CN112783789A

CN112783789A - Adaptation test method, device and computer readable storage medium

Info

Publication number: CN112783789A
Application number: CN202110163201.3A
Authority: CN
Inventors: 陈建华; 梁永泽
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2021-02-05
Filing date: 2021-02-05
Publication date: 2021-05-11
Anticipated expiration: 2041-02-05
Also published as: CN112783789B

Abstract

The application provides an adaptation test method, equipment and a computer readable storage medium; the method comprises the following steps: running the adaptive test client and displaying a selection control aiming at the client to be tested; responding to the selection operation acted on the selection control, and displaying a running page of the running client to be tested and a test page of the running adaptive test client, wherein the test page is independent of the running page; acquiring abnormal data of the running client to be tested and acquiring data of the equipment to be tested through the running adaptive test client; and sending the adaptation test data carrying the abnormal data and the data of the equipment to be tested to the server side equipment so that the server side equipment determines the adaptation test result comprising the estimated abnormal equipment based on the adaptation test data. Through the application, the test effect of the adaptation test can be improved.

Description

Adaptation test method, device and computer readable storage medium

Technical Field

The present application relates to testing technologies in the field of computer applications, and in particular, to an adaptation testing method, an adaptation testing device, and a computer-readable storage medium.

Background

With the rapid development of computer application technology, the types of terminal devices are increasing, and therefore, before the functional application is put into the market for application, the client of the functional application is generally operated in a plurality of different types of terminal devices to perform adaptation tests, and then the functional application is completed based on adaptation test results.

Generally, in order to perform an adaptation test, various instructions are usually sent to a terminal device, so that the terminal device runs a client of a function application and intercepts a screenshot in a running process and sends the screenshot to a server device, and the server device also obtains the screenshot. However, in the process of implementing the adaptation test, since the server device can only obtain the screenshot sent by the terminal device, the adaptation test result obtained by the server device based on the screenshot is simpler, and the test effect of the adaptation test is poorer.

Disclosure of Invention

The embodiment of the application provides an adaptation test method, an adaptation test device, adaptation test equipment and a computer-readable storage medium, and the test effect of the adaptation test can be improved.

The technical scheme of the embodiment of the application is realized as follows:

the embodiment of the application provides an adaptation test method, which comprises the following steps:

running the adaptive test client and displaying a selection control aiming at the client to be tested;

responding to the selection operation acted on the selection control, and displaying a running page of the running client to be tested and a test page of the running adaptive test client, wherein the test page is independent of the running page;

acquiring abnormal data of the running client to be tested and acquiring data of equipment to be tested through the running adaptive test client;

sending adaptive test data carrying the abnormal data and the data of the equipment to be tested to server side equipment so as to enable the server side equipment to

Determining an adaptation test result including a predicted abnormal device based on the adaptation test data.

The embodiment of the present application further provides an adaptation testing method, including:

receiving adaptation test data which are sent by equipment to be tested and comprise abnormal data and equipment to be tested data, wherein the adaptation test data are acquired through an adaptation test client running on the equipment to be tested, and the abnormal data correspond to the client running on the equipment to be tested;

determining a clustering dimension based on the device information associated with the abnormal data;

clustering the data of the equipment to be tested and a preset equipment database according to the clustering dimension to obtain each equipment cluster;

determining a related equipment cluster corresponding to the equipment to be tested from each equipment cluster;

and obtaining estimated abnormal equipment except the equipment to be tested in the associated equipment cluster, thereby obtaining an adaptive test result comprising the estimated abnormal equipment, wherein the estimated abnormal equipment is estimated equipment with abnormality corresponding to the abnormal data.

The embodiment of the present application provides a first adaptation testing arrangement, includes:

the client running module is used for running the adaptive test client and displaying a selection control for the client to be tested;

the adaptive testing module is used for responding to the selection operation acted on the selection control and displaying the running page of the running client to be tested and the testing page of the running adaptive testing client, wherein the testing page is independent of the running page;

the data acquisition module is used for acquiring abnormal data of the running client to be tested and acquiring data of equipment to be tested through the running adaptive test client;

and the data sending module is used for sending adaptation test data carrying the abnormal data and the data of the equipment to be tested to the server side equipment so that the server side equipment determines an adaptation test result comprising pre-estimated abnormal equipment based on the adaptation test data.

In this embodiment of the application, the data acquisition module is further configured to monitor the running client to be tested through the running adaptive test client, and obtain monitored client running data; and when the client to be tested, which determines that the client running data is running, is abnormal based on preset running data, generating the abnormal data.

In this embodiment of the application, the data obtaining module is further configured to, in a process of monitoring the running client to be tested by the running adaptive test client, respond to a reporting operation acting on the test page, and display an abnormal reporting control; and responding to the reporting operation acted on the abnormal reporting control to obtain the abnormal data.

In this embodiment of the present application, the client running module is further configured to run the adaptive test client and display a path test setting control, where the path test setting control is used to trigger a setting process of a path test; responding to the setting operation acted on the path test setting control, and displaying set path test setting information; and responding to the test trigger operation aiming at the path test setting information, and displaying the selection control aiming at the client to be tested.

In this embodiment of the application, the first adaptive testing device further includes a path testing module, configured to set information based on the path test, and perform screenshot on the running page through the running adaptive testing client, so as to obtain running path testing data of the client to be tested.

In this embodiment of the application, the data sending module is further configured to send the adaptation test data, which carries the path test data, the abnormal data, and the data of the device to be tested, to the server device.

In this embodiment of the application, the first adaptive testing device further includes a version obtaining module, configured to obtain, through the adaptive testing client, client version information of the running client to be tested.

In this embodiment of the application, the data sending module is further configured to send the adaptation test data, which carries the client version information, the abnormal data, and the data of the device to be tested, to the server device.

The embodiment of the present application provides a second adaptation testing arrangement, includes:

the data receiving module is used for receiving adaptation test data which are sent by equipment to be tested and comprise abnormal data and equipment to be tested data, wherein the adaptation test data are acquired through an adaptation test client running on the equipment to be tested, and the abnormal data correspond to the client running on the equipment to be tested;

the dimension determining module is used for determining a clustering dimension based on the equipment information associated with the abnormal data;

the equipment clustering module is used for clustering the equipment data to be tested and a preset equipment database according to the clustering dimension to obtain each equipment cluster;

a class cluster determining module, configured to determine, from each device class cluster, a related device class cluster corresponding to the device to be tested;

and the equipment estimation module is used for acquiring estimated abnormal equipment except the equipment to be tested in the associated equipment cluster so as to acquire an adaptive test result comprising the estimated abnormal equipment, wherein the estimated abnormal equipment is estimated equipment with abnormality corresponding to the abnormal data.

In this embodiment of the application, the second adaptive testing device further includes an exception filtering module, configured to filter the exception data to obtain to-be-processed exception data.

In this embodiment of the application, the dimension determining module is further configured to determine the clustering dimension based on the device information associated with the to-be-processed abnormal data.

In the embodiment of the present application, the adaptive test data further includes client version information of the running client to be tested; the anomaly filtering module is further used for acquiring repaired anomaly data corresponding to an application to be tested, wherein the client to be tested corresponds to the application to be tested; acquiring repaired client version information corresponding to the abnormal data from the repaired abnormal data; and in the abnormal data, determining the data with the client version information higher than the repaired client version information as the abnormal data to be processed.

In an embodiment of the present application, the exception filtering module is further configured to obtain device reference data, where the device reference data is the lowest configuration information of a device running the client to be tested; and when the data of the equipment to be tested is higher than or equal to the reference data of the equipment, determining the abnormal data as the abnormal data to be processed.

In this embodiment of the application, the second adaptive testing device further includes an information updating module, configured to obtain an abnormal similarity between the abnormal data and preset abnormal data; when the abnormal similarity is smaller than a similarity threshold value, adding the abnormal data into the preset abnormal data, and adding the data of the equipment to be tested into the preset equipment database; and when the abnormal similarity is larger than or equal to the similarity threshold, merging the abnormal data and the preset abnormal data, and adding the data of the equipment to be tested to the equipment information corresponding to the preset abnormal data in the preset equipment database.

In this embodiment of the application, the device clustering module is further configured to cluster the added preset device database according to the clustering dimension.

In an embodiment of the present application, the adaptation test data further includes path test data; the second adaptation testing device further comprises an abnormal playback module, which is used for generating a client abnormal video based on the path testing data when the abnormal similarity is smaller than the similarity threshold; and playing the abnormal video of the client.

In this embodiment of the present application, the second adaptive testing apparatus further includes a priority determining module, configured to obtain a coverage rate of the use of the pre-estimated abnormal device; and determining the processing priority of the abnormal data based on the use coverage rate, so as to correct the abnormality corresponding to the abnormal data based on the processing priority.

In this embodiment of the present application, the second adaptive testing device further includes a processing triggering module, configured to display the abnormal data; receiving a processing operation for the exception data, wherein the processing operation comprises one or more of an ignore operation, a device association operation, and a fix-up request operation.

In this embodiment of the application, the dimension determining module is further configured to determine the clustering dimension based on the device information associated with the abnormal data in response to the device association operation.

In this embodiment of the present application, the second adaptive testing apparatus further includes an information sending module, configured to obtain a sending object; and sending reminding information carrying the estimated abnormal equipment to the sending object.

The embodiment of the application provides a device under test for adaptation test, includes:

a first memory for storing executable instructions;

and the first processor is used for realizing the adaptive test method applied to the equipment to be tested when the executable instructions stored in the first memory are executed.

The embodiment of the application provides a server side device for adaptation test, which comprises:

a second memory for storing executable instructions;

and the second processor is used for realizing the adaptation test method applied to the server equipment when the executable instructions stored in the second memory are executed.

The embodiment of the application provides a computer-readable storage medium, which stores executable instructions and is used for realizing an adaptive test method applied to equipment to be tested when being executed by a first processor; or the adaptation test method applied to the server-side equipment is realized when the second processor executes the adaptation test method.

The embodiment of the application has at least the following beneficial effects: triggering the operation of the client to be tested by operating the adaptive test client on the equipment to be tested, monitoring abnormal data of the operating client to be tested through the operating adaptive test client, acquiring data of the equipment to be tested, sending the data to be tested to the server equipment, clustering the equipment by the server equipment based on the abnormal data and the data of the equipment to be tested, and predicting estimated abnormal equipment with possible abnormality; therefore, the obtained adaptive test result has great significance, and the test effect of the adaptive test can be improved.

Drawings

FIG. 1 is an alternative architecture diagram of an adaptive test system provided by an embodiment of the present application;

fig. 2 is a schematic structural diagram of a terminal in fig. 1 according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a server in fig. 1 according to an embodiment of the present disclosure;

FIG. 4 is an alternative flow chart of the adaptation testing method provided by the embodiment of the present application;

FIG. 5 is a schematic flow chart of another alternative adaptation testing method provided in the embodiments of the present application;

FIG. 6 is a schematic flow chart of another alternative fitting test method provided in the embodiments of the present application;

fig. 7 is a schematic flowchart of an exemplary adaptive testing method applied to a device under test according to an embodiment of the present application;

fig. 8 is a schematic diagram of an exemplary running client to be tested according to an embodiment of the present disclosure;

fig. 9 is a schematic page diagram of exemplary data of a device under test according to an embodiment of the present application;

fig. 10 is a flowchart illustrating an exemplary adaptation testing method applied to a server device according to an embodiment of the present application.

Detailed Description

In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the attached drawings, the described embodiments should not be considered as limiting the present application, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.

In the following description, references to the terms "first", "second", and the like are only used for distinguishing similar objects and do not denote a particular order or importance, but rather the terms "first", "second", and the like may be used interchangeably with the order of priority or the order in which they are expressed, where permissible, to enable embodiments of the present application described herein to be practiced otherwise than as specifically illustrated and described herein.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.

Before further detailed description of the embodiments of the present application, terms and expressions referred to in the embodiments of the present application will be described, and the terms and expressions referred to in the embodiments of the present application will be used for the following explanation.

1) An exception, also called a bug (bug) is a defect existing in the specific implementation of hardware, software, and protocol or in the system security policy, such as flash back, low frame rate, high memory usage, and an error in the output log.

2) The system comprises a client, an application program which is operated in a terminal and used for providing various services, and a function application; for example, adapting a test client, a client to be tested, etc.; the client device is a device running the application, for example, a device under test.

3) The operation is a manner for triggering the device to execute processing, such as a click operation, a double-click operation, a long-press operation, a sliding operation, a gesture operation, a received trigger instruction, and the like; in addition, various operations in the embodiments of the present application may be a single operation or may be a collective term for a plurality of operations.

4) In response to the condition or state on which the process being performed depends being indicated, the one or more operations being performed may be in real time or may have a set delay when the dependent condition or state is satisfied; there is no restriction on the order of execution of the operations performed unless otherwise specified.

5) The floating window is a system-level window and refers to a movable window which floats on the surface of other functional applications; in the android system, the floating Window is managed by a Window Manager Service (WMS), and in addition, the Window management Service is used to manage all windows, such as application windows except system windows.

Generally, in order to perform an adaptation test, for example, when the adaptation test is performed on a theme pack, the theme pack may be copied to a device to be tested, and an application instruction is sent to the device to be tested, so that the device to be tested automatically applies the theme pack; sending a screenshot instruction to the equipment to be tested so that the equipment to be tested can screenshot a screen to obtain a screenshot picture; sending an uploading instruction to the equipment to be tested so that the equipment to be tested uploads the screenshot picture; at this time, the server device also obtains the screenshot. In addition, for the adaptation test, the application client can be installed on the device to be tested, the installed application client is triggered to operate, the application clients are switched one by one to be displayed on the page of the device to be tested, the displayed page is intercepted to obtain a page image, and the server device pulls the page image from the device to be tested. However, in the two processes of implementing the adaptation test, since the service device can only obtain the screenshot sent by the terminal device, the adaptation test result obtained by the service based on the screenshot is simpler, and the test effect of the adaptation test is poorer.

Based on this, embodiments of the present application provide an adaptation test method, apparatus, device, and computer-readable storage medium, which can improve a test effect of an adaptation test. The following describes exemplary applications of the device under test and the server device for adaptation test provided in the embodiment of the present application; the device provided by the embodiment of the present application may be implemented as various types of user terminals such as a notebook computer, a tablet computer, a desktop computer, a set-top box, a mobile device (e.g., a mobile phone, a portable music player, a personal digital assistant, a dedicated messaging device, and a portable game device), and may also be implemented as a server. In the following, an exemplary application will be described when the device under test for adaptation test is implemented as a terminal, and the server-side device for adaptation test is implemented as a server.

Referring to fig. 1, fig. 1 is an alternative architecture diagram of an adaptation test system provided in an embodiment of the present application; as shown in fig. 1, in order to support an adaptive testing application, in the adaptive testing system 100, a terminal 200 (a device under test, which exemplarily shows a terminal 200-1 and a terminal 200-2) and a server 300 (a server device) are connected via a network 400, and the network 400 may be a wide area network or a local area network, or a combination of the two. In addition, the adaptation test system 100 further includes a database 500, and the database 500 is used for providing data support for the server 300 when the server 300 provides the functional service to the terminal 200 through the network 400.

The terminal 200 is used for operating the adaptive test client and displaying a selection control for the client to be tested; responding to the selection operation acted on the selection control, displaying a running page of the running client to be tested and a test page (for example, displaying a floating window with a 'report problem' button) of the running adaptive test client, wherein the test page is independent of the running page; acquiring abnormal data of the running client to be tested and acquiring data of the equipment to be tested through the running adaptive test client; the adaptation test data carrying the abnormal data and the data of the device to be tested is sent to the server 300 through the network 400, so that the server 300 determines the adaptation test result including the estimated abnormal device based on the adaptation test data.

The server 300 is configured to receive adaptation test data including abnormal data and terminal 200 data, which is sent by the terminal 200 through the network 400, where the adaptation test data is obtained through an adaptation test client running on the terminal 200, and the abnormal data corresponds to a client to be tested running on the terminal 200; determining a clustering dimension based on the device information associated with the abnormal data; clustering equipment data to be tested and a preset equipment database according to clustering dimensions to obtain each equipment cluster; determining a related equipment cluster corresponding to the terminal 200 from each equipment cluster; and obtaining estimated abnormal equipment except the terminal 200 in the associated equipment cluster, thereby obtaining an adaptation test result comprising the estimated abnormal equipment, wherein the estimated abnormal equipment is the equipment with the abnormality corresponding to the estimated abnormal data.

In some embodiments, the server 300 may be an independent physical server, may also be a server cluster or a distributed system formed by a plurality of physical servers, and may also be a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a CDN (Content Delivery Network), a big data and artificial intelligence platform, and the like. The terminal 200 may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, which is not limited in the embodiment of the present invention.

Referring to fig. 2, fig. 2 is a schematic diagram of a constituent structure of a terminal in fig. 1 according to an embodiment of the present disclosure, where the terminal 200 shown in fig. 2 includes: at least one first processor 210, a first memory 250, at least one first network interface 220, and a first user interface 230. The various components in the terminal 200 are coupled together by a first bus system 240. It is understood that the first bus system 240 is used to enable communications for connections between these components. The first bus system 240 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as a first bus system 240 in fig. 2.

The first Processor 210 may be an integrated circuit chip having Signal processing capabilities, such as a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., wherein the general purpose Processor may be a microprocessor or any conventional Processor, etc.

The first user interface 230 includes one or more first output devices 231, including one or more speakers and/or one or more visual display screens, that enable presentation of media content. The first user interface 230 also includes one or more first input devices 232, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

The first memory 250 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid state memory, hard disk drives, optical disk drives, and the like. The first memory 250 optionally includes one or more storage devices physically located remotely from the first processor 210.

The first memory 250 includes volatile memory or nonvolatile memory and may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), and the volatile Memory may be a Random Access Memory (RAM). The first memory 250 described in embodiments herein is intended to comprise any suitable type of memory.

In some embodiments, the first memory 250 is capable of storing data to support various operations, examples of which include programs, modules, and data structures, or subsets or supersets thereof, as exemplified below.

A first operating system 251 including system programs for processing various basic system services and performing hardware-related tasks, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks;

a first network communication module 252 for communicating to other computing devices via one or more (wired or wireless) first network interfaces 220, an exemplary first network interface 220 comprising: bluetooth, wireless-compatibility authentication (Wi-Fi), and Universal Serial Bus (USB), etc.;

a first presentation module 253 to enable presentation of information (e.g., a user interface for operating peripherals and displaying content and information) via one or more first output devices 231 (e.g., a display screen, speakers, etc.) associated with the first user interface 230;

a first input processing module 254 for detecting one or more user inputs or interactions from one of the one or more first input devices 232 and translating the detected inputs or interactions.

In some embodiments, the first adaptive testing device provided by the embodiments of the present application may be implemented in software, and fig. 2 illustrates the first adaptive testing device 255 stored in the first memory 250, which may be software in the form of programs and plug-ins, and includes the following software modules: the client running module 2551, the adaptation testing module 2552, the data obtaining module 2553, the data sending module 2554, the path testing module 2555 and the version obtaining module 2556 are logical, and therefore any combination or further splitting can be performed according to the implemented functions.

Referring to fig. 3, fig. 3 is a schematic diagram of a component structure of a server in fig. 1 according to an embodiment of the present disclosure, where the server 300 shown in fig. 3 includes: at least one second processor 310, a second memory 350, at least one second network interface 320, and a second user interface 330. The various components in the server 300 are coupled together by a second bus system 340. It will be appreciated that the second bus system 340 is used to enable connection communications between these components. The second bus system 340 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as the second bus system 340 in fig. 3.

The second processor 310 may be an integrated circuit chip having signal processing capabilities, such as a general purpose processor, a digital signal processor, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., wherein the general purpose processor may be a microprocessor or any conventional processor, etc.

The second user interface 330 includes one or more second output devices 331, including one or more speakers and/or one or more visual displays, that enable presentation of media content. The second user interface 330 also includes one or more second input devices 332, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

The second memory 350 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid state memory, hard disk drives, optical disk drives, and the like. The second memory 350 optionally includes one or more storage devices physically located remote from the second processor 310.

The second memory 350 includes either volatile memory or nonvolatile memory, and may also include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory and the volatile memory may be a random access memory. The second memory 350 described in embodiments herein is intended to comprise any suitable type of memory.

In some embodiments, the second memory 350 is capable of storing data to support various operations, examples of which include programs, modules, and data structures, or subsets or supersets thereof, as exemplified below.

A second operating system 351 including system programs for processing various basic system services and performing hardware-related tasks, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks;

a second network communication module 352 for communicating to other computing devices via one or more second network interfaces 320, the example second network interfaces 320 including: bluetooth, wireless compatibility authentication, universal serial bus, and the like;

a second presentation module 353 for enabling presentation of information via one or more second output devices 331 associated with the second user interface 330;

a second input processing module 354 for detecting one or more user inputs or interactions from one of the one or more second input devices 332 and translating the detected inputs or interactions.

In some embodiments, the second adaptive testing device provided by the embodiments of the present application may be implemented in software, and fig. 3 illustrates the second adaptive testing device 355 stored in the second memory 350, which may be software in the form of programs and plug-ins, and includes the following software modules: the data receiving module 3551, the dimension determining module 3552, the device clustering module 3553, the class cluster determining module 3554, the device pre-estimating module 3555, the anomaly filtering module 3556, the information updating module 3557, the anomaly playback module 3558, the priority determining module 3559, the processing triggering module 35510, and the information sending module 35511, which are logical and thus may be arbitrarily combined or further split according to the functions implemented.

The functions of the respective modules will be explained below.

In other embodiments, the apparatus provided in the embodiments of the present Application may be implemented in hardware, and for example, the apparatus provided in the embodiments of the present Application may be a processor in the form of a hardware decoding processor, which is programmed to execute the adaptation test method provided in the embodiments of the present Application, for example, the processor in the form of the hardware decoding processor may be one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field Programmable Gate Arrays (FPGAs), or other electronic components.

In the following, the adaptation testing method provided by the embodiment of the present application will be described in conjunction with exemplary applications and implementations of the terminal and the server provided by the embodiment of the present application.

Referring to fig. 4, fig. 4 is an alternative flowchart of a fitting test method provided in an embodiment of the present application, which will be described with reference to the steps shown in fig. 4.

S401, running the adaptive test client by the device to be tested, and displaying a selection control for the client to be tested.

In the embodiment of the application, the adaptive test client is installed on the device to be tested and used for performing adaptive test on the client to be tested and the device to be tested; therefore, the equipment to be tested is also provided with a client to be tested. Here, the installed adaptation test client may be displayed on a screen of the device to be tested, and when the user operates the displayed adaptation test client to operate the adaptation test client, the device to be tested also receives the operation of the user on the adaptation test client; at this time, the device under test also operates the adaptive test client in response to the operation for the adaptive test client. And after the equipment to be tested runs the adaptive test client, displaying the selection control of the client to be tested on the equipment to be tested.

The adaptive test client can load and display each client on the device to be tested after running, and the device to be tested is provided with the client to be tested, so that the device to be tested can display the client to be tested after running the adaptive test client; the adaptive test client is used for performing adaptive test on the running of the client to be tested on the equipment to be tested, so that the equipment to be tested can display a control triggering the running of the client to be tested after running the adaptive test client, namely, the control is selected; the selection control may be a control displayed independently from the client to be tested, or may also be a control corresponding to the client to be tested, which is displayed in a triggerable manner, and this is not specifically limited in this embodiment of the application.

S402, the device to be tested responds to the selection operation acted on the selection control, and displays the running page of the running client to be tested and the testing page of the running adaptive testing client.

In the embodiment of the application, when the user triggers the operation of the client to be tested through the selection control, the equipment to be tested receives the selection operation acted on the selection control; at this time, the equipment to be tested responds to the selection operation, operates the client to be tested, and displays the page of the operated client to be tested, namely the operation page; meanwhile, the running test page of the adaptive test client is displayed in a mode independent of the running page.

It should be noted that the test page is used for displaying the running adaptive test client, and the running page is used for displaying the running client to be tested; moreover, the test page is independent of the running page; for example, the test page is a system window independent of the run page, such as a floating window and a pull-down window.

S403, the device to be tested obtains abnormal data of the running client to be tested and obtains data of the device to be tested through the running adaptive test client.

In the embodiment of the application, the adaptive test client running on the test page is used for monitoring the running client to be tested so as to acquire the abnormal data of the running client to be tested; moreover, the adaptive test client is used for performing adaptive test on the running of the client to be tested on the equipment to be tested, so that the running adaptive test client is also used for acquiring basic information of the equipment to be tested, and data of the equipment to be tested is also acquired.

It should be noted that the abnormal data refers to data that does not satisfy preset operating conditions during the operation of the client to be tested, such as data of flash back, low frame rate, high memory, log error reporting/tracking (trace), and the like; the preset operation condition is, for example, a performance threshold value or other conditions used for determining whether the operation is abnormal, and is, for example, a preset abnormal keyword ("error", "trace", or the like), and a preset abnormal phenomenon (flash back or the like); in addition, the exception data includes one or both of an exception type and an exception description. The data of the device to be tested is basic information of the device to be tested, for example, model data: device model, system version, Open Graphics Library (opengl) version, available memory/total memory, available memory space/total memory space, CPU model and host frequency, GPU (Graphics Processing Unit) version, GPU extension, and model aspect ratio.

S404, the device to be tested sends the adaptive test data carrying the abnormal data and the device to be tested to the server side device.

In the embodiment of the application, after the device to be tested obtains the abnormal data and the data of the device to be tested, the adaptive test client completes the acquisition of the test data, so that the device to be tested carries the abnormal data and the data of the device to be tested in the adaptive test data and sends the adaptive test data to the server side device, so that the server side device determines an adaptive test result including the estimated abnormal device based on the adaptive test data, wherein the estimated abnormal device is a device which is estimated to have an abnormality corresponding to the abnormal data. Here, the adaptation test data includes at least anomaly data and device under test data.

Accordingly, in this embodiment of the application, after S404 is executed, that is, after the device to be tested sends the adaptive test data carrying the abnormal data and the device data to be tested to the server device, the server device also receives the adaptive test data including the abnormal data and the device data to be tested, which is sent by the device to be tested. It is easy to know that the adaptive test data is obtained through an adaptive test client running on the device to be tested, and the abnormal data corresponds to the client running on the device to be tested, that is, the abnormal data is the abnormal data of the moving client to be tested.

S405, the server side equipment determines a clustering dimension based on the equipment information related to the abnormal data.

It should be noted that after the server device obtains the abnormal data, the abnormal data is a defect or a problem occurring in the running process of the client to be tested on the device to be tested, so that the abnormal data is associated with the device to be tested, and the associated device information is the clustering dimension. Here, the clustering dimension includes one or more of device aspect ratio, processor information, memory information, storage space information, GPU information, and system version; the length-width ratio of the device is size information of a display screen of the device, the processor information is related information (for example, a CPU model, a main frequency, and the like) of a processor of the device, the memory information is information corresponding to a memory of the device (for example, a memory size, a total memory size, and the like), the storage space information is information corresponding to a storage space of the device (for example, a memory size, a total storage space size, and the like), the GPU information is information corresponding to a GPU of the device (for example, a GPU version, a GPU extension, and the like), and the system version is information corresponding to an operating system of the device (for example, an operating system type, an operating system version, and the like).

In the embodiment of the application, when the abnormal data includes one or both of the abnormal type and the abnormal description, the associated device information is determined based on one or both of the abnormal type and the abnormal description; for example, when the abnormal data includes an abnormal type, a correspondence relationship between the abnormal type and the device information is set in advance, so that the device information associated with the abnormal data can be determined based on the correspondence relationship between the preset abnormal type and the device information.

Illustratively, when the anomaly type is an interface adaptation problem, the associated device information is a device aspect ratio; when the abnormal type is the problem of blocking (the frame rate is too low), the associated equipment information is processor information, main frequency information and the like; when the abnormal type is a flash back problem, the associated equipment information comprises a memory, a system version and the like; and when the abnormal type is a rendering problem, the associated equipment information is a GPU version, a GPU extension name and the like.

And S406, clustering the data of the equipment to be tested and the preset equipment database by the server equipment according to the clustering dimension to obtain each equipment cluster.

In the embodiment of the application, after the server device obtains the clustering dimension, the server device obtains the device data sent by other pre-received devices to be tested, and then obtains the preset device database. Therefore, the server side equipment combines the data of the equipment to be tested and the preset equipment database, and clusters the combined data according to the clustering dimension, wherein the obtained clustering result is each equipment cluster.

It should be noted that, for a clustering dimension, a difference between each device class cluster is large, and a difference between each device in each device class cluster is small.

S407, the server device determines a related device class cluster corresponding to the device to be tested from each device class cluster.

In the embodiment of the present application, after the server device obtains each device class cluster, the device class cluster to which the device to be tested belongs is determined as the associated device class cluster. It is easy to know that the associated device class cluster includes devices to be tested, and each device in the associated device class cluster is similar in clustering dimension.

S408, the server side equipment obtains the estimated abnormal equipment except the equipment to be tested in the associated equipment cluster, so that an adaptive test result comprising the estimated abnormal equipment is obtained.

It should be noted that, because the devices in the associated device cluster are similar in clustering dimension, and the clustering dimension is the device information associated with the abnormal data, when the client to be tested is operated, the client to be tested which is operated has a higher probability of having the abnormal data besides the device to be tested in the associated device cluster; therefore, the server-side equipment determines the equipment except the equipment to be tested in the associated equipment cluster as the estimated abnormal equipment, and at the moment, the adaptive test result comprising the estimated abnormal equipment is obtained.

The adaptive test client is operated on the equipment to be tested to trigger the operation of the client to be tested, so that the abnormal data of the operating client to be tested is monitored through the operating adaptive test client, the data of the equipment to be tested is acquired and sent to the server side equipment, the server side equipment clusters the equipment based on the abnormal data and the data of the equipment to be tested, and then the estimated abnormal equipment with possible abnormality is predicted; therefore, the obtained adaptive test result has great significance, and the test effect of the adaptive test can be improved.

In this embodiment of the application, the device under test in S403 acquires the abnormal data of the running client under test through the running adaptive test client, which may be implemented through S4031 and S4032, and the following steps are respectively described.

S4031, the device to be tested monitors the running client to be tested through the running adaptive test client, and obtains monitored client running data.

In the embodiment of the application, when the device to be tested monitors the condition of the running client to be tested through the running adaptive test client, the performance data, the output log and the like of the device to be tested when running the device to be tested can be monitored, namely the running data of the client; such as system logs ("logcat" records), application logs, and performance data (CPU usage, frame rate, memory footprint, etc.).

And S4032, when the device to be tested determines that the client operation data is abnormal for the running client to be tested based on the preset operation data, generating abnormal data.

It should be noted that preset operation data is preset in the device to be tested, or the device to be tested can acquire the preset operation data from other devices, where the preset operation data is used to determine whether the monitored client operation data represents that an abnormal client to be tested is present, and corresponds to the preset operation condition; therefore, the preset operation data may be a performance threshold, may also be preset abnormal keywords (for example, errors, exceptions, and the like), may also be implementation steps of the application function, and the like, which is not specifically limited in this embodiment of the present application.

Illustratively, when the device under test detects that the client operating data exceeds a monitoring threshold (frame rate is too low, memory is too high, etc.) or preset abnormal keywords (log has error/trace, etc.) through the operating adaptive test client, the bug is automatically uploaded.

It can be understood that by comparing the monitored client operation data with the preset operation data, the client operation data is automatically reported when the abnormality is determined to exist based on the comparison result, and the intelligence and the coverage rate of the adaptation test are improved.

In this embodiment of the application, the device under test in S403 acquires the abnormal data of the running client under test through the running adaptive test client, which may be implemented through S4033 and S4034, and the following steps are respectively described.

S4033, in the process that the equipment to be tested monitors the running client to be tested through the running adaptive test client, responding to the reporting operation acted on the test page, and displaying an abnormal reporting control.

In the embodiment of the application, the equipment to be tested monitors the running client to be tested through the running adaptive test client, and in the process of monitoring the running client to be tested, when a user triggers abnormal reporting through operation on a test page, the equipment to be tested also receives reporting operation acting on the test page; at this time, the device to be tested responds to the reporting operation and displays an abnormal reporting control.

It should be noted that a control for triggering reporting of an exception, such as an "exception report" button, a "problem report" button, etc., may be displayed on the test page; therefore, when the control for triggering reporting exception is triggered, for example, when the "exception reporting" button is clicked, the device under test receives the reporting operation acting on the test page. The exception reporting control is used for triggering reporting of an exception, and may include one or two of an exception type reporting control and an exception description reporting control, for example; the abnormal type reporting control is used for reporting abnormal types, such as interface adaptation problems, flash back problems, rendering problems, function problems, stuck problems and the like; and the abnormal description reporting control is used for reporting the abnormal description.

S4034, the device to be tested responds to the reporting operation acted on the abnormal reporting control to obtain abnormal data.

In the embodiment of the application, when a user triggers the abnormal reporting control to report abnormal data, the equipment to be tested also receives the reporting operation acted on the abnormal reporting control; at this time, the device to be tested responds to the reporting operation, and obtains the abnormal data reported by the user.

It can be understood that, by displaying the running adaptive test client on the test page independent of the running page, the reporting of the abnormal data can be triggered by responding to the operation on the test page, so that the reporting process of the abnormal data is optimized, and the reporting efficiency of the abnormal data is improved.

Referring to fig. 5, fig. 5 is a schematic flow chart of another alternative adaptation testing method provided in the embodiment of the present application; as shown in fig. 5, in the embodiment of the present application, S409 is further included after S404; that is to say, after the server device receives the adaptive test data including the abnormal data and the device-under-test data sent by the device-under-test, the adaptive test method further includes step S409, which is described below.

And S409, filtering the abnormal data by the server side equipment to obtain the abnormal data to be processed.

It should be noted that, after receiving the abnormal data, the server device filters the abnormal data and then analyzes the abnormal data to establish the association between the abnormality and the device. The abnormal data comprises data corresponding to at least one abnormality, and the filtered abnormal data is to-be-processed abnormal data. In addition, when the server-side device filters the abnormal data, the filtering may include one or more of version filtering, baseline filtering and repeated filtering; the version filtering is to filter abnormal data based on the version information of the client to be detected so as to filter repaired abnormality; the baseline filtering is to filter abnormal data based on the preset lowest operation configuration of the equipment so as to filter the abnormality caused by the lowest operation configuration; the repeated filtering is filtering based on the similarity between the abnormal data and the reported abnormality so as to filter out repeated abnormality.

With continued reference to fig. 5, accordingly, in the embodiment of the present application, S405 may be implemented by S4051; that is, the server device determines the clustering dimension based on the device information associated with the abnormal data, including S4051, which will be described below.

S4051, the server side device determines a clustering dimension based on the device information associated with the abnormal data to be processed.

It should be noted that, after the server device filters the received abnormal data, the associated device information is determined based on the filtered abnormal data, i.e., the abnormal data to be processed, so as to obtain the clustering dimension.

It can be understood that the server device filters the received abnormal data to filter some abnormal data which do not need to be processed, and processes the abnormal data to be processed obtained by filtering, so that the calculation amount of the abnormal data in the adaptation test process is reduced, the resource consumption of the adaptation test can be reduced, and the adaptation test efficiency is improved.

In the embodiment of the present application, S410 is further included after S402; that is, after the device under test displays the running page of the running client under test and the test page of the running adaptive test client in response to the selection operation acting on the selection control, the adaptive test method further includes S410, which is described below.

S410, the device to be tested obtains the client version information of the running client to be tested through the running adaptive test client.

It should be noted that the adaptive test client running on the device to be tested is also used to obtain version information of the running client to be tested, and the obtained version information of the client to be tested is client version information.

Accordingly, in the embodiment of the present application, S404 may be implemented by S4041; that is, the device under test sends the adaptive test data carrying the abnormal data and the device under test to the server device, including S4041, which is described below.

S4041, the device to be tested sends adaptive test data carrying the client version information, the abnormal data and the device to be tested to the server device.

It should be noted that, after the device to be tested obtains the client version information and the abnormal data of the running client to be tested through the running adaptive test client, and obtains the device to be tested data of the device to be tested, the client version information, the abnormal data and the device to be tested data are combined into adaptive test data to be sent to the server device.

Correspondingly, in the embodiment of the application, the adaptation test data received by the server device includes the client version information of the running client to be tested, in addition to the abnormal data and the data of the device to be tested. At this time, S409 can be realized by S4091-S4093; that is, the server device filters the abnormal data to obtain the abnormal data to be processed, which includes S4091 to S4093, and the following describes each step.

S4091, the server side device obtains repaired abnormal data corresponding to the application to be tested.

It should be noted that the application to be tested is a functional application to be tested, and with the continuous improvement of the application to be tested, clients to be tested of different versions can be obtained, and the client to be tested is a client to be tested of one version of the application to be tested; that is, the client to be tested corresponds to the application to be tested. In addition, the repaired exception data is exception data modified for the application to be tested.

And S4092, the server side equipment acquires the repaired client side version information corresponding to the abnormal data from the repaired abnormal data.

In the embodiment of the application, the server device determines target repaired abnormal data corresponding to the abnormal data from the repaired abnormal data, and determines version information of a client corresponding to the target repaired abnormal data as repaired client version information. The target repaired anomaly data may be similar to the anomaly data (greater than a threshold), or may be data with a consistent anomaly type and/or anomaly description, which is not specifically limited in the embodiment of the present application.

It should be noted that, because the exception data corresponds to at least one exception, the server device obtains the version information of the repaired client corresponding to each exception, and combines the version information of at least one repaired client corresponding to at least one exception, so as to obtain the version information of the repaired client.

And S4093, the server side device determines the data with the client version information higher than the repaired client version information in the abnormal data as the abnormal data to be processed.

It should be noted that, for each anomaly in the anomaly data, the server device determines version information of a corresponding repaired client from the repaired client version information, and if the client version information is higher than the repaired client version information, the anomaly in the anomaly data is not filtered; and if the client version information is lower than or equal to the repaired client version information, filtering the exception in the abnormal data, so that the abnormal data to be processed, which is obtained when filtering the exception data, is the data of which the client version information is higher than the repaired client version information in the abnormal data.

Illustratively, for a certain problem (any exception in the exception data), if the 2.0 version has repaired the problem, if the application version reported by the bug is 1.0, the server device will automatically filter out the problem.

In the embodiment of the present application, S409 may also be implemented by S4094 and S4095; that is, the server device filters the abnormal data to obtain the abnormal data to be processed, which includes S4094 and S4095, and the following describes each step.

And S4094, the server side equipment acquires the equipment reference data.

It should be noted that the device reference data is the lowest configuration information of the device running the client to be tested; for example, the model memory is larger than 1G, the system version is larger than a certain version, the mobile phone storage is larger than 8G, and the GPU supports the texture compression format (astc).

And S4095, when the data of the equipment to be tested is higher than or equal to the equipment reference data, the server equipment determines the abnormal data as the abnormal data to be processed.

It should be noted that the server device compares the device data to be tested with the device reference data, and if the device data to be tested is higher than or equal to the device reference data, determines the abnormal data as the abnormal data to be processed; and if the data of the device to be tested is lower than the reference data of the device, filtering the abnormal data, and at the moment, not executing the step S405.

In the embodiment of the present application, S411 to S413 are further included after S404; that is to say, after the server device receives the adaptive test data including the abnormal data and the device-under-test data sent by the device-under-test, the adaptive test method further includes S411 to S413, and the following steps are respectively described.

S411, the server side equipment acquires the abnormal similarity between the abnormal data and preset abnormal data.

In the embodiment of the application, the server device may obtain the abnormal similarity between the abnormal data and the preset abnormal data based on one or more of the abnormal type, the abnormal description, the log information and the path test screenshot. The preset abnormal data is data received before the server-side equipment receives the abnormal data.

And S412, when the abnormal similarity is smaller than the similarity threshold, the server-side equipment adds the abnormal data to preset abnormal data, and adds the equipment data to be tested to a preset equipment database.

It should be noted that the server device compares the abnormal similarity with a similarity threshold, and if the abnormal similarity is smaller than the similarity threshold, it indicates that the abnormal data is not similar to the preset abnormal data; therefore, the server-side equipment adds the abnormal data to the abnormal database corresponding to the preset abnormal data, and adds the equipment data to be tested to the preset equipment database. And the data in the preset abnormal database and the data in the preset equipment database have a corresponding relation.

And S413, when the abnormal similarity is larger than or equal to the similarity threshold, the server-side equipment merges the abnormal data and preset abnormal data, and adds the equipment data to be tested to the equipment information corresponding to the preset abnormal data in the preset equipment database.

It should be noted that the server device compares the abnormal similarity with a similarity threshold, and if the abnormal similarity is greater than or equal to the similarity threshold, it indicates that the abnormal data is similar to the preset abnormal data; therefore, the server-side equipment merges the abnormal data and the preset abnormal data, and adds the equipment data to be tested to the equipment information corresponding to the preset abnormal data in the preset equipment database.

It can be understood that the abnormal data is classified by acquiring the abnormal similarity of the abnormal data and the preset abnormal data, the processing consumption of the abnormal data in the adaptation test process is simplified, and the video test efficiency is improved.

Accordingly, in the embodiment of the present application, S406 may be implemented by 4061; that is, the server device performs clustering on the device data to be tested and the preset device database according to the clustering dimension, including S4061, which is described below.

S4061, the server side device clusters the added preset device database according to the clustering dimension.

It should be noted that the added preset device database includes the device data to be tested and the preset device database; therefore, the server-side equipment clusters the data of the equipment to be tested and the preset equipment database according to the clustering dimension, namely clusters the added preset equipment database according to the clustering dimension.

In the embodiment of the application, S401 can be realized through S4011-S4013; that is, the device under test runs the adaptive test client, displays the selection controls for the client under test, including S4011 to S4013, and the following describes each step separately.

S4011, running the adaptive test client by the device to be tested, and displaying the path test setting control.

It should be noted that the path test setting control is used for triggering the setting process of the path test; for example, the path test setting control includes one or two of a state setting control and a screenshot time setting control, where the state setting control is used to trigger the state opening and closing of the path test, and the screenshot time setting control is used to trigger the setting processing of the screenshot time of the path test.

And S4012, the device to be tested responds to the setting operation acted on the path test setting control and displays the set path test setting information.

In the embodiment of the application, when a user sets the path test by triggering the path test setting control, the device to be tested also receives the setting operation acted on the path test setting control; at this time, the device under test also obtains the set path test setting information in response to the setting operation. Here, the path test setting information includes one or both of an open state and a screenshot trigger condition; wherein, the starting state refers to whether the path test is started or not; the screenshot triggering condition is a condition for performing screenshot on the path test, and may be time, an event, or the like, which is not specifically limited in this embodiment of the present application.

And S4013, the device to be tested responds to the test trigger operation aiming at the path test setting information, and displays a selection control aiming at the client to be tested.

It should be noted that, when the user completes the setting of the path test and performs the adaptive test on the to-be-tested client according to the set path test setting information, for example, when the "adaptive test" button is clicked, the to-be-tested device also receives the test trigger operation according to the path test setting information; at this time, the device to be tested responds to the test trigger operation, and displays a selection control for the client to be tested.

Correspondingly, in the embodiment of the present application, S414 is further included after S402; that is, after the device under test displays the running page of the running client under test and the test page of the running adaptive test client in response to the selection operation acting on the selection control, the adaptive test method further includes S414, which is described below.

And S414, the device to be tested performs screenshot on the running page based on the path test setting information and through the running adaptive test client, and obtains the path test data of the running client to be tested.

It should be noted that, when the starting state in the path test setting information is starting, the device to be tested performs screenshot on the running page through the running adaptive test client based on the screenshot triggering condition in the path test setting information, and the obtained screenshot of the path test is the path test data of the running client to be tested.

S4041, the device to be tested sends adaptive test data carrying the path test data, the abnormal data and the device to be tested to the server side device.

It should be noted that after the device to be tested obtains the path test data, the adaptation test data of the path test data, the abnormal data and the device to be tested is combined into the adaptation test data, and the adaptation test data carrying the path test data, the abnormal data and the device to be tested is sent to the server device.

Correspondingly, in the embodiment of the application, the adaptive test data sent by the device to be tested to the server device includes path test data, abnormal data and device to be tested data; therefore, the adaptation test data received by the server device includes path test data in addition to the abnormal data and the device-to-be-tested data. Thus, S415 and S416 are also included after S411; that is to say, after the server device obtains the abnormal similarity between the abnormal data and the preset abnormal data, the adaptation test method further includes S415 and S416, which are described below.

And S415, when the abnormal similarity is smaller than the similarity threshold value, the server equipment generates a client abnormal video based on the path test data.

It should be noted that when the abnormal similarity is smaller than the similarity threshold, the server device generates the client abnormal video based on the path test data, so as to reproduce the abnormality through the client abnormal video.

And S416, the server side equipment plays the abnormal video of the client side.

It should be noted that after the server device obtains the client abnormal video, the server device may play the client abnormal video on the server device, so as to reproduce the abnormality by playing the client abnormal video.

It can be understood that the abnormal reproduction can be realized by generating the path test data into the client abnormal video and playing the client abnormal video, so that the abnormal positioning speed is improved.

Referring to fig. 6, fig. 6 is a schematic flow chart of yet another alternative adaptation testing method provided in the embodiment of the present application; as shown in fig. 6, in the embodiment of the present application, S408 is followed by S417 and S418; that is to say, after the server device obtains the adaptation test result including the estimated abnormal device, the adaptation test method further includes S417 and S418, and the following steps are respectively described.

S417, the server side equipment obtains the use coverage rate of the estimated abnormal equipment.

It should be noted that, an equipment use coverage information base is preset in the server device, or the server device can obtain the equipment use coverage information base; the device use coverage information base includes use coverage conditions corresponding to each device, such as market coverage; therefore, the server-side equipment can obtain the estimated use coverage condition of the abnormal equipment, and the use coverage rate is obtained.

S418, the server side equipment determines the correction priority of the abnormal data based on the use coverage rate, and corrects the abnormality corresponding to the abnormal data based on the correction priority.

It should be noted that after the server device obtains the coverage rate of the predicted abnormal device, the predicted abnormal device is a device with an abnormality corresponding to the predicted abnormal data; therefore, the priority of correction of abnormal data, i.e., the correction priority, is positively correlated with the usage coverage. Here, the server device may correct the abnormality corresponding to the abnormal data based on the correction priority.

It can be understood that the use coverage rate of the abnormal equipment is estimated through statistics, so that the correction priority of the abnormal data is determined based on the influence range of the preset abnormal equipment, and the processing efficiency and accuracy of the abnormal data in the adaptive test process are improved.

In the embodiment of the present application, after S404 and before S405, S419 and S420 are further included; that is to say, after the server device receives the adaptation test data including the abnormal data and the data of the device to be tested, which is sent by the device to be tested, and before the server device determines the clustering dimension based on the device information associated with the abnormal data, the adaptation test method further includes S419 and S420, which are described below.

And S419, displaying the abnormal data by the server side equipment.

It should be noted that after the server device obtains the abnormal data, the abnormal data may also be displayed, so as to process the abnormal data according to the displayed abnormal data.

And S420, the server side equipment receives processing operation aiming at the abnormal data.

It should be noted that, when the user processes the displayed abnormal data, the server device also receives a processing operation for the abnormal data. The processing operation includes one or more of an ignoring operation, a device associating operation and a correction request operation, the ignoring operation is an operation that does not process the abnormal data, the device associating operation is an operation that establishes association between the abnormality and the device based on the abnormal data, and the correction request operation is an operation that requests correction of the abnormal data (for example, an operation of providing a bug list).

In this embodiment of the present application, when the processing operation includes a device association operation, S405 may also be implemented by S4052; that is, the server device determines the clustering dimension based on the device information associated with the abnormal data, including S4052, which is explained below.

S4052, the server-side device responds to the device association operation, and based on the device information associated with the abnormal data, the clustering dimension is determined.

That is, the server device determines the clustering dimension based on the device information associated with the abnormal data, and the server device is triggered in response to the device association operation.

In the embodiment of the present application, S421 and S422 are also included after S408; that is to say, after the server device obtains the adaptation test result including the estimated abnormal device, the adaptation test method further includes S421 and S422, which are described below.

S421, the server side equipment acquires the sending object.

It should be noted that the server device is provided with the transmission object in advance, or the server device can acquire the transmission object from another device. Wherein the sending object is a sending target adapted to the test result.

And S421, the server side equipment sends the reminding information carrying the estimated abnormal equipment to the sending object.

It should be noted that after the server device obtains the sending object and the abnormal pre-estimation device, the server device sends a reminding message carrying the abnormal pre-estimation device to the sending object, so that the sending object obtains the abnormal pre-estimation device.

Next, an exemplary application of the embodiment of the present application in a practical application scenario will be described.

Referring to fig. 7, fig. 7 is a schematic flowchart illustrating an exemplary adaptive testing method applied to a device under test according to an embodiment of the present disclosure; referring to fig. 7, the exemplary adaptation test method applied to the device under test includes:

s701, running a device client (adaptive test client) on the mobile phone (to-be-tested equipment), and displaying an application list.

S702, selecting a test application (a client to be tested) from the application list to run.

Referring to fig. 8, fig. 8 is a schematic diagram illustrating an exemplary running client to be tested according to an embodiment of the present application; as shown in fig. 8, the device client is run on the mobile phone, displaying page 8-1; the page 8-1 is a page corresponding to the application list, and displays all applications installed on the mobile phone, because the adaptive test is performed on the running of the test application 8-11 on the mobile phone, all applications displayed in the page 8-1 include the test application 8-11 (here, the test application 8-11 displayed in the page 8-1 is a selection control of the client to be tested in this embodiment of the present application). When the displayed test application 8-11 is clicked, the "start test" and the "uninstall application" are displayed, and when the "start test" is clicked (here, the operation of clicking the displayed test application 8-11 and clicking the "start test" is a selection operation in the embodiment of the present application), the test application 8-11 is executed.

It should be noted that, after the test application 8-11 clicks "start test", the running device client displays the device client in a floating window (test page) manner, and then starts the test application 8-11.

And S703, monitoring the running test application by the device client, and regularly capturing the screen. S704 or S706 is performed.

It should be noted that the device client monitors the test application, including log output (logcat record and application log) and performance data (memory occupation, frame rate, etc.), and regularly performs screenshot storage on the screen (running page) of the test application running on the mobile phone.

S704, based on the monitored data (client operation data), determines whether there is an abnormality. If yes, executing S705; if not, S703 is performed.

It should be noted that the exception is a flash back, a frame rate is too low, a memory is too high, or an error/trace in log output is monitored.

S705, generating a reporting bug (abnormal data) comprising a bug type (abnormal type) and a bug description (abnormal description) based on the monitored data.

And S706, responding to the active reporting operation (reporting operation) acted on the floating window, and acquiring the selected exception type and the filled exception description.

And S707, acquiring model data (data of the equipment to be tested) and the version (client version information) of the test application.

Referring to fig. 9, fig. 9 is a schematic page diagram of exemplary data of a device under test provided in an embodiment of the present application; as shown in fig. 9, the model data 9-11 displayed on the page 9-1 includes a mobile phone model, a manufacturer, an android version, an opengl version, an available memory/total memory, an available storage space/total storage space, a CPU model, master frequency information, GPU information, and the like.

S708, reporting the obtained screenshot (path test information), the monitored data, the reported bug, the model data, and the version of the test application to a device server (server device). S703 is executed or S709 is executed.

Here, the obtained screenshot (path test information), the monitored data, the reported bug, the model data, and the version of the test application, that is, the adaptation test data in the embodiment of the present application.

And S709, closing the device client.

It should be noted that, after the mobile phone executes S708, the corresponding processing flow of the device server refers to fig. 10, and fig. 10 is a schematic flow diagram of an exemplary adaptation testing method applied to a server device according to an embodiment of the present application; as shown in fig. 10, the exemplary adaptation testing method applied to the server device includes:

s1001, receiving screenshots, monitoring data, reporting bugs, model data and testing application versions.

S1002, filtering the reported bug based on the version and model data of the test application.

S1003, obtaining the bug similarity (abnormal similarity) between the filtered reported bug and the existing bug (preset abnormal data).

It should be noted that the filtered reported bug is compared with the existing bug (preset abnormal data), and the comparison mode includes bug type, bug description, trace and screenshot.

S1004, judging whether the bug similarity exceeds a threshold (similarity threshold); if so, S1005 is performed, otherwise, S1006 or S1011 is performed.

And S1005, combining the filtered reported bug and the existing bug, and supplementing the model of the existing bug based on the model data. S1007 is executed.

Here, the model of the existing bug is supplemented based on the model data, that is, the model data is supplemented to the device information base.

And S1006, newly adding the filtered reported bug to the existing bug, and newly adding the model data to an equipment information base (a preset equipment database). S1007 is executed.

S1007, determining the model dimension (clustering dimension) based on the filtered bug type of the reported bug. The model dimensions include length-width ratio, CPU, GPU, memory, storage space and the like.

And S1008, clustering the new equipment information base (the added preset equipment database) according to the model dimension.

Here, the new device information library is the device information library after the execution of S1005 or S1006.

S1009, estimating the related devices which may have the filtered reported bug based on the clustering result.

And S1010, determining the priority of the filtered reported bug based on the model display coverage rate (using coverage rate) of the associated equipment.

S1011, a sequence frame video (client-side abnormal video) is generated based on the screenshot.

It can be understood that, in a scenario of performing multi-model adaptation test on an application to be tested in a centralized manner, by using the adaptation test method provided by the embodiment of the application, on one hand, a bug can be reported only by selecting a bug type and filling in a bug description, so that a bug reporting flow is optimized. On the other hand, when the device client detects that the application to be tested is flashed off, the frame rate is too low, the memory is too high, and the log has error/trace, the bug is automatically reported, so that omission of a part of tested bugs can be avoided, the reported bugs are comprehensive, and the adaptive test effect is improved. On the other hand, many bug problems can occur repeatedly, and by filtering and combining the bugs, the resource consumption of bug processing is reduced, and the bug processing efficiency is improved; and the bug reproduces the sequential frame video, the log of the application, the logcat record, the model data and the version of the test application, and can realize problem location and bug reproduction. On the other hand, the problem machine type prediction function and the bug priority determination function are also realized.

Continuing with the exemplary structure of the first adaptive testing device 255 implemented as a software module provided in the embodiments of the present application, in some embodiments, as shown in fig. 2, the software module stored in the first adaptive testing device 255 of the first memory 250 may include:

a client running module 2551, configured to run the adaptive test client and display a selection control for the client to be tested;

an adaptive test module 2552, configured to display, in response to a selection operation acting on the selection control, a running page of the running client to be tested and a test page of the running adaptive test client, where the test page is independent of the running page;

a data obtaining module 2553, configured to obtain, through the running adaptive test client, abnormal data of the running client to be tested and obtain data of the device to be tested;

a data sending module 2554, configured to send adaptation test data carrying the abnormal data and the data of the device to be tested to the server device, so that the server device determines, based on the adaptation test data, an adaptation test result including pre-estimated abnormal devices.

In this embodiment of the application, the data obtaining module 2553 is further configured to monitor the running client to be tested through the running adaptive test client, and obtain monitored client running data; and when the client to be tested, which determines that the client running data is running, is abnormal based on preset running data, generating the abnormal data.

In this embodiment of the application, the data obtaining module 2553 is further configured to, in a process of monitoring the running client to be tested by the running adaptive test client, respond to a reporting operation acting on the test page, and display an abnormal reporting control; and responding to the reporting operation acted on the abnormal reporting control to obtain the abnormal data.

In this embodiment of the present application, the client running module 2551 is further configured to run the adaptive test client and display a path test setting control, where the path test setting control is used to trigger a setting process of a path test; responding to the setting operation acted on the path test setting control, and displaying set path test setting information; and responding to the test trigger operation aiming at the path test setting information, and displaying the selection control aiming at the client to be tested.

In this embodiment of the application, the first adaptive testing device 255 further includes a path testing module 2555, configured to set information based on the path test, and perform screenshot on the running page through the running adaptive testing client, so as to obtain running path testing data of the client to be tested.

In this embodiment of the application, the data sending module 2554 is further configured to send the adaptation test data carrying the path test data, the abnormal data, and the data of the device under test to the server device.

In this embodiment of the application, the first adaptive testing device 255 further includes a version obtaining module 2556, configured to obtain, through the running adaptive testing client, client version information of the running client to be tested.

In this embodiment of the application, the data sending module 2554 is further configured to send the adaptation test data, which carries the client version information, the abnormal data, and the data of the device under test, to the server device.

Embodiments of the present application provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The first processor of the computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, so that the computer device executes the adaptation test method applied to the device to be tested in the embodiment of the present application.

Continuing with the exemplary structure of the second adaptive testing device 355 implemented as a software module provided in the embodiments of the present application, in some embodiments, as shown in fig. 3, the software module stored in the second adaptive testing device 355 of the second memory 350 may include:

the data receiving module 3551 is configured to receive adaptation test data which is sent by a device to be tested and includes abnormal data and device to be tested data, where the adaptation test data is acquired through an adaptation test client running on the device to be tested, and the abnormal data corresponds to the client running on the device to be tested;

a dimension determining module 3552, configured to determine a clustering dimension based on the device information associated with the abnormal data;

the device clustering module 3553 is configured to cluster the device data to be tested and a preset device database according to the clustering dimension to obtain each device class cluster;

a class cluster determining module 3554, configured to determine, from the device class clusters, a related device class cluster corresponding to the device to be tested;

an equipment estimation module 3555, configured to obtain estimated abnormal equipment in the associated equipment cluster except the equipment to be tested, so as to obtain an adaptation test result including the estimated abnormal equipment, where the estimated abnormal equipment is estimated to have an abnormality corresponding to the abnormal data.

In this embodiment of the application, the second adaptive testing device 355 further includes an exception filtering module 3556, configured to filter the exception data to obtain exception data to be processed.

In this embodiment of the application, the dimension determining module 3552 is further configured to determine the clustering dimension based on the device information associated with the to-be-processed abnormal data.

In the embodiment of the present application, the adaptive test data further includes client version information of the running client to be tested; the anomaly filtering module 3556 is further configured to obtain repaired anomaly data corresponding to an application to be tested, where the client to be tested corresponds to the application to be tested; acquiring repaired client version information corresponding to the abnormal data from the repaired abnormal data; and in the abnormal data, determining the data with the client version information higher than the repaired client version information as the abnormal data to be processed.

In this embodiment of the application, the anomaly filtering module 3556 is further configured to obtain device reference data, where the device reference data is the lowest configuration information of a device running the client to be tested; and when the data of the equipment to be tested is higher than or equal to the reference data of the equipment, determining the abnormal data as the abnormal data to be processed.

In this embodiment of the application, the second adaptive testing device 355 further includes an information updating module 3557, configured to obtain an abnormal similarity between the abnormal data and preset abnormal data; when the abnormal similarity is smaller than a similarity threshold value, adding the abnormal data into the preset abnormal data, and adding the data of the equipment to be tested into the preset equipment database; and when the abnormal similarity is larger than or equal to the similarity threshold, merging the abnormal data and the preset abnormal data, and adding the data of the equipment to be tested to the equipment information corresponding to the preset abnormal data in the preset equipment database.

In this embodiment of the application, the device clustering module 3553 is further configured to cluster the added preset device database according to the clustering dimension.

In an embodiment of the present application, the adaptation test data further includes path test data; the second adaptation test device 355 further includes an anomaly playback module 3558 configured to generate a client anomaly video based on the path test data when the anomaly similarity is less than the similarity threshold; and playing the abnormal video of the client.

In this embodiment of the present application, the second adaptive testing device 355 further includes a priority determining module 3559, configured to obtain a coverage rate of the use of the pre-estimated abnormal device; and determining the processing priority of the abnormal data based on the use coverage rate, so as to correct the abnormality corresponding to the abnormal data based on the processing priority.

In the embodiment of the present application, the second adaptive testing device 355 further includes a processing triggering module 35510, configured to display the abnormal data; receiving a processing operation for the exception data, wherein the processing operation comprises one or more of an ignore operation, a device association operation, and a fix-up request operation.

In this embodiment, the dimension determining module 3552 is further configured to determine the clustering dimension based on the device information associated with the abnormal data in response to the device association operation.

In the embodiment of the present application, the second adaptive testing device 355 further includes an information sending module 35511, configured to obtain a sending object; and sending reminding information carrying the estimated abnormal equipment to the sending object.

Embodiments of the present application provide 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 executes the computer instructions, so that the computer device executes the adaptation testing method applied to the server device according to the embodiment of the present application.

The embodiment of the application provides a computer-readable storage medium storing executable instructions, wherein the executable instructions are stored, and when being executed by a first processor, the executable instructions cause the first processor to execute the adaptation test method applied to the device to be tested, provided by the embodiment of the application; or, when the executable instructions are executed by the second processor, the second processor is caused to execute the adaptation testing method applied to the server device provided by the embodiment of the application; for example, the adaptation test method as shown in fig. 4.

In some embodiments, the computer-readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash, magnetic surface memory, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories.

In some embodiments, executable instructions may be written in any form of programming language (including compiled or interpreted languages), in the form of programs, software modules, scripts or code, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

By way of example, executable instructions may correspond, but do not necessarily have to correspond, to files in a file system, and may be stored in a portion of a file that holds other programs or data, such as in one or more scripts in a hypertext Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code).

By way of example, executable instructions may be deployed to be executed on one computing device or on multiple computing devices at one site or distributed across multiple sites and interconnected by a communication network.

In summary, the adaptive test client is operated on the device to be tested to trigger the operation of the client to be tested, so that the operating adaptive test client monitors abnormal data of the operating client to be tested and acquires data of the device to be tested to send the data to the server device, the server device clusters the devices based on the abnormal data and the data of the device to be tested, and then pre-estimated abnormal devices with possible abnormalities are predicted; therefore, the obtained adaptive test result has great significance, and the test effect of the adaptive test can be improved. In addition, the adaptation test method provided by the embodiment of the application can also quickly determine the abnormal repair priority, realize abnormal reappearance and abnormal filtering, quickly locate the abnormality, reduce the resource consumption of the adaptation test and improve the efficiency of the adaptation test.

The above description is only an example of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, and improvement made within the spirit and scope of the present application are included in the protection scope of the present application.

Claims

1. An adaptation test method, comprising:

2. The method according to claim 1, wherein the obtaining, by the running adaptive test client, the abnormal data of the running client to be tested comprises:

monitoring the running client to be tested through the running adaptive test client to obtain monitored client running data;

and when the client to be tested, which determines that the client running data is running, is abnormal based on preset running data, generating the abnormal data.

3. The method according to claim 1, wherein the obtaining, by the running adaptive test client, the abnormal data of the running client to be tested comprises:

responding to the reporting operation acted on the test page in the process of monitoring the running client to be tested by the running adaptive test client, and displaying an abnormal reporting control;

and responding to the reporting operation acted on the abnormal reporting control to obtain the abnormal data.

4. The method of any one of claims 1 to 3, wherein the running of the adaptive test client that displays the selection control for the client under test comprises:

running the adaptive test client and displaying a path test setting control, wherein the path test setting control is used for triggering the setting processing of the path test;

responding to the setting operation acted on the path test setting control, and displaying set path test setting information;

responding to the test trigger operation aiming at the path test setting information, and displaying the selection control aiming at the client to be tested;

after the running page of the running client to be tested and the test page of the running adaptive test client are displayed in response to the selection operation acted on the selection control, the method further comprises the following steps:

based on the path test setting information, the running page is subjected to screenshot through the running adaptive test client, and path test data of the running client to be tested are obtained;

the sending of the adaptation test data carrying the abnormal data and the data of the device to be tested to the server side device includes:

and sending the adaptive test data carrying the path test data, the abnormal data and the data of the equipment to be tested to the server side equipment.

5. The method according to any one of claims 1 to 3, wherein after displaying the running page of the running client under test and the test page of the running adaptive test client in response to the selection operation acting on the selection control, the method further comprises:

acquiring client version information of the running client to be tested through the running adaptive test client;

and sending the adaptive test data carrying the client version information, the abnormal data and the data of the equipment to be tested to the server equipment.

6. An adaptation test method, comprising:

7. The method of claim 6, wherein after receiving the adapted test data including the anomaly data and the device under test data sent by the device under test, the method further comprises:

filtering the abnormal data to obtain abnormal data to be processed;

determining a clustering dimension based on the device information associated with the abnormal data, including:

and determining the clustering dimension based on the equipment information associated with the abnormal data to be processed.

8. The method of claim 7, wherein the adaptation test data further comprises client version information of the running client under test;

the filtering the abnormal data to obtain the abnormal data to be processed includes:

acquiring repaired abnormal data corresponding to an application to be tested, wherein the client to be tested corresponds to the application to be tested;

acquiring repaired client version information corresponding to the abnormal data from the repaired abnormal data;

and in the abnormal data, determining the data with the client version information higher than the repaired client version information as the abnormal data to be processed.

9. The method according to claim 7, wherein the filtering the abnormal data to obtain the abnormal data to be processed comprises:

acquiring equipment reference data, wherein the equipment reference data is the lowest configuration information of equipment operating the client to be tested;

and when the data of the equipment to be tested is higher than or equal to the reference data of the equipment, determining the abnormal data as the abnormal data to be processed.

10. The method according to any one of claims 6 to 9, wherein after receiving the adapted test data including the abnormal data and the device under test data sent by the device under test, the method further comprises:

acquiring abnormal similarity between the abnormal data and preset abnormal data;

when the abnormal similarity is smaller than a similarity threshold value, adding the abnormal data into the preset abnormal data, and adding the data of the equipment to be tested into the preset equipment database;

when the abnormal similarity is larger than or equal to the similarity threshold, combining the abnormal data with the preset abnormal data, and adding the equipment data to be tested to the equipment information corresponding to the preset abnormal data in the preset equipment database;

the clustering the to-be-tested equipment data and the preset equipment database according to the clustering dimension comprises the following steps:

and clustering the added preset equipment database according to the clustering dimension.

11. The method of claim 10, wherein the adaptation test data further comprises path test data;

after the obtaining of the abnormal similarity between the abnormal data and the preset abnormal data, the method further includes:

when the abnormal similarity is smaller than the similarity threshold value, generating a client abnormal video based on the path test data;

and playing the abnormal video of the client.

12. The method according to any one of claims 6 to 9, wherein after obtaining the fitting test result including the pre-estimated abnormal device, the method further comprises:

acquiring the use coverage rate of the estimated abnormal equipment;

and determining the processing priority of the abnormal data based on the use coverage rate, so as to correct the abnormality corresponding to the abnormal data based on the processing priority.

13. A device under test for adaptive testing, comprising:

a first memory for storing executable instructions;

a first processor for implementing the method of any one of claims 1 to 5 when executing executable instructions stored in the first memory.

14. A server-side device for adaptation testing, comprising:

a second memory for storing executable instructions;

a second processor, adapted to perform the method of any of claims 6 to 12 when executing the executable instructions stored in the second memory.

15. A computer-readable storage medium having stored thereon executable instructions for, when executed by a first processor, implementing the method of any one of claims 1 to 5; or for implementing the method of any of claims 6 to 12 when executed by a second processor.