exemplary embodiment. For example, the electronic device 1100 may be provided as a server. (Refer to...) Figure 11 The electronic device 1100 includes a processor 1122, which may be one or more, and a memory 1132 for storing computer programs executable by the processor 1122. The computer program stored in the memory 1132 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 1122 may be used to execute the computer program to perform the aforementioned interface anomaly detection method.

[0198] Additionally, the electronic device 1100 may also include a power supply component 1126 and a communication component 1150. The power supply component 1126 can be used to perform power management of the electronic device 1100, and the communication component 1150 can be used to implement communication of the electronic device 1100, such as wired or wireless communication. Furthermore, the electronic device 1100 may also include an input / output (I / O) interface 1158. The electronic device 1100 can operate on an operating system stored in the memory 1132.

[0199] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the interface anomaly detection method described above. For example, the non-transitory computer-readable storage medium may be the memory 1132 including the program instructions described above, which may be executed by the processor 1122 of the electronic device 1100 to complete the interface anomaly detection method described above.

[0200] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described interface anomaly detection method when executed by the programmable device.

[0201] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0202] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0203] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. An interface abnormality detection method characterized by comprising: The method is applied to an electronic device, and the method comprises: obtaining a plurality of user interfaces displayed by a target application on a plurality of terminal devices; obtaining vertex coordinate information of each object in each of the plurality of user interfaces; obtaining a first identification result and a second identification result of each of the user interfaces according to the vertex coordinate information, and determining whether each of the user interfaces is displayed abnormally according to the first identification result and the second identification result of each of the user interfaces; wherein the first identification result is obtained by: obtaining a coordinate range of each object in each of the user interfaces according to first vertex coordinate information of each object in each of the user interfaces; comparing the coordinate ranges of each object in each of the user interfaces to determine whether there is an abnormal object with intersecting coordinate ranges in each of the user interfaces, the intersecting coordinate ranges referring to the coordinates of one or more vertices of an object being located within the coordinate range of another object; in the case that there is an abnormal object with intersecting coordinate ranges in a first user interface, determining whether the same object in other user interfaces also has the intersecting coordinate ranges to obtain a first number of user interfaces with the intersecting coordinate ranges, the first user interface being any one of the plurality of user interfaces, and the same object being an object with the same coordinate information as the abnormal object in the other user interfaces; in the case that the first number is less than a set number, determining that the first user interface is displayed abnormally, and obtaining a first identification result indicating abnormality; wherein the second identification result is obtained by: determining the number of objects in each of the user interfaces according to second vertex coordinate information of each object in each of the user interfaces; obtaining a reference value of the number of objects according to the average value of the number of objects in the plurality of user interfaces, the reference value being determined according to the average value of the number of objects in the plurality of user interfaces; comparing the number of objects in each of the user interfaces with the reference value; in the case that the number of objects in a second user interface is greater than or equal to the reference value, performing vectorization on the object pictures in each of the user interfaces to obtain picture vectors of each object in each of the user interfaces, the second user interface being any one of the plurality of user interfaces; determining whether picture vectors with the same picture number match each other according to the picture vectors of each object in each of the user interfaces; in the case that a first picture vector with the same picture number does not match, obtaining a matching rate of the first picture vector; in the case that the matching rate is greater than or equal to a set threshold, determining that the user interface in which the first picture vector does not match is displayed abnormally, and obtaining a second identification result indicating abnormality.

2. The method of claim 1, wherein, The vertex coordinate information of each object in each of the plurality of user interfaces is obtained by: obtaining the vertex coordinate information of each object in each of the user interfaces according to feature information of each of the user interfaces, wherein the feature information comprises the code of the user interface and / or the interface screenshot of the user interface.

3. The method of claim 2, wherein, The comparison of the objects according to the vertex coordinate information of the objects in each user interface to determine whether the user interface is displayed abnormally comprises: The comparison of the objects according to the first vertex coordinate information of the objects in the user interface and / or the second vertex coordinate information of the objects in the user interface to determine whether the user interface is displayed abnormally; The first vertex coordinate information is determined according to the code of the user interface, and the second vertex coordinate information is determined according to the interface screenshot of the user interface.

4. The method of claim 2, wherein, The feature information is the code of the user interface, and the vertex coordinate information of the objects in each user interface is obtained according to the feature information of each user interface, which comprises: The code of each user interface is obtained; The first vertex coordinate information of the objects in each user interface is obtained according to the code.

5. The method of claim 2, wherein, The feature information is the interface screenshot of the user interface, and the vertex coordinate information of the objects in each user interface is obtained according to the feature information of each user interface, which comprises: The interface screenshot of each user interface is obtained; The second vertex coordinate information of the objects in each user interface is obtained by recognizing the interface screenshot through an edge detection algorithm.

6. The method of claim 3, wherein, The comparison of the objects according to the first vertex coordinate information of the objects in the user interface and / or the second vertex coordinate information of the objects in the user interface to determine whether the user interface is displayed abnormally comprises: The coordinate ranges of the objects in each user interface are compared according to the first vertex coordinate information of the objects in each user interface to determine whether the user interface is abnormal.

7. The method of claim 3, wherein, The comparison of the objects according to the first vertex coordinate information of the objects in the user interface and / or the second vertex coordinate information of the objects in the user interface to determine whether the user interface is displayed abnormally comprises: The matching degree of the objects in each user interface with the objects in other interfaces is obtained according to the second vertex coordinate information of the objects in each user interface to determine whether the user interface is abnormal according to the matching degree.

8. The method of claim 1, wherein, The method further comprises: In the case that the first number is greater than or equal to a set number, it is determined that the first user interface is displayed normally.

9. The method of claim 1, wherein, The method further comprises: In the case that the number of objects in the second user interface is less than the reference value, it is determined that the second user interface is displayed abnormally.

10. The method of claim 1, wherein, The determination of whether each user interface is displayed abnormally according to the first identification result and the second identification result of each user interface comprises: In the case that the first identification result and the second identification result of any user interface both indicate that the user interface is displayed abnormally, it is determined that the user interface is displayed abnormally; In the case that the first identification result and the second identification result of the user interface both indicate that the user interface is displayed normally, it is determined that the user interface is displayed normally; In a case that one of the first identification result and the second identification result of the user interface indicates that the user interface is displayed normally and the other indicates that the user interface is displayed abnormally, it is determined that the user interface is displayed abnormally.

11. An interface abnormality detection device characterized by comprising: The device is applied to an electronic device, and the device comprises: an interface obtaining module, configured to obtain a plurality of user interfaces displayed by a target application on a plurality of terminal devices; an information obtaining module, configured to obtain vertex coordinate information of each object in each user interface of the plurality of user interfaces; an abnormality determining module, configured to obtain a first identification result and a second identification result of each user interface according to the vertex coordinate information, and determine whether the each user interface is displayed abnormally according to the first identification result and the second identification result of the each user interface; wherein the first identification result is obtained by: obtaining coordinate ranges of each object in the each user interface according to first vertex coordinate information of each object in the each user interface; comparing the coordinate ranges of each object in the each user interface to determine whether there is an abnormal object with intersecting coordinate ranges in the each user interface, the intersecting coordinate ranges indicating that one or more vertexes of one object are located in the coordinate range of another object; in a case that there is an abnormal object with intersecting coordinate ranges in a first user interface, determining whether the same object in other user interfaces also has the intersecting coordinate ranges to obtain a first number of user interfaces with the intersecting coordinate ranges, the first user interface being any user interface of the plurality of user interfaces, and the same object being an object with the same coordinate information as the abnormal object in the other user interfaces; in a case that the first number is less than a set number, determining that the first user interface is displayed abnormally, and obtaining a first identification result indicating abnormality; wherein the second identification result is obtained by: determining a number of objects in the each user interface according to second vertex coordinate information of each object in the each user interface; obtaining a reference value of the number of objects according to an average value of the number of objects in the plurality of user interfaces, the reference value being determined according to the average value; comparing the number of objects in the each user interface with the reference value; in a case that the number of objects in a second user interface is greater than or equal to the reference value, performing vectorization on object pictures in each user interface to obtain picture vectors of each object in each user interface, the second user interface being any user interface of the plurality of user interfaces; determining whether picture vectors with the same picture number match each other according to the picture vectors of each object in each user interface; in a case that a first picture vector with the same picture number does not match, obtaining a matching rate of the first picture vector; in a case that the matching rate is greater than or equal to a set threshold, determining that the user interface in which the first picture vector does not match is displayed abnormally, and obtaining a second identification result indicating abnormality.

12. A screen abnormality detection apparatus characterized by comprising: comprise: a processor; a memory for storing processor-executable instructions; The processor is configured to execute the executable instructions to implement the steps of the method of any one of claims 1-10.

13. A computer-readable storage medium having stored thereon computer program instructions, wherein, The program instructions, when executed by the processor, implement the steps of the method of any one of claims 1-10.

14. A chip, characterized by The apparatus comprises a processor and an interface; the processor is configured to read instructions to implement the method of any one of claims 1-10.

Images