CN116340174A

CN116340174A - Graphic page testing method, training method and device

Info

Publication number: CN116340174A
Application number: CN202310325369.9A
Authority: CN
Inventors: 张哲�; 牛伟嘉; 吴志刚
Original assignee: China Citic Bank Corp Ltd
Current assignee: China Citic Bank Corp Ltd
Priority date: 2023-03-29
Filing date: 2023-03-29
Publication date: 2023-06-27

Abstract

The disclosure provides a graphic page testing method, a graphic page training method and a graphic page testing device, and relates to the technical field of computers. The specific implementation scheme is as follows: determining and accessing a tested page based on preset configuration data; acquiring current page information of a tested page, and matching the page operation matched with the page information through a graphic page test model; executing the page operation to test the tested page and obtaining a corresponding test result; and generating and storing a test case according to the test result.

Description

Graphic page testing method, training method and device

Technical Field

The disclosure relates to the field of computer technology, and in particular, to a method for testing a graphic page, a training method and a training device.

Background

At present, the function of the graphic page is tested by adopting manual work, a tester opens each tested page, then tests the function of the page element in the page, and records the test process.

Disclosure of Invention

The disclosure provides a graphic page testing method, a training method and a training device.

According to a first aspect of the present disclosure, there is provided a graphic page testing method, including:

determining and accessing a tested page based on preset configuration data;

acquiring current page information of a tested page, and matching the page operation matched with the page information through a graphic page test model;

executing the page operation to test the tested page and obtaining a corresponding test result;

and generating and storing a test case according to the test result.

According to a second aspect of the present disclosure, there is provided a training method of a graphic page test model, including:

acquiring historical test cases in the training data set, and executing the historical test cases to perform test training;

recording the test process of the historical test cases aiming at each historical test case, and generating and storing a pre-test result corresponding to each test process;

and acquiring verification data in the verification data set, verifying the pre-test result, if the verification is passed, generating a new test case according to the pre-test result, and storing the new test case in the training data set.

According to a third aspect of the present disclosure, there is provided a graphic page testing apparatus comprising:

the determining module is used for determining and accessing the tested page based on preset configuration data;

the acquisition module is used for acquiring current page information of the tested page and matching the page operation matched with the page information through the graphic page test model;

the execution module is used for executing the page operation to test the tested page and obtaining a corresponding test result;

and the storage module is used for generating and storing the test cases according to the test results.

According to a fourth aspect of the present disclosure, there is provided a training apparatus of a graphic page test model, including:

the acquisition module is used for acquiring historical test cases in the training data set and executing the historical test cases to carry out test training;

the generating module is used for recording the testing process of the historical testing cases aiming at each historical testing case, and generating and storing a pre-testing result corresponding to each testing process;

and the storage module is used for acquiring verification data in the verification data set, verifying the pre-test result, generating a new test case according to the pre-test result if the verification is passed, and storing the new test case into the training data set.

According to a fifth aspect of the present disclosure, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of responding as described in the claims.

According to a sixth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the answering method according to the above claims.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a method for testing a graphic page according to an embodiment of the present disclosure;

FIG. 2 is a flow chart of a training method of a graphic page test model according to an embodiment of the disclosure;

FIG. 3 is a schematic diagram of a graphic page testing apparatus according to an embodiment of the present disclosure;

FIG. 4 is a schematic structural diagram of a training device for a graphic page test model according to an embodiment of the present disclosure;

fig. 5 is a block diagram of an electronic device used to implement an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In some related technologies, the function test of the graphic page is mostly performed manually, which has low efficiency and wastes a lot of manpower.

The embodiment of the disclosure provides a graphic page testing method, a training method and a device, which aim to solve at least one of the technical problems in the prior art.

The response method provided by the embodiment of the present disclosure may be performed by an electronic device such as a terminal device or a server, where the terminal device may be a vehicle-mounted device, a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor invoking computer readable program instructions stored in a memory. Alternatively, the method may be performed by a server.

Fig. 1 shows a flowchart of a graphics page testing method provided by an embodiment of the disclosure, where, as shown in fig. 1, the method may mainly include:

in step S110, a tested page is determined and accessed based on preset configuration data.

Wherein, the configuration data required by the test can be configured before the test is started, and specifically, the configuration data can include at least one of the following: the access address of the tested page, the user name of the tested page and the password corresponding to the user name. Then in this case S110 comprises a number of sub-steps:

and step one, acquiring a tested page access address contained in the configuration data, and accessing the tested page according to the tested page access address.

And secondly, logging in the tested page through the user name of the tested page and the password corresponding to the user name contained in the configuration data.

Specifically, the user name and the password are the user name and the password of the account number required by the webpage or the system corresponding to the tested page.

In step S120, current page information of the tested page is obtained, and the page operation matched with the page information is matched through the graphic page test model.

The graphic page test model is a model for testing the graphic page function of the tested page in this embodiment, and the model has a capability of cloning a certain behavior through pre-training, which is described in detail in the model training section later.

In this case, S120 specifically includes: and determining page elements contained in the tested page and page states of the tested page.

Wherein the page information includes all information describing the page, e.g., the page information includes one of the following indications: the page elements contained in the tested page and the page state of the tested page. Wherein the page element comprises at least one of a graphic element (such as an input box, a determination button, a selection box, a drop-down box) and a text element, and the page state comprises at least one of the following: input state, activation state, privacy browsing state, etc. In the training stage, a plurality of test cases are used as input and input graphic page test models to train, in the training process, page elements contained in a tested page in each test case are determined, the page state of the tested page and the relationship of page operations corresponding to the page elements and the page states are stored as test results, in the testing stage, when at least one of the page elements and the page states is determined, the page operations matched with the at least one of the page elements and the page states are determined through the models, and then the page operations are executed. By the method, repeated tests can be reduced, the model has a certain behavior cloning capability, and page operations executed for different tested pages can be decided, so that the graphic pages can be automatically tested.

In some manners, the tested page includes a plurality of associated tested pages, and S120 specifically includes: and sequentially determining page elements and page states contained in each tested page, and matching page operations corresponding to each tested page.

In step S130, a page operation is performed to test the tested page, and a corresponding test result is obtained.

Specifically, a page operation is executed for at least one page element, an execution result obtained after the page operation is executed is obtained, and meanwhile, associated information after the page operation is executed is recorded, wherein the associated information comprises at least one of the following: the method comprises the steps of page elements aimed at by page operation (namely operation targets of the page operation), execution time of the page operation, associated pages associated with the execution of the page operation, system resources used for executing the page operation, screenshot of a tested page and partial screenshot of the page elements aimed at by the page operation. According to the above, the execution result and the associated information are stored as the test result.

In some implementations, the page under test includes a plurality of associated pages under test. Step S130 includes a plurality of sub-steps:

and step one, executing page operation corresponding to each tested page, and obtaining a subtest result corresponding to each tested page.

In S120, a page operation corresponding to each tested page is matched, and then negative operations of each tested page are sequentially executed, so as to obtain a sub-test result of the tested page, where, in the same way as above, the sub-test result of one tested page includes: and the execution result of the page operation of the tested page and the associated information after the page operation is executed.

And step two, generating access paths of all the tested pages according to the time sequence of executing the page operation.

According to the time sequence of executing page operation of each tested page, recording the association relation of each tested page, and generating an access path according to the association relation and access time. For example, in the test, if the page operation is performed on the tested page a to jump to the tested page B, the access path is the tested page a-the tested page B.

And thirdly, generating a serialized test result according to the access path and the sub test result corresponding to each tested page.

According to the access path, each sub-test result is stored as a visualized and serialized test result according to the time sequence, namely, each sub-test result is stored as visualized graphic information in a time sequence mode.

In step S140, a test case is generated and saved according to the test result.

Generating a test case of the tested page according to the generated test, and storing the access path and the test result, wherein the test case further comprises an association relation between page information (including page elements and page states) and page operation, and the test case further comprises at least one of the following steps: the path length of the access path, the number of pages of the tested page covered by the case, and the number of elements of the page elements involved in the test. In the embodiment of the present disclosure, the test cases may be stored in a case database, which may be provided in a separate server or in an apparatus stored in a graphic page test model used in the embodiment of the present disclosure, which is not limited herein, and may also include online cases. During the training phase, cases may be acquired from a training dataset in a case database for training.

In other words, in the graphic page testing method provided by the embodiment of the disclosure, the tested page is automatically tested through the graphic page testing model, so that the page information of the tested page can be identified, and corresponding page operation is matched, namely, the next strategy is selected through the graphic page testing model, the tested page is automatically operated, and the automation of the graphic page function test in the tested page is realized, so that the efficiency of the graphic page test can be effectively improved, and the repeated test is avoided through the identification of the page information, and the system resource can be saved.

Fig. 2 is a flow chart illustrating a training method of a graphic page test model according to an embodiment of the disclosure, where, as shown in fig. 2, the method may mainly include:

in step S210, historical test cases in the training data set are acquired, and the historical test cases are executed for test training.

In an embodiment of the disclosure, a case database may be included, where the case database includes a training dataset and a verification dataset, the training dataset includes a plurality of test cases, and during a training phase, the test cases in the training dataset may be read for model training; the verification data set comprises test results of a plurality of test cases, and after the test results are obtained in the training stage, the validity of the model training can be verified by using the test results in the verification data set. The case database may be set in a separate server, or may be set in a device stored in a graphic page test model used in the embodiment of the present disclosure, which is not limited herein, and the case database stores test cases generated by the method provided in the embodiment of the present disclosure, or may include online cases.

In S210, executing the historical test case to perform the test training specifically includes: determining page elements contained in the tested page and the page state of the tested page; determining a page operation to be executed, and determining a target page element (namely an operation target) corresponding to the page operation; and executing the page operation to obtain a pre-test result corresponding to the page operation.

In step S220, for each historical test case, the test process of the historical test case is recorded, and the pre-test result corresponding to each test process is generated and stored.

In the training stage, each test process and the corresponding pre-test result of the test process are recorded through a recording function.

In some examples, S220 includes a plurality of sub-steps:

and step one, acquiring page elements contained in the tested page, the page state of the tested page and corresponding page operation in the test process.

And step two, generating a pre-test result according to the association relation among the page elements, the page states and the page operation.

Wherein, the page element comprises at least one of graphic elements (such as an input box, a determination button, a selection box and a drop-down box) and text elements, and the page state comprises at least one of the following: input state, activation state, privacy browsing state, etc. In the testing process, determining page elements aimed at by each page operation, executing the page operation to obtain an execution result, and recording associated information of the page operation, wherein the associated information comprises at least one of the following steps: the method comprises the steps of page elements aimed at by page operation (namely operation targets of the page operation), execution time of the page operation, associated pages associated with the execution of the page operation, system resources used for executing the page operation, screenshot of a tested page and partial screenshot of the page elements aimed at by the page operation. And according to the above, storing the execution result and the associated information as a pre-test result of the training.

The method provided in the embodiment of the present disclosure may further include: after multiple pre-test results are obtained, carrying out differential recognition on the pre-test results in the pre-test results; and classifying and storing the pre-test results according to the differential recognition results, and controlling the pre-test results of different categories in a relatively smaller differential interval.

In step S230, verification data in the verification data set is acquired, and the pre-test result is verified.

And verifying whether decision capability of the currently trained graphic page test model meets expected requirements or not by adopting verification data, if the verification is passed, generating a new test case according to the pre-test result, and storing the new test case into a training data set. The verification data in the verification data set may be a pre-test result of a historical test case, after the pre-test result is obtained, the pre-test result may be screened, a part of the pre-test result is screened to generate a test case and stored in the training data set, or a part of the pre-test result may be used as verification data and stored in the verification data set, specifically, 80% of the pre-test result may be stored in the training data set, and 20% of the pre-test result may be stored in the verification data set.

It should be noted that, the training method of the graphic page test model provided by the embodiment of the present disclosure may perform training in an offline state, and only needs to download at least part of information in the training data set and the verification data set to the local area of the storage model, so that network resources may not be occupied.

That is, in the training method of the graphic page test model provided by the embodiment of the disclosure, a case filling training data set can be generated autonomously, and then a cloning algorithm is learned through a case training model in the training data set, so that efficient model training is realized.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related user personal information all conform to the regulations of related laws and regulations, and the public sequence is not violated.

Based on the same principle as the method shown in fig. 1, fig. 3 shows a schematic structural diagram of a graphic page testing apparatus provided by an embodiment of the disclosure, and as shown in fig. 3, the apparatus 30 may include:

a determining module 301, configured to determine and access a tested page based on preset configuration data;

the acquiring module 302 is configured to acquire current page information of a tested page, and match a page operation matched with the page information through a graphic page test model;

the execution module 303 is configured to execute a page operation to test a tested page, and obtain a corresponding test result;

and the storage module 304 is configured to generate and store a test case according to the test result.

Based on the same principle as the method shown in fig. 2, fig. 4 shows a schematic structural diagram of a training device for a graphic page test model according to an embodiment of the disclosure, and as shown in fig. 4, the device 40 may include:

the acquiring module 401 is configured to acquire a historical test case in the training data set, and execute the historical test case to perform test training;

a generating module 402, configured to record a testing process of the historical testing case for each historical testing case, and generate and store a pre-testing result corresponding to each testing process;

the storage module 403 is configured to obtain verification data in the verification data set, verify the pre-test result, generate a new test case according to the pre-test result if the verification is passed, and store the new test case in the training data set.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

Fig. 5 illustrates a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 5, the apparatus 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

Various components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, mouse, etc.; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the respective methods and processes described above, such as a response method. For example, in some embodiments, the response method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the answering method described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the answer method by any other suitable means (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A method of testing a graphics page, comprising:

determining and accessing a tested page based on preset configuration data;

and generating and storing a test case according to the test result.

2. The method of claim 1, wherein when the tested page is plural, the performing the page operation tests the tested page and obtains a corresponding test result, including:

executing the page operation corresponding to each tested page, and obtaining the subtest result corresponding to each tested page;

generating access paths of all the tested pages according to the time sequence of executing the page operation;

and generating a serialized test result according to the access path and the sub-test result corresponding to each tested page.

3. The method of claim 1, wherein the configuration data comprises at least one of: the method comprises the steps of accessing an address of a tested page, a user name of the tested page and a password corresponding to the user name; the determining and accessing the tested page based on the preset configuration data comprises the following steps:

acquiring a tested page access address contained in the configuration data, and accessing a tested page according to the tested page access address;

logging in the tested page through the user name of the tested page and the password corresponding to the user name contained in the configuration data.

4. The method of claim 1, wherein the obtaining current page information for the tested page comprises: and determining page elements contained in the tested page and the page state of the tested page.

5. A training method of a graphic page test model, comprising:

6. The method of claim 5, wherein generating and saving the pre-test results corresponding to each test procedure comprises: acquiring page elements contained in a tested page, the page state of the tested page and corresponding page operation in the test process;

and generating the pre-test result according to the page element, the page state and the association relation of the page operation.

7. A graphics page testing apparatus, comprising:

8. A training device for a graphic page test model, comprising:

9. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4 and/or the method of any one of claims 5-6.

10. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-4 and/or the method of any one of claims 5-6.