WO2020253466A1 - 一种用户界面的测试用例生成方法及装置 - Google Patents
一种用户界面的测试用例生成方法及装置 Download PDFInfo
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- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
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- G06F11/3684—Test management for test design, e.g. generating new test cases
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- the embodiments of the present invention relate to the technical field of financial technology, and in particular to a method and device for generating test cases of a user interface.
- the embodiment of the present invention provides a method and device for generating test cases of a user interface, so as to improve the efficiency of generating test cases.
- an embodiment of the present invention provides a test case generation method for a user interface, including: acquiring a user interface; using an image recognition model to identify image features of the user interface, and determining control modules in the user interface, each Each control module includes control type information and control location information; a test case of the user interface is generated according to each control module and preset control operations.
- the image recognition model is used to identify the image characteristics of the user interface, and the control modules in the user interface are determined.
- Each control module includes control type information and control position information, and then users are generated according to each control module and preset control operations Test cases for the interface. There is no need to manually identify controls in the user interface and write code to generate test cases, thereby improving the efficiency of generating test cases, further improving the testing efficiency of the user interface, and reducing the testing cost of the user interface.
- the generating the test case of the user interface according to each control module and preset control operations includes: using a cyclic neural network model to decode control type information and control position information of each control module to generate the Test code corresponding to the user interface; compiling the test code corresponding to the user interface and preset control operations to generate test cases for the user interface.
- the cyclic neural network model is used to convert the control modules in the user interface image into test code, and then the test code and control operations are compiled into test cases, so there is no need to manually write and maintain test codes, thereby improving the generation of test cases effectiveness.
- the method further includes: executing a test case of the user interface to obtain a test result of the user interface.
- the user interface can be tested.
- the method further includes: generating a test case set according to the test cases of multiple user interfaces; executing the test case set to obtain test results of multiple user interfaces.
- a test case set is generated according to the test cases of multiple user interfaces; the test case set is executed to obtain test results of multiple user interfaces, which can realize the testing of batch user interfaces.
- the step of using an image recognition model to recognize image features of the user interface and determining the control module in the user interface further includes: comparing the user interface with a historical version interface of the user interface; When it is determined that the degree of difference between the user interface and the historical version interface is greater than a preset threshold, an image recognition model is used to identify the image characteristics of the user interface, and the control module in the user interface is determined.
- the degree of difference when the degree of difference is greater than the preset threshold, it indicates that the user interface of the current version has changed compared with the interface of the historical version.
- the image features of the user interface can be identified through the image recognition model, and the user interface can be determined Control module in order to regenerate test cases.
- the method further includes: updating the test case of the historical version interface with the test case of the user interface.
- test cases of the historical version interface are updated by the test cases of the user interface, without manual update and maintenance, thereby improving the update efficiency of the test cases of the user interface.
- an embodiment of the present invention provides a test case generation device for a user interface, including:
- the acquisition module is used to acquire the user interface
- the recognition module is used to recognize the image features of the user interface using an image recognition model, and determine the control modules in the user interface, each control module includes control type information and control location information;
- the processing module is used to generate test cases of the user interface according to each control module and preset control operations.
- the processing module is specifically configured to: use a cyclic neural network model to decode control type information and control position information of each control module, and generate test code corresponding to the user interface; and convert the test code corresponding to the user interface Compile with preset control operations to generate test cases for the user interface.
- the processing module is further configured to execute a test case of the user interface to obtain a test result of the user interface.
- the processing module is further configured to: generate a test case set according to test cases of multiple user interfaces; execute the test case set to obtain test results of multiple user interfaces.
- the identification is specifically used to: compare the user interface with a historical version interface of the user interface; when it is determined that the degree of difference between the user interface and the historical version interface is greater than a preset threshold,
- the image recognition model is used to recognize the image characteristics of the user interface, and the control module in the user interface is determined.
- the update module is specifically configured to: use the test cases of the user interface to update the test cases of the historical version interface.
- an embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and running on the processor, and the processor implements a user interface test when the program is executed. Steps of the use case generation method.
- an embodiment of the present invention provides a computer-readable storage medium that stores a computer program executable by a computer device, and when the program runs on the computer device, the computer device executes a user interface test Steps of the use case generation method.
- FIG. 1 is a schematic diagram of an application scenario provided by an embodiment of the present invention.
- FIG. 2 is a schematic flowchart of a method for generating test cases for a user interface provided by an embodiment of the present invention
- FIG. 3 is a schematic diagram of a user interface provided by an embodiment of the present invention.
- FIG. 4 is a schematic diagram of a user interface provided by an embodiment of the present invention.
- FIG. 5 is a schematic flowchart of a method for generating test cases for a user interface according to an embodiment of the present invention
- FIG. 6 is a schematic structural diagram of a test case generation device for a user interface provided by an embodiment of the present invention.
- FIG. 7 is a schematic structural diagram of a computer device provided by an embodiment of the present invention.
- User interface is the medium for interaction and information exchange between the system and users.
- Convolutional neural networks (convolutional neural networks, CNN), a feedforward neural network, consists of one or more convolutional layers and a fully connected layer at the top (corresponding to classic neural networks), and also includes correlation weights and pooling Floor. Convolutional neural networks have excellent performance in image processing.
- RNN Recurrent Neural Network
- neurons can not only receive information from other neurons, but also receive their own information, forming a network structure with loops.
- Domain-specific language domain-specific language, DSL.
- the method for generating test cases for a user interface in the embodiment of the present invention can be applied to the application scenario shown in FIG. 1, and the application scenario includes the front-end device 101 and the test system 102.
- the front-end device 101 may be a smart phone, a tablet computer, a portable personal computer, or the like.
- the front-end device 101 is pre-installed with application software related to the financial industry.
- the front-end device 101 runs the application software, intercepts the user interface of the application software, and sends the user interface to the test system 102.
- the testing system 102 includes a continuous integration testing platform 1021 and an update testing platform 1022.
- the continuous integration test platform 1021 uses the image recognition model to identify the image characteristics of the user interface, and determines the control modules in the user interface.
- Each control module includes control type information and control location information, and then generated according to each control module and preset control operations User interface test cases, and then generate test case sets based on multiple user interface test cases.
- the continuous integration test platform 1021 executes a set of test cases and obtains test results of multiple user interfaces.
- the update detection platform 1022 compares the user interface with the historical version interface of the user interface, and when it is determined that the difference between the user interface and the historical version interface is greater than a preset threshold, the test case of the user interface is used to update the test case of the historical version interface.
- the embodiment of the present invention provides a flow of a test case generation method for a user interface.
- the flow of the method can be executed by the test case generation device of the user interface, and the test case generation device of the user interface It may be the test system 102 in FIG. 1, as shown in FIG. 2, including the following steps:
- Step S201 Obtain a user interface.
- the user interface is an image intercepted from application software executed on the front-end device.
- the user interface shown in FIG. 3 includes a switch, an add button, and a sliding bar.
- step S202 the image recognition model is used to recognize the image characteristics of the user interface, and the control module in the user interface is determined.
- the image recognition model may be a convolutional neural network model, a forward neural network model, and the like. Since different controls have different image characteristics, the image recognition model recognizes the image characteristics of the user interface and can divide the user interface into multiple control modules, each of which includes control type information and control position information. Illustratively, as shown in Figure 4, the convolutional neural network model is used to identify the image features of the user interface shown in Figure 3, and the user interface shown in Figure 3 is divided into three control modules, which can be divided into switches according to control types. Control module, add button control module, and slider control module.
- the switch control module includes the position information of the switch control
- the add button control module includes the position information of the added button
- the slider control module includes the position of the slider control. information.
- Step S203 Generate test cases of the user interface according to each control module and preset control operations.
- control operations include clicking, inputting, sliding, and so on.
- the image recognition model is used to identify the image characteristics of the user interface, and the control modules in the user interface are determined.
- Each control module includes control type information and control position information, and then operates according to each control module and preset control Generate test cases for the user interface without manually identifying controls in the user interface and writing code to generate test cases, thereby improving the efficiency of generating test cases, further improving the testing efficiency of the user interface, and reducing the testing cost of the user interface.
- the embodiment of the present invention provides at least the following two implementation manners for generating test cases for the user interface:
- a cyclic neural network model is used to decode the control type information and control position information of each control module, and generate test code corresponding to the user interface. Compile the test codes corresponding to the user interface and preset control operations to generate test cases for the user interface.
- the cyclic neural network model decodes the control type information and control position information of each control module.
- Each hidden state of the cyclic neural network model contains the context information of the control module, and then generates test code based on the context information and the corresponding control module , Where the test code can be DSL code.
- the cyclic neural network model is used to decode the control type information and control position information of the switch control module, and the DSL code corresponding to the control module is generated as: label (x, y, l, w) and switch (x, y, l , W), where label is a label, switch is a switch, x and y are the coordinates of the control, l is the length of the control, and w is the width of the control.
- the same method can be used to generate the DSL code corresponding to other control modules in the user interface, and finally the context information of the control module identified by the cyclic neural network model and the DSL code corresponding to the control module are used to obtain the DSL code of the user interface. Compile the DSL code and the preset control operations corresponding to each control module in the user interface to generate test cases for the user interface.
- the cyclic neural network model is used to convert the control modules in the user interface image into test code, and then the test code and control operations are compiled into test cases, so there is no need to manually write and maintain test codes, thereby improving the efficiency of generating test cases.
- the test code corresponding to each control module is generated according to the control type information and control position information of each control module. Then, the control position information of each control module is combined with the test code corresponding to all control modules to generate the test code corresponding to the user interface. Compile the test codes corresponding to the user interface and preset control operations to generate test cases for the user interface.
- the embodiment of the present invention provides at least the following two testing methods:
- test cases of the user interface can be generated. Further, the test results of the user interface can be sent to the relevant testers to achieve Testing the user interface.
- test case set is generated according to the test cases of multiple user interfaces, and then the test case set is executed to obtain test results of multiple user interfaces. Further, a test report can be generated based on the test results of multiple user interfaces and sent to the tester, thereby realizing the testing of batch user interfaces.
- the user interface can be compared with the historical version interface of the user interface.
- the image recognition model recognizes the image characteristics of the user interface and determines the control module in the user interface.
- the corresponding user interface may or may not be updated. Therefore, when the application software version is updated, you can first determine whether the user interface is updated, and then further determine whether the user interface test needs to be generated Example.
- the average hash (dhash) algorithm, perceptual hash (phash) algorithm, difference value hash (dhash) algorithm, etc. can be used to determine the degree of difference between the user interface and the historical version interface. When the degree of difference is greater than the preset threshold, it means that the user interface of the current version has changed compared to the interface of the historical version.
- the test case of the historical version interface is used to test the user interface of the current version, the test result will be biased, so it needs to be regenerated Test case.
- test cases of the historical version interface can be used to test the user interface of the current version without regenerating the user interface. Test case.
- the test cases of the user interface may be used to update the test cases of the historical version interface.
- the test case of the user interface can be directly replaced with the test case of the historical version interface.
- Judge whether the user interface is updated by comparing the differences between different versions of the user interface. If it is updated, regenerate the test cases of the user interface to update the test cases of the historical version interface, without manual update and maintenance, thereby improving the test cases of the user interface The update efficiency.
- the following describes a method for generating test cases for a user interface provided by an embodiment of the present invention in combination with specific implementation scenarios.
- the method is executed by the test case generation device of the user interface, as shown in FIG. 5 ,
- the method includes the following steps:
- Step S501 Obtain a user interface.
- step S502 the difference value hash algorithm is used to determine the degree of difference between the user interface and the historical version interface of the user interface.
- step S503 it is determined whether the degree of difference between the user interface and the historical version interface is greater than a preset threshold, if so, step S504 is executed, otherwise, step S511 is executed.
- a test report of the degree of difference between the user interface and the historical version interface of the user interface is generated.
- step S504 the convolutional neural network model is used to identify the image characteristics of the user interface, and the control module in the user interface is determined.
- Each control module includes control type information and control location information.
- Step S505 Use the cyclic neural network model to decode the control type information and control position information of each control module, and generate test code corresponding to the user interface.
- Step S506 Compile the test code corresponding to the user interface and the preset control operations to generate a test case of the user interface.
- Step S507 Use the test cases of the user interface to update the test cases of the historical version interface.
- Step S508 Generate a test case set based on the test cases of the multiple user interfaces.
- Step S509 Execute the test case set to obtain test results of multiple user interfaces.
- Step S510 Generate a test report and send the test report to the tester.
- Step S511 Execute the test case of the historical version interface to obtain the test result of the user interface.
- the image recognition model is used to identify the image characteristics of the user interface, and the control modules in the user interface are determined.
- Each control module includes control type information and control position information, and then operates according to each control module and preset control Generate test cases for the user interface without manually identifying controls in the user interface and writing code to generate test cases, thereby improving the efficiency of generating test cases, further improving the testing efficiency of the user interface, and reducing the testing cost of the user interface.
- the cyclic neural network model is used to convert the controls in the user interface image into test code, and then the test code and control operations are compiled into test cases, so there is no need to manually write and maintain test codes, thereby improving the efficiency of generating test cases.
- the following uses the user interface of financial application software as an example to introduce a user interface testing method, which is executed interactively by the front-end equipment and the testing system, including:
- the front-end equipment installs the financial application software to be tested and runs the financial application software.
- the front-end equipment intercepts the user interface of the financial application software and sends the user interface to the test system.
- the intercepted user interface includes the login interface and the financial business operation interface.
- the test system uses a convolutional neural network model to identify the image characteristics of the login interface, and determine the control modules in the login interface.
- the control modules in the login interface include a username input box module, a password input box module, and a login button module.
- Each control module includes control type information and control location information. Then use the cyclic neural network model to decode the control type information and control position information of each control module, and generate the test code corresponding to the login interface.
- an embodiment of the present invention provides a test case generation device for a user interface.
- the device 600 includes:
- the obtaining module 601 is used to obtain a user interface
- the recognition module 602 is configured to use an image recognition model to recognize image features of the user interface and determine control modules in the user interface, each control module includes control type information and control location information;
- the processing module 603 is configured to generate test cases of the user interface according to each control module and preset control operations.
- processing module 603 is specifically configured to:
- processing module 603 is further configured to:
- the test case of the user interface is executed to obtain the test result of the user interface.
- processing module 603 is further configured to:
- the identification module 602 is specifically configured to:
- an image recognition model is used to identify the image characteristics of the user interface, and the control module in the user interface is determined.
- it also includes an update module 604;
- the update module 604 is specifically configured to:
- an embodiment of the present invention provides a computer device. As shown in FIG. 7, it includes at least one processor 701 and a memory 702 connected to the at least one processor.
- the embodiment of the present invention does not limit the processor.
- the specific connection medium between the 701 and the memory 702 is, for example, the connection between the processor 701 and the memory 702 through a bus in FIG. 7.
- the bus can be divided into address bus, data bus, control bus, etc.
- the memory 702 stores instructions that can be executed by at least one processor 701. By executing the instructions stored in the memory 702, the at least one processor 701 can execute the aforementioned test case generation method of the user interface. step.
- the processor 701 is the control center of the computer equipment, which can use various interfaces and lines to connect to various parts of the computer equipment, and generate a test by running or executing instructions stored in the memory 702 and calling data stored in the memory 702 Example.
- the processor 701 may include one or more processing units, and the processor 701 may integrate an application processor and a modem processor.
- the application processor mainly processes the operating system, user interface, and application programs.
- the adjustment processor mainly deals with wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 701.
- the processor 701 and the memory 702 may be implemented on the same chip, and in some embodiments, they may also be implemented on separate chips.
- the processor 701 may be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application specific integrated circuit (ASIC), a field programmable gate array or other programmable logic devices, discrete gates or transistors Logic devices and discrete hardware components can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention.
- the general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present invention may be directly embodied as being executed and completed by a hardware processor, or executed and completed by a combination of hardware and software modules in the processor.
- the memory 702 as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules.
- the memory 702 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (Random Access Memory, RAM), static random access memory (Static Random Access Memory, SRAM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), magnetic memory, disk , CD, etc.
- the memory 702 is any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.
- the memory 702 in the embodiment of the present invention may also be a circuit or any other device capable of realizing a storage function for storing program instructions and/or data.
- the embodiments of the present invention provide a computer-readable storage medium that stores a computer program executable by a computer device, and when the program runs on the computer device, the computer device executes the user interface The steps of the test case generation method.
- the embodiments of the present invention may be provided as methods or computer program products. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.
- a computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
- These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device.
- the device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.
- These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment.
- the instructions provide steps for implementing functions specified in a flow or multiple flows in the flowchart and/or a block or multiple blocks in the block diagram.
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Abstract
本发明实施例提供了一种用户界面的测试用例生成方法及装置，涉及金融科技技术领域，该方法包括：采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息，然后根据每个控件模块及预设的控件操作生成用户界面的测试用例，而不需要人工识别用户界面中的控件并编写代码生成测试用例，从而提高了生成测试用例的效率，进一步可以提高用户界面的测试效率，降低用户界面的测试成本。通过比较不同版本的用户界面的差异度判断用户界面是否更新，若更新，则重新生成用户界面的测试用例来更新历史版本界面的测试用例，无需人工参更新和维护，从而提高用户界面的测试用例的更新效率。
Description
相关申请的交叉引用
本申请要求在2019年06月21日提交中国专利局、申请号为201910540156.1、申请名称为“一种用户界面的测试用例生成方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本发明实施例涉及金融科技技术领域，尤其涉及一种用户界面的测试用例生成方法及装置。
随着计算机技术的发展，越来越多的技术应用在金融领域，传统金融业正在逐步向金融科技(Fintech)转变，但由于金融行业的安全性、实时性要求，也对技术提出的更高的要求。目前，金融行业的用户界面软件越来越多，对用户界面软件进行自动化测试的要求也越来越高。在一些测试方式中，在生成测试用例时，需要人工参与识别用户界面中的控件，人工编写代码生成测试用例，该方法生成测试用例的效率低，从而影响用户界面的测试效率，提高了用户界面的测试成本。
发明内容
本发明实施例提供了一种用户界面的测试用例生成方法及装置，用以提高生成测试用例的效率。
第一方面，本发明实施例提供了一种用户界面的测试用例生成方法，包括：获取用户界面；采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息；根据每个控件模块及预设的控件操作生成所述用户界面的测试用例。
通过上述方法，采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息，然后根据每个控件模块及预设的控件操作生成用户界面的测试用例。而不需要人工识别用户界面中的控件并编写代码生成测试用例，从而提高了生成测试用例的效率，进一步可以提高用户界面的测试效率，降低用户界面的测试成本。
可选地，所述根据每个控件模块及预设的控件操作生成所述用户界面的测试用例，包括：采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成所述用户界面对应的测试代码；将所述用户界面对应的测试代码和预设的控件操作进行编译，生成所述用户界面的测试用例。
通过上述方法，采用循环神经网络模型将用户界面图像中的控件模块转化为测试代码，然后将测试代码和控件操作编译成测试用例，故不需要人工编写和维护测试代码，从而提高生成测试用例的效率。
可选地，还包括：执行所述用户界面的测试用例获得所述用户界面的测试结果。
通过上述方法，可以实现对用户界面的测试。
可选地，还包括：根据多个用户界面的测试用例生成测试用例集；执行所述测试用例集，获得多个用户界面的测试结果。
通过上述方法，根据多个用户界面的测试用例生成测试用例集；执行所述测试用例集，获得多个用户界面的测试结果，可以实现对批量用户界面的测试。
可选地，所述采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，还包括：将所述用户界面与所述用户界面的历史版本界面进行比对；在确定所述用户界面和所述历史版本界面的差异度大于预设阈值时，采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块。
通过上述方法，当差异度大于预设阈值时，说明当前版本的用户界面相较于历史版本界面发生了变化，可以通过图像识别模型识别所述用户界面的 图像特征，确定所述用户界面中的控件模块，以便重新生成测试用例。
可选地，还包括：采用所述用户界面的测试用例更新所述历史版本界面的测试用例。
通过上述方法，采用所述用户界面的测试用例更新所述历史版本界面的测试用例，无需人工参更新和维护，从而提高用户界面的测试用例的更新效率。
第二方面，本发明实施例提供了一种用户界面的测试用例生成装置，包括：
获取模块，用于获取用户界面；
识别模块，用于采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息；
处理模块，用于根据每个控件模块及预设的控件操作生成所述用户界面的测试用例。
可选地，所述处理模块具体用于：采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成所述用户界面对应的测试代码；将所述用户界面对应的测试代码和预设的控件操作进行编译，生成所述用户界面的测试用例。
可选地，所述处理模块还用于：执行所述用户界面的测试用例获得所述用户界面的测试结果。
可选地，所述处理模块还用于：根据多个用户界面的测试用例生成测试用例集；执行所述测试用例集，获得多个用户界面的测试结果。
可选地，所述识别具体用于：将所述用户界面与所述用户界面的历史版本界面进行比对；在确定所述用户界面和所述历史版本界面的差异度大于预设阈值时，采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块。
可选地，还包括更新模块；所述更新模块具体用于：采用所述用户界面 的测试用例更新所述历史版本界面的测试用例。
第三方面，本发明实施例提供了一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现用户界面的测试用例生成方法的步骤。
第四方面，本发明实施例提供了一种计算机可读存储介质，其存储有可由计算机设备执行的计算机程序，当所述程序在计算机设备上运行时，使得所述计算机设备执行用户界面的测试用例生成方法的步骤。
图1为本发明实施例提供的一种应用场景示意图；
图2为本发明实施例提供的一种用户界面的测试用例生成方法的流程示意图；
图3为本发明实施例提供的一种用户界面的示意图；
图4为本发明实施例提供的一种用户界面的示意图；
图5为本发明实施例提供的一种用户界面的测试用例生成方法的流程示意图；
图6为本发明实施例提供的一种用户界面的测试用例生成装置的结构示意图；
图7为本发明实施例提供的一种计算机设备的结构示意图。
为了方便理解，下面对本发明实施例中涉及的名词进行解释。
用户界面(user interface，UI)，系统和用户之间进行交互和信息交换的媒介。
卷积神经网络(convolutional neural networks，CNN)，一种前馈神经网络，由一个或多个卷积层和顶端的全连通层(对应经典的神经网络)组成，同时也包括关联权重和池化层。卷积神经网络在图像处理方面有出色表现。
循环神经网络(recurrent neural network，RNN)，一类具有短期记忆能力的神经网络。在循环神经网络中，神经元不但可以接受其它神经元的信息，也可以接受自身的信息，形成具有环路的网络结构。
领域特定语言(domain-specific language，DSL)。
本发明实施例中的用户界面的测试用例生成方法可以应用于如图1所示的应用场景，在该应用场景中包括前端设备101、测试系统102。前端设备101可以是智能手机、平板电脑或便携式个人计算机等等。前端设备101预先安装金融行业相关的应用软件，前端设备101运行应用软件，截取应用软件的用户界面并将用户界面发送至测试系统102。测试系统102包括持续集成测试平台1021、更新检测平台1022。持续集成测试平台1021采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息，然后根据每个控件模块及预设的控件操作生成用户界面的测试用例，之后再根据多个用户界面的测试用例生成测试用例集。持续集成测试平台1021执行测试用例集，获得多个用户界面的测试结果。更新检测平台1022将用户界面与用户界面的历史版本界面进行比对，在确定用户界面和历史版本界面的差异度大于预设阈值时，采用用户界面的测试用例更新历史版本界面的测试用例。
基于图1所示的应用场景图，本发明实施例提供了一种用户界面的测试用例生成方法的流程，该方法的流程可以由用户界面的测试用例生成装置执行，用户界面的测试用例生成装置可以是图1中的测试系统102，如图2所示，包括以下步骤：
步骤S201，获取用户界面。
具体地，用户界面是从前端设备上执行的应用软件中截取的图像。示例性地，如图3所示用户界面中，包括开关、增加按钮、滑动条。
步骤S202，采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块。
具体地，图像识别模型可以是卷积神经网络模型、前向神经网络模型等。 由于不同的控件拥有不同的图像特征，故图像识别模型识别用户界面的图像特征，可以将用户界面划分为多个控件模块，每个控件模块包括控件类型信息和控件位置信息。示例性地，如图4所示，采用卷积神经网络模型识别图3所示的用户界面的图像特征，将图3所示的用户界面划分为3个控件模块，按照控件类型可以分为开关控件模块、增加按钮控件模块以及滑动条控件模块，在开关控件模块中包括开关控件的位置信息，在增加按钮控件模块中包括增加按钮的位置信息，在滑动条控件模块中包括滑动条控件的位置信息。
步骤S203，根据每个控件模块及预设的控件操作生成用户界面的测试用例。
具体地，控件操作包括点击、输入、滑动等。
本发明实施例中，采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息，然后根据每个控件模块及预设的控件操作生成用户界面的测试用例，而不需要人工识别用户界面中的控件并编写代码生成测试用例，从而提高了生成测试用例的效率，进一步可以提高用户界面的测试效率，降低用户界面的测试成本。
可选地，在上述步骤S203中，本发明实施例至少提供以下两种生成用户界面的测试用例的实施方式：
在一种可能的实施方式中，采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成用户界面对应的测试代码。将用户界面对应的测试代码和预设的控件操作进行编译，生成用户界面的测试用例。
具体地，循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，循环神经网络模型每一个隐藏状态都包含了控件模块的上下文信息，之后根据上下文信息和对应的控件模块生成测试代码，其中，测试代码可以为DSL代码。示例性地，采用循环神经网络模型解码开关控件模块的控件类型信息和控件位置信息，生成该控件模块对应的DSL代码为：label(x，y，l，w)和switch(x，y，l，w)，其中，label为标签，switch为开关，x、y为控件 的坐标，l为控件的长度，w为控件的宽度。采用同样的方法可以生成用户界面中其他控件模块对应的DSL代码，最后采用循环神经网络模型识别的控件模块的上下文信息以及控件模块对应的DSL代码获得用户界面的DSL代码。将DSL代码和用户界面中每个控件模块对应的预设控件操作进行编译，生成用户界面的测试用例。采用循环神经网络模型将用户界面图像中的控件模块转化为测试代码，然后将测试代码和控件操作编译成测试用例，故不需要人工编写和维护测试代码，从而提高生成测试用例的效率。
在一种可能的实施方式中，根据每个控件模块的控件类型信息和控件位置信息，生成每个控件模块对应的测试代码。然后将每个控件模块的控件位置信息组合所有控件模块对应的测试代码，生成用户界面对应的测试代码。将用户界面对应的测试代码和预设的控件操作进行编译，生成用户界面的测试用例。
在对用户界面进行测试时，本发明实施例至少提供以下两种测试方式：
在一种可能的实施方式中，在生成用户界面的测试用例后，可以执行用户界面的测试用例获得用户界面的测试结果，进一步地，可以将用户界面的测试结果发送至相关的测试人员，实现对用户界面的测试。
在另一种可能的实施方式中，在生成用户界面的测试用例后，根据多个用户界面的测试用例生成测试用例集，然后执行测试用例集，获得多个用户界面的测试结果。进一步地，可以基于多个用户界面的测试结果生成测试报告并将测试报告发送至测试人员，从而实现对批量用户界面的测试。
可选地，在上述步骤S202中，在获取到用户界面后，可以将用户界面与用户界面的历史版本界面进行比对，在确定用户界面和历史版本界面的差异度大于预设阈值时，采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块。
具体地，随着应用软件的版本更新，对应的用户界面可能会更新，也可能不会更新，故应用软件版本更新时，可以先判断用户界面是否更新，再进一步确定是否需要生成用户界面的测试用例。可以采用平均哈希(dhash)算 法、感知哈希(phash)算法、差异值哈希(dhash)算法等确定用户界面和历史版本界面的差异度。当差异度大于预设阈值时，说明当前版本的用户界面相较于历史版本界面发生了变化，采用历史版本界面的测试用例测试当前版本的用户界面时，测试结果将出现偏差，故需要重新生成测试用例。当差异度不大于预设阈值时，说明当前版本的用户界面相较于历史版本界面基本没有变化，可以采用历史版本界面的测试用例测试当前版本的用户界面，不需要再重复生成该用户界面的测试用例。
进一步地，生成用户界面的测试用例后，可以采用用户界面的测试用例更新历史版本界面的测试用例。比如，可以直接将该用户界面的测试用例替换历史版本界面的测试用例。通过比较不同版本的用户界面的差异度判断用户界面是否更新，若更新，则重新生成用户界面的测试用例来更新历史版本界面的测试用例，无需人工参更新和维护，从而提高用户界面的测试用例的更新效率。
为了更好的解释本发明实施例，下面结合具体的实施场景描述本发明实施例提供的一种用户界面的测试用例生成方法，该方法由用户界面的测试用例生成装置执行，如图5所示，该方法包括以下步骤：
步骤S501，获取用户界面。
步骤S502，采用差异值哈希算法确定用户界面和用户界面的历史版本界面的差异度。
步骤S503，判断用户界面和历史版本界面的差异度是否大于预设阈值，若是，则执行步骤S504，否则执行步骤S511。
具体地，生成用户界面与用户界面的历史版本界面之间的差异度测试报告。
步骤S504，采用卷积神经网络模型识别用户界面的图像特征，确定用户界面中的控件模块。
每个控件模块包括控件类型信息和控件位置信息。
步骤S505，采用循环神经网络模型解码每个控件模块的控件类型信息和 控件位置信息，生成用户界面对应的测试代码。
步骤S506，将用户界面对应的测试代码和预设的控件操作进行编译，生成用户界面的测试用例。
步骤S507，采用用户界面的测试用例更新历史版本界面的测试用例。
步骤S508，根据多个用户界面的测试用例生成测试用例集。
步骤S509，执行测试用例集，获得多个用户界面的测试结果。
步骤S510，生成测试报告并将测试报告发送至测试人员。
步骤S511，执行历史版本界面的测试用例，获得用户界面的测试结果。
本发明实施例中，采用图像识别模型识别用户界面的图像特征，确定用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息，然后根据每个控件模块及预设的控件操作生成用户界面的测试用例，而不需要人工识别用户界面中的控件并编写代码生成测试用例，从而提高了生成测试用例的效率，进一步可以提高用户界面的测试效率，降低用户界面的测试成本。采用循环神经网络模型将用户界面图像中的控件转化为测试代码，然后将测试代码和控件操作编译成测试用例，故不需要人工编写和维护测试代码，从而提高生成测试用例的效率。通过比较不同版本的用户界面的差异度判断用户界面是否更新，若更新，则重新生成用户界面的测试用例来更新历史版本界面的测试用例，无需人工参更新和维护，从而提高用户界面的测试用例的更新效率。
为了更好的解释本发明实施例，下面以金融应用软件的用户界面为例介绍一种用户界面的测试方法，该方法由前端设备和测试系统交互执行，包括：
前端设备上安装待测试的金融应用软件并运行金融应用软件，前端设备截取金融应用软件的用户界面并将用户界面发送至测试系统，设定截取的用户界面包括登录界面、金融业务操作界面等。针对登录界面，测试系统采用卷积神经网络模型识别登录界面的图像特征，确定登录界面中的控件模块，登录界面中的控件模块包括用户名输入框模块、密码输入框模块、登录按钮模块，每个控件模块包括控件类型信息和控件位置信息。然后采用循环神经 网络模型解码每个控件模块的控件类型信息和控件位置信息，生成登录界面对应的测试代码。将登录界面对应的测试代码和预设的控件操作进行编译，生成登录界面的测试用例。按照上述同样的方法生成金融业务操作界面等其他用户界面的测试用例，此处不再赘述。将从金融应用软件截取的多个用户界面的测试用例生成测试用例集，然后执行测试用例，生成金融应用软件的用户界面测试报告并将测试报告发送至测试人员。
基于相同的技术构思，本发明实施例提供了一种用户界面的测试用例生成装置，如图6所示，该装置600包括：
获取模块601，用于获取用户界面；
识别模块602，用于采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息；
处理模块603，用于根据每个控件模块及预设的控件操作生成所述用户界面的测试用例。
可选地，所述处理模块603具体用于：
采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成所述用户界面对应的测试代码；
将所述用户界面对应的测试代码和预设的控件操作进行编译，生成所述用户界面的测试用例。
可选地，所述处理模块603还用于：
执行所述用户界面的测试用例获得所述用户界面的测试结果。
可选地，所述处理模块603还用于：
根据多个用户界面的测试用例生成测试用例集；
执行所述测试用例集，获得多个用户界面的测试结果。
可选地，所述识别模块602具体用于：
将所述用户界面与所述用户界面的历史版本界面进行比对；
在确定所述用户界面和所述历史版本界面的差异度大于预设阈值时，采 用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块。
可选地，还包括更新模块604；
所述更新模块604具体用于：
采用所述用户界面的测试用例更新所述历史版本界面的测试用例。
基于相同的技术构思，本发明实施例提供了一种计算机设备，如图7所示，包括至少一个处理器701，以及与至少一个处理器连接的存储器702，本发明实施例中不限定处理器701与存储器702之间的具体连接介质，图7中处理器701和存储器702之间通过总线连接为例。总线可以分为地址总线、数据总线、控制总线等。
在本发明实施例中，存储器702存储有可被至少一个处理器701执行的指令，至少一个处理器701通过执行存储器702存储的指令，可以执行前述的用户界面的测试用例生成方法中所包括的步骤。
其中，处理器701是计算机设备的控制中心，可以利用各种接口和线路连接计算机设备的各个部分，通过运行或执行存储在存储器702内的指令以及调用存储在存储器702内的数据，从而生成测试用例。可选的，处理器701可包括一个或多个处理单元，处理器701可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器701中。在一些实施例中，处理器701和存储器702可以在同一芯片上实现，在一些实施例中，它们也可以在独立的芯片上分别实现。
处理器701可以是通用处理器，例如中央处理器(CPU)、数字信号处理器、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件，可以实现或者执行本发明实施例中公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本发明实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的 硬件及软件模块组合执行完成。
存储器702作为一种非易失性计算机可读存储介质，可用于存储非易失性软件程序、非易失性计算机可执行程序以及模块。存储器702可以包括至少一种类型的存储介质，例如可以包括闪存、硬盘、多媒体卡、卡型存储器、随机访问存储器(Random Access Memory，RAM)、静态随机访问存储器(Static Random Access Memory，SRAM)、可编程只读存储器(Programmable Read Only Memory，PROM)、只读存储器(Read Only Memory，ROM)、带电可擦除可编程只读存储器(Electrically Erasable Programmable Read-Only Memory，EEPROM)、磁性存储器、磁盘、光盘等等。存储器702是能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。本发明实施例中的存储器702还可以是电路或者其它任意能够实现存储功能的装置，用于存储程序指令和/或数据。
基于相同的技术构思，本发明实施例提供了一种计算机可读存储介质，其存储有可由计算机设备执行的计算机程序，当所述程序在计算机设备上运行时，使得所述计算机设备执行用户界面的测试用例生成方法的步骤。
本领域内的技术人员应明白，本发明的实施例可提供为方法、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的 装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。
Claims (10)
- 一种用户界面的测试用例生成方法，其特征在于，包括：获取用户界面；采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息；根据每个控件模块及预设的控件操作生成所述用户界面的测试用例。
- 如权利要求1所述的方法，其特征在于，所述根据每个控件模块及预设的控件操作生成所述用户界面的测试用例，包括：采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成所述用户界面对应的测试代码；将所述用户界面对应的测试代码和预设的控件操作进行编译，生成所述用户界面的测试用例。
- 如权利要求1所述的方法，其特征在于，还包括：执行所述用户界面的测试用例获得所述用户界面的测试结果。
- 如权利要求1所述的方法，其特征在于，还包括：根据多个用户界面的测试用例生成测试用例集；执行所述测试用例集，获得多个用户界面的测试结果。
- 如权利要求1至4任一所述的方法，其特征在于，所述采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，包括：将所述用户界面与所述用户界面的历史版本界面进行比对；在确定所述用户界面和所述历史版本界面的差异度大于预设阈值时，采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块。
- 如权利要求5所述的方法，其特征在于，还包括：采用所述用户界面的测试用例更新所述历史版本界面的测试用例。
- 一种用户界面的测试用例生成装置，其特征在于，包括：获取模块，用于获取用户界面；识别模块，用于采用图像识别模型识别所述用户界面的图像特征，确定所述用户界面中的控件模块，每个控件模块包括控件类型信息和控件位置信息；处理模块，用于根据每个控件模块及预设的控件操作生成所述用户界面的测试用例。
- 如权利要求7所述的装置，其特征在于，所述处理模块具体用于：采用循环神经网络模型解码每个控件模块的控件类型信息和控件位置信息，生成所述用户界面对应的测试代码；将所述用户界面对应的测试代码和预设的控件操作进行编译，生成所述用户界面的测试用例。
- 一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现权利要求1～6任一权利要求所述方法的步骤。
- 一种计算机可读存储介质，其特征在于，其存储有可由计算机设备执行的计算机程序，当所述程序在计算机设备上运行时，使得所述计算机设备执行权利要求1～6任一所述方法的步骤。
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| CN111522615B (zh) * | 2020-04-23 | 2023-08-15 | 深圳赛安特技术服务有限公司 | 命令行界面的更新方法、装置、设备及存储介质 |
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| CN111897740B (zh) * | 2020-08-24 | 2023-06-13 | 抖音视界有限公司 | 用户界面的测试方法、装置、电子设备及计算机可读介质 |
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