CN112433937A - Test case processing method and device and storage medium - Google Patents
Test case processing method and device and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3684—Test management for test design, e.g. generating new test cases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3692—Test management for test results analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
- G06T7/41—Analysis of texture based on statistical description of texture
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Abstract
The application relates to a data processing technology, in particular to a test case processing method, a test case processing device and a storage medium, wherein the method comprises the following steps: acquiring a target test case, wherein the target test case comprises at least one test file; acquiring target display parameters of a brain picture to be generated; determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier; acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier; screening the attribute information set according to the target attribute identification to obtain attribute information of the at least one test file; and generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case. By adopting the embodiment of the application, the management efficiency of the test case is improved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a test case processing method, a test case processing device and a storage medium.
Background
At present, most of companies write test cases in excel, upload the test cases to a system platform finally, and write the test cases to manage based on the system platform, so that the test cases written by the method are inconvenient to check, the data is abundant, confusion is easy to occur, the management difficulty is increased, and the condition that the test of the corresponding test cases passes through cannot be checked in real time, therefore, the problem of how to improve the management efficiency of the test cases needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a test case processing method, a test case processing device and a storage medium, and can improve the management efficiency of test cases.
In a first aspect, an embodiment of the present application provides a test case processing method, where the method includes:
acquiring a target test case, wherein the target test case comprises at least one test file;
acquiring target display parameters of a brain picture to be generated;
determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier;
acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
screening the attribute information set according to the target attribute identification to obtain attribute information of the at least one test file;
and generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case.
In a second aspect, an embodiment of the present application provides a test case processing apparatus, including: a first obtaining unit, a second obtaining unit, a determining unit, a third obtaining unit, a screening unit and a generating unit, wherein,
the first obtaining unit is used for obtaining a target test case, and the target test case comprises at least one test file;
the second acquisition unit is used for acquiring target display parameters of the brain picture to be generated;
the determining unit is used for determining a target attribute identifier corresponding to the target display parameter according to a mapping relation between a preset display parameter and an attribute identifier;
the third obtaining unit is configured to obtain an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
the screening unit is used for screening the attribute information set according to the target attribute identification to obtain the attribute information of the at least one test file;
the generating unit is used for generating a target brain graph according to the attribute information of the at least one test file, and the target brain graph is used for displaying the target test case.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that, in the test case processing method, apparatus, and storage medium described in the embodiments of the present application, a target test case is obtained, where the target test case includes at least one test file, a target display parameter of a brain image to be generated is obtained, a target attribute identifier corresponding to the target display parameter is determined according to a mapping relationship between preset display parameters and attribute identifiers, an attribute information set of the at least one test file is obtained, the attribute information set includes a plurality of attribute information, each attribute information corresponds to one attribute identifier, the attribute information set is screened according to the target attribute identifier to obtain attribute information of the at least one test file, a target brain image is generated according to the attribute information of the at least one test file, and the target brain image is used for displaying the target test case, so that a corresponding brain image can be generated based on the attribute information of the test file of the test case, the brain graph shows the test cases, so that the management efficiency of the test cases can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a test case processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another test case processing method provided in the embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 4 is a block diagram illustrating functional units of a test case processing apparatus according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device according to the embodiment of the present application may include various handheld devices (such as a mobile phone, a tablet computer, a POS machine, etc.) having a wireless communication function, a desktop computer, an in-vehicle device, a wearable device (a smart watch, a smart bracelet, a wireless headset, an augmented reality/virtual reality device, smart glasses), an AI robot, a computing device, or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), a Mobile Station (MS), a terminal device (terminal device), etc. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices.
The following describes embodiments of the present application in detail.
Referring to fig. 1, fig. 1 is a schematic flowchart of a test case processing method provided in an embodiment of the present application, and as shown in the drawing, the test case processing method is applied to an electronic device, and includes:
101. obtaining a target test case, wherein the target test case comprises at least one test file.
The target test case may be a test item or a part of the test item. The target test case may include at least one test file. A test file may be understood as a page or a link or a test branch.
102. And acquiring target display parameters of the brain picture to be generated.
In the embodiment of the present application, the target display parameter may be at least one of the following: background color, frame structure, hierarchical pattern, font size, etc., without limitation. The attribute identification may be at least one of: attribute names, attribute priorities, node locations, process contents, storage locations corresponding to the attributes, and the like, which are not limited herein.
Optionally, in the step 102, obtaining the target display parameter of the brain map to be generated may include the following steps:
21. displaying a plurality of brain graph styles on a display interface;
22. determining a target brain graph style selected by a user from the plurality of brain graph styles;
23. and obtaining the display parameters of the target brain graph style to obtain the target display parameters of the brain graph to be generated.
The electronic equipment can display a plurality of brain picture styles on the display interface, and then can select favorite brain picture samples through man-machine interaction, so that target brain picture styles can be obtained, and display parameters corresponding to the target brain picture styles are used as target display parameters of the brain pictures to be generated.
103. And determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier.
In the embodiment of the present application, the display parameter may be at least one of the following: background color, frame structure, hierarchical pattern, font size, etc., without limitation. The attribute identification may be at least one of: attribute names, attribute priorities, node locations, process contents, storage locations corresponding to the attributes, and the like, which are not limited herein. In a specific implementation, the mapping relationship between the preset display parameter and the attribute identifier may be pre-stored in the electronic device. Furthermore, after obtaining the target display parameter of the brain image to be generated, the electronic device may determine the target attribute identifier corresponding to the target display parameter according to a preset mapping relationship between the display parameter and the attribute identifier.
104. And acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier.
The electronic device may obtain an attribute information set of at least one test file, where the attribute information set includes a plurality of attribute information, and each attribute information corresponds to an attribute identifier.
105. And screening the attribute information set according to the target attribute identification to obtain the attribute information of the at least one test file.
In specific implementation, the electronic device can filter the attribute information set according to the target attribute identifier to obtain the attribute information of at least one test file, and thus, the attribute information of the test file can be filtered according to the display parameters of the brain graph required by the user, so that the brain graph required by the user is generated, and the user experience is facilitated to be improved.
106. And generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case.
In a specific implementation, the electronic device may generate a target brain graph through the brain graph generation tool and by using the attribute information of the at least one test file, where the target brain graph is used to display the target test case.
In specific implementation, aiming at the existing management scheme, the test cases are compiled into the brain graph in a format of 'case classification-case name-flow (including url, entries) -check points' through the brain graph, and visualization is realized. The visualized management can clearly show the content of each process node and check point, and can carry out the extension secondary development, check the execution result of the automatic test case in real time and the like.
For example, the brain graph is generated by means of node + attribute, which specifically includes the following steps:
{
"nodeId":"A-001",
"name": 100001-brain graph test ",
"colour":"green"
}
furthermore, a unique value (nodeId) of each node is generated according to each brain graph file to identify the nodes, the attributes are used for storing the attributes (test passing state, node description, name, color and the like) of each node, the brain graph is an online brain graph, the brain graph storage format is a json format, the attributes are stored in a key-value format, the data stored in a database is also json, the data does not need to be converted into a file format (xmind) for storage, the data has better reusability and a more convenient storage mode compared with xmind, and the fields (such as the test passing state, the node description, the name, the color and the like) in json of the brain graph are read by the front end, analyzed and then rendered and displayed on the front end page. The online brain graph can be exported to be stored locally in an xmnd format, so that data migration is facilitated. The online brain graph is convenient for the common use of all the systems.
In a specific implementation, the following is an example of a hundred degree brain map, specifically as follows:
1. the open source framework development based on the Baidu brain graph or the ant golden clothes, and the storage path is as follows: requirement name-test case classification-test case (including step) -check point, each case identification case-id represents a test case;
2. the front end uses vue to embed the brain graph plug-in into the page, the back end analyzes and stores or performs other operations through the brain graph json parameter transmitted by the front end, and the back end can use java, springboot, mysql
3. The case color is used for representing the test execution result, the correlation can be carried out through the back-end code, the test case is stored after the execution is finished, and the corresponding test case color is modified
4. The plug-in function can be directly used for exporting the xmind, the excel is required to be analyzed, and each node level is separated by using special characters when the brain graph library is exported.
Optionally, in the step 106, generating the target brain graph according to the attribute information of the at least one test file may include the following steps:
61. converting the attribute information of the at least one test file into an initial brain map by a brain map generating tool;
62. and displaying the initial brain map on a designated page according to the target display parameters to obtain the target brain map.
The brain graph generation tool is used for realizing brain graph generation, and the specified page can be set by a user or defaulted by a system. In specific implementation, the electronic device may convert the attribute information of the at least one test file into an initial brain map through a brain map generation tool, and further may display the initial brain map on a designated page according to the target display parameter to obtain a target brain map, so that a brain map required by a user may be obtained.
Optionally, after the step 106, the following steps may be further included:
a1, acquiring target identity information;
a2, determining target authority information corresponding to the target identity information according to a preset mapping relation between the identity information and the authority information;
and A3, operating the target brain graph according to the target authority information.
Wherein, the identity information may be at least one of the following: a character string, a fingerprint image, a face image, a fingerprint image, a palm print image, an electroencephalogram, an electrocardiogram, and the like, without limitation. The rights information may be at least one of: refer, modify, delete, add, etc., without limitation. The electronic device can pre-store a mapping relation between preset identity information and permission information, and in specific implementation, the electronic device can acquire target identity information, determine target permission information corresponding to the target identity information according to the mapping relation between the preset identity information and the permission information, and operate a target brain graph according to the target permission information.
Further optionally, the step a3, performing an operation on the target brain graph according to the target permission information, may include the following steps:
a31, obtaining target touch parameters;
a32, determining a target operation instruction corresponding to the target touch parameter according to a mapping relation between preset touch parameters and operation instructions;
a33, acquiring an operation instruction set corresponding to the target authority information;
and A34, when the operation instruction set comprises the target operation instruction, executing corresponding operation on the target brain graph according to the target operation instruction.
In an embodiment of the present application, the touch parameter may be at least one of the following: the touch track generated by the touch display screen, the touch strength of the touch display screen, the touch area of the touch display screen, the touch duration of the touch display screen, the touch frequency of the touch display screen, and the like are not limited herein, for example, the touch track may be a track where the touch strength is greater than a preset strength, the touch strength may be a strength where the touch duration is greater than the preset duration, the touch area may be a touch area where the touch strength is within a preset range, and the like, and the limitation is not limited herein, where the preset strength, the preset duration, and the preset range may all be set by a user or default.
In specific implementation, the mapping relationship between the preset touch parameter and the operation instruction may be pre-stored in the electronic device. Furthermore, the electronic device may obtain the target touch parameter, and determine a target operation instruction corresponding to the target touch parameter according to a mapping relationship between a preset touch parameter and the operation instruction. The electronic device can acquire an operation instruction set corresponding to the target authority information, and when the operation instruction set includes the target operation instruction, corresponding operation is performed on the target brain graph according to the target operation instruction.
Optionally, when the target brain map includes the sequence brain map, after the step 106 generates the target brain map according to the attribute information of the at least one test file, the method may further include the following steps:
b1, determining the content capacity corresponding to each brain map in the sequence brain map to obtain a plurality of content capacities;
b2, determining target playing parameters according to the content capacities;
b3, playing the sequence brain graph according to the target playing parameters.
The target brain map may be a sequence brain map, the sequence brain map may include a plurality of brain maps, the plurality of brain maps may be different forms of a brain map, or may be understood as brain maps of different parts of a case, each part corresponding to a brain map. The playback parameters may include at least one of: the playing time, the playing volume, the playing speed, etc., which are not limited herein.
In a specific implementation, the electronic device may determine a content capacity corresponding to each brain map in the sequence brain map to obtain a plurality of content capacities, where the content capacities may be understood as the number of characters of the brain map, the number of layers of a frame of the brain map, the size of the brain map picture, and the like, and are not limited herein. The playing parameters are different according to different content capacities, so that the electronic equipment can determine the target playing parameters according to the content capacities, can play the sequence brain graph according to the target playing parameters, can adjust the playing parameters according to the characteristics of the brain graph, and is beneficial to improving user experience.
Further optionally, the step B2, determining the target playing parameter according to the plurality of content capacities, may include the following steps:
b21, determining the content capacity ratio among the plurality of content capacities;
b22, determining the playing time length of each brain graph in the sequence brain graph according to the content capacity ratio;
b23, determining the playing time sequence of the sequence brain graph according to the playing duration, and taking the playing time sequence as the target playing parameter.
The electronic equipment can determine content capacity ratios among a plurality of content capacities, further determine the playing time length of each brain graph in the sequence brain graph according to the content capacity ratios, wherein the ratio is large, the playing time length is long, and the ratio is small, the playing time length is long, further, as the sequence brain graph has the playing sequence, the playing time sequence of the sequence brain graph can be determined according to the playing time length, the playing time sequence is used as a target playing parameter, and the playing parameter can be adjusted according to the characteristics of the brain graph.
Optionally, before the step 101, the following steps may be included:
s1, acquiring a target fingerprint image;
s2, determining a target image quality evaluation value of the target fingerprint image;
s3, when the target image quality evaluation value is larger than a preset threshold value, matching the target fingerprint image with a preset fingerprint template;
and S4, executing the step of obtaining the target test case when the target fingerprint image is successfully matched with the preset fingerprint template.
S5, when the target image quality evaluation value is smaller than or equal to the preset threshold value, determining a target image enhancement parameter corresponding to the target image quality evaluation value;
s6, carrying out image enhancement processing on the target fingerprint image according to the target image enhancement parameter to obtain a first fingerprint image;
s7, matching the first fingerprint image with the preset fingerprint template;
and S8, executing the step of obtaining the target test case when the first fingerprint image is successfully matched with the preset fingerprint template.
The preset fingerprint template and the preset threshold value can be stored in the electronic device in advance. The preset threshold may be set by the user or by default. In a specific implementation, the electronic device may acquire a target fingerprint image, and may perform image quality evaluation on the target fingerprint image by using at least one image quality evaluation index to obtain a target image quality evaluation value, where the image quality evaluation index may include at least one of: signal-to-noise ratio, entropy, sharpness, edge preservation, mean square error, mean gradient, etc., and is not limited thereto. Further, the electronic device may match the target fingerprint image with a preset fingerprint template when the target image quality evaluation value is greater than a preset threshold, and execute step 101 when the target fingerprint image is successfully matched with the preset fingerprint template.
Further, the electronic device may determine a target image enhancement parameter corresponding to the target image quality evaluation value when the target image quality evaluation value is less than or equal to a preset threshold, in this embodiment, the image enhancement parameter may be an image enhancement algorithm and a corresponding image enhancement control parameter, and the image enhancement algorithm may be at least one of: gray scale stretching, wavelet transformation, histogram equalization, Retinex algorithm, etc., which are not limited herein, the image enhancement control parameter is a parameter for controlling the amplitude or effect of image enhancement, and different image enhancement algorithms may correspond to different image enhancement control parameters. The electronic device may further pre-store a mapping relationship between a preset image quality evaluation value and an image enhancement parameter, and determine a target image enhancement parameter corresponding to the target image quality evaluation value according to the mapping relationship. Furthermore, the electronic device can perform image enhancement processing on the target fingerprint image according to the target image enhancement parameter to obtain a first fingerprint image, the electronic device can match the first fingerprint image with the preset fingerprint template, and execute the step 101 when the first fingerprint image is successfully matched with the preset fingerprint template, otherwise, the electronic device can prompt the user to continue inputting the fingerprint image, and therefore the fingerprint identification efficiency can be improved.
Further, the step S2 of determining the target image quality evaluation value of the target fingerprint image may include the following steps:
s21, extracting low-frequency components and high-frequency components of the target fingerprint image;
s22, dividing the low-frequency component into a plurality of areas;
s23, determining the signal-to-noise ratio corresponding to each of the plurality of regions to obtain a plurality of signal-to-noise ratios;
s24, determining an average signal-to-noise ratio and a target mean square error according to the signal-to-noise ratios;
s25, determining a target adjusting coefficient corresponding to the target mean square error;
s26, adjusting the average signal-to-noise ratio according to the target adjustment coefficient to obtain a target signal-to-noise ratio;
s27, determining a first evaluation value corresponding to the target signal-to-noise ratio according to a mapping relation between a preset signal-to-noise ratio and the evaluation value;
s28, determining the target energy ratio of the energy value of the low-frequency component to the energy value of the target fingerprint image;
s29, determining a target low-frequency weight corresponding to the target energy proportion according to a preset mapping relation between the low-frequency energy proportion and the low-frequency weight, and determining a target high-frequency weight according to the target low-frequency weight;
s30, determining the distribution density of the target characteristic points according to the high-frequency components;
s31, determining a second evaluation value corresponding to the target feature point distribution density according to a preset mapping relation between the feature point distribution density and the evaluation value;
and S32, performing weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image.
In specific implementation, the electronic device may perform multi-scale feature decomposition on the target fingerprint image by using a multi-scale decomposition algorithm to obtain a low-frequency component and a high-frequency component, where the multi-scale decomposition algorithm may be at least one of the following: the pyramid transform algorithm, wavelet transform, contourlet transform, non-down-sampling contourlet transform, ridgelet transform, shear wave transform, etc., are not limited herein. Further, the electronic device may divide the low frequency component into a plurality of regions, each region having the same or different area size. The low frequency component reflects the main features of the image, and the high frequency component reflects the detail information of the image.
Furthermore, the electronic device can determine a signal-to-noise ratio corresponding to each of the plurality of regions to obtain a plurality of signal-to-noise ratios, and determine an average signal-to-noise ratio and a target mean square error according to the plurality of signal-to-noise ratios, wherein the signal-to-noise ratio reflects the amount of the image information to a certain extent, and the mean square error can reflect the stability of the image information. The electronic device may pre-store a mapping relationship between a preset mean square error and an adjustment coefficient, and further determine a target adjustment coefficient corresponding to the target mean square error according to the mapping relationship, in this embodiment, a value range of the adjustment coefficient may be-0.15 to 0.15.
Further, the electronic device may adjust the average snr according to a target adjustment coefficient to obtain a target snr, where the target snr is (1+ target adjustment coefficient) × the average snr. The electronic device may pre-store a mapping relationship between a preset signal-to-noise ratio and an evaluation value, and further, may determine a first evaluation value corresponding to the target signal-to-noise ratio according to the mapping relationship between the preset signal-to-noise ratio and the evaluation value.
In addition, the electronic device may pre-store a mapping relationship between a preset low-frequency energy ratio and a low-frequency weight, where the low-frequency energy ratio is an energy ratio between a low-frequency component of the original image and the original image, determine a target energy ratio corresponding to an energy value of the low-frequency component and an energy value of the target fingerprint image, determine a target low-frequency weight corresponding to the target energy ratio according to the mapping relationship between the preset low-frequency energy ratio and the low-frequency weight, and determine a target high-frequency weight according to the target low-frequency weight, where the target low-frequency weight + the target high-frequency weight is 1.
Further, the electronic device may determine a target feature point distribution density from the high-frequency components, where the target feature point distribution density is the total number of feature points/area of the high-frequency components. The electronic device may further pre-store a mapping relationship between a preset feature point distribution density and an evaluation value, further determine a second evaluation value corresponding to the target feature point distribution density according to the mapping relationship between the preset feature point distribution density and the evaluation value, and finally perform a weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight, and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image, which is specifically as follows:
target image quality evaluation value (first evaluation value, target low-frequency weight + second evaluation value, target high-frequency weight)
Therefore, image quality evaluation can be carried out based on two dimensions of the low-frequency component and the high-frequency component of the fingerprint image, and the image quality evaluation value of the image can be accurately obtained, namely the target image quality evaluation value, so that the test safety can be ensured, and the user experience is improved.
It can be seen that, the test case processing method described in the embodiment of the present application obtains a target test case, where the target test case includes at least one test file, obtains a target display parameter of a brain graph to be generated, determines a target attribute identifier corresponding to the target display parameter according to a mapping relationship between preset display parameters and attribute identifiers, obtains an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, each attribute information corresponds to one attribute identifier, screens the attribute information set according to the target attribute identifier to obtain the attribute information of the at least one test file, generates a target brain graph according to the attribute information of the at least one test file, and the target brain graph is used for displaying the target test case, so that a corresponding brain graph can be generated based on the attribute information of the test file of the test case, the test case is displayed through the brain graph, the management efficiency of the test cases can be improved.
Referring to fig. 2, fig. 2 is a schematic flowchart of a test case processing method applied to an electronic device according to an embodiment of the present application, where as shown in the figure, the test case processing method includes:
201. obtaining a target test case, wherein the target test case comprises at least one test file.
202. And acquiring target display parameters of the brain picture to be generated.
203. And determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier.
204. And acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier.
205. And screening the attribute information set according to the target attribute identification to obtain the attribute information of the at least one test file.
206. And generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case.
207. And acquiring target identity information.
208. And determining target authority information corresponding to the target identity information according to a preset mapping relation between the identity information and the authority information.
209. And operating the target brain graph according to the target authority information.
The detailed description of the steps 201 to 209 may refer to the corresponding steps described in fig. 1, and is not repeated herein.
It can be seen that, the test case processing method described in the embodiment of the present application obtains a target test case, where the target test case includes at least one test file, obtains a target display parameter of a brain graph to be generated, determines a target attribute identifier corresponding to the target display parameter according to a mapping relationship between a preset display parameter and an attribute identifier, obtains an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, each attribute information corresponds to one attribute identifier, screens the attribute information set according to the target attribute identifier to obtain the attribute information of the at least one test file, generates a target brain graph according to the attribute information of the at least one test file, where the target brain graph is used to display the target test case, obtains target identity information, and generates the target brain graph according to the mapping relationship between the preset identity information and authority information, the target authority information corresponding to the target identity information is determined, and the target brain graph is operated according to the target authority information, so that on one hand, the corresponding brain graph can be generated based on the attribute information of the test file of the test case, the test case can be displayed through the brain graph, the management efficiency of the test case can be improved, on the other hand, different operations can be implemented according to the user authority, and the management efficiency of the test case is further improved.
In accordance with the foregoing embodiments, please refer to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in the drawing, the electronic device includes a processor, a memory, a communication interface, and one or more programs, the one or more programs are stored in the memory and configured to be executed by the processor, and in an embodiment of the present application, the programs include instructions for performing the following steps:
acquiring a target test case, wherein the target test case comprises at least one test file;
acquiring target display parameters of a brain picture to be generated;
determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier;
acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
screening the attribute information set according to the target attribute identification to obtain attribute information of the at least one test file;
and generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case.
It can be seen that, in the electronic device described in the embodiment of the present application, a target test case is obtained, where the target test case includes at least one test file, a target display parameter of a brain graph to be generated is obtained, a target attribute identifier corresponding to the target display parameter is determined according to a mapping relationship between preset display parameters and attribute identifiers, an attribute information set of the at least one test file is obtained, the attribute information set includes a plurality of attribute information, each attribute information corresponds to one attribute identifier, the attribute information set is screened according to the target attribute identifier to obtain attribute information of the at least one test file, a target brain graph is generated according to the attribute information of the at least one test file, and the target brain graph is used for displaying the target test case, so that a corresponding brain graph can be generated based on the attribute information of the test file of the test case, and the test case is displayed through the brain graph, the management efficiency of the test cases can be improved.
Optionally, in the aspect of obtaining the target display parameter of the brain map to be generated, the program includes instructions for performing the following steps:
displaying a plurality of brain graph styles on a display interface;
determining a target brain graph style selected by a user from the plurality of brain graph styles;
and obtaining the display parameters of the target brain graph style to obtain the target display parameters of the brain graph to be generated.
Optionally, in the aspect of generating the target brain graph according to the attribute information of the at least one test file, the program includes instructions for performing the following steps:
converting the attribute information of the at least one test file into an initial brain map by a brain map generating tool;
and displaying the initial brain map on a designated page according to the target display parameters to obtain the target brain map.
Optionally, after the aspect of generating the target brain graph according to the attribute information of the at least one test file, the program further includes instructions for performing the following steps:
acquiring target identity information;
determining target authority information corresponding to the target identity information according to a preset mapping relation between the identity information and the authority information;
and operating the target brain graph according to the target authority information.
Optionally, in terms of the operating the target brain graph according to the target permission information, the program includes instructions for performing the following steps:
acquiring a target touch parameter;
determining a target operation instruction corresponding to the target touch parameter according to a preset mapping relation between the touch parameter and the operation instruction;
acquiring an operation instruction set corresponding to the target authority information;
and when the operating instruction set comprises the target operating instruction, executing corresponding operation on the target brain graph according to the target operating instruction.
Optionally, when the target brain map includes a sequence brain map, after the aspect of generating the target brain map according to the attribute information of the at least one test file, the program further includes instructions for performing the following steps:
determining the content capacity corresponding to each brain map in the sequence brain map to obtain a plurality of content capacities;
determining a target playing parameter according to the plurality of content capacities;
and playing the sequence brain graph according to the target playing parameters.
Optionally, in the aspect of determining the target playing parameter according to the plurality of content capacities, the program includes instructions for performing the following steps:
determining a content capacity fraction between the plurality of content capacities;
determining the playing time length of each brain graph in the sequence brain graph according to the content capacity ratio;
and determining the playing time sequence of the sequence brain graph according to the playing duration, and taking the playing time sequence as the target playing parameter.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Fig. 4 is a block diagram of functional unit components of a test case processing apparatus 400 involved in the embodiments of the present application. The test case processing apparatus 400, the apparatus 400 comprising: a first acquisition unit 401, a second acquisition unit 402, a determination unit 403, a third acquisition unit 404, a filtering unit 405, and a generation unit 406, wherein,
the first obtaining unit 401 is configured to obtain a target test case, where the target test case includes at least one test file;
the second obtaining unit 402 is configured to obtain a target display parameter of a brain image to be generated;
the determining unit 403 is configured to determine, according to a mapping relationship between preset display parameters and attribute identifiers, a target attribute identifier corresponding to the target display parameter;
the third obtaining unit 404 is configured to obtain an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
the screening unit 405 is configured to screen the attribute information set according to the target attribute identifier to obtain attribute information of the at least one test file;
the generating unit 406 is configured to generate a target brain graph according to the attribute information of the at least one test file, where the target brain graph is used to display the target test case.
It can be seen that, the test case processing apparatus described in the embodiment of the present application obtains a target test case, where the target test case includes at least one test file, obtains a target display parameter of a brain graph to be generated, determines a target attribute identifier corresponding to the target display parameter according to a mapping relationship between preset display parameters and attribute identifiers, obtains an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, each attribute information corresponds to one attribute identifier, screens the attribute information set according to the target attribute identifier to obtain the attribute information of the at least one test file, generates a target brain graph according to the attribute information of the at least one test file, and the target brain graph is used for displaying the target test case, so that a corresponding brain graph can be generated based on the attribute information of the test file of the test case, the test case is displayed through the brain graph, the management efficiency of the test cases can be improved.
Optionally, in the aspect of acquiring the target display parameter of the brain image to be generated, the second acquiring unit 402 is specifically configured to:
displaying a plurality of brain graph styles on a display interface;
determining a target brain graph style selected by a user from the plurality of brain graph styles;
and obtaining the display parameters of the target brain graph style to obtain the target display parameters of the brain graph to be generated.
Optionally, in respect that the target brain graph is generated according to the attribute information of the at least one test file, the generating unit 403 is specifically configured to:
converting the attribute information of the at least one test file into an initial brain map by a brain map generating tool;
and displaying the initial brain map on a designated page according to the target display parameters to obtain the target brain map.
Optionally, the apparatus 400 is further specifically configured to perform the following operations:
acquiring target identity information;
determining target authority information corresponding to the target identity information according to a preset mapping relation between the identity information and the authority information;
and operating the target brain graph according to the target authority information.
Optionally, in terms of the operating the target brain map according to the target permission information, the apparatus 400 is specifically configured to:
acquiring a target touch parameter;
determining a target operation instruction corresponding to the target touch parameter according to a preset mapping relation between the touch parameter and the operation instruction;
acquiring an operation instruction set corresponding to the target authority information;
and when the operating instruction set comprises the target operating instruction, executing corresponding operation on the target brain graph according to the target operating instruction.
Optionally, when the target brain map includes the sequence brain map, after the target brain map is generated according to the attribute information of the at least one test file, the apparatus 400 is further specifically configured to perform the following operations:
determining the content capacity corresponding to each brain map in the sequence brain map to obtain a plurality of content capacities;
determining a target playing parameter according to the plurality of content capacities;
and playing the sequence brain graph according to the target playing parameters.
Optionally, in the aspect of determining the target playing parameter according to the plurality of content capacities, the apparatus 400 is specifically configured to:
determining a content capacity fraction between the plurality of content capacities;
determining the playing time length of each brain graph in the sequence brain graph according to the content capacity ratio;
and determining the playing time sequence of the sequence brain graph according to the playing duration, and taking the playing time sequence as the target playing parameter.
It can be understood that the functions of each program module of the test case processing apparatus in this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for test case processing, the method comprising:
acquiring a target test case, wherein the target test case comprises at least one test file;
acquiring target display parameters of a brain picture to be generated;
determining a target attribute identifier corresponding to the target display parameter according to a preset mapping relation between the display parameter and the attribute identifier;
acquiring an attribute information set of the at least one test file, wherein the attribute information set comprises a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
screening the attribute information set according to the target attribute identification to obtain attribute information of the at least one test file;
and generating a target brain graph according to the attribute information of the at least one test file, wherein the target brain graph is used for displaying the target test case.
2. The method according to claim 1, wherein the obtaining target presentation parameters of the brain map to be generated comprises:
displaying a plurality of brain graph styles on a display interface;
determining a target brain graph style selected by a user from the plurality of brain graph styles;
and obtaining the display parameters of the target brain graph style to obtain the target display parameters of the brain graph to be generated.
3. The method according to claim 1, wherein the generating a target brain map according to the attribute information of the at least one test file comprises:
converting the attribute information of the at least one test file into an initial brain map by a brain map generating tool;
and displaying the initial brain map on a designated page according to the target display parameters to obtain the target brain map.
4. The method according to any one of claims 1-3, wherein after generating the target brain map according to the attribute information of the at least one test file, the method further comprises:
acquiring target identity information;
determining target authority information corresponding to the target identity information according to a preset mapping relation between the identity information and the authority information;
and operating the target brain graph according to the target authority information.
5. The method of claim 4, wherein the operating the target brain graph according to the target permission information comprises:
acquiring a target touch parameter;
determining a target operation instruction corresponding to the target touch parameter according to a preset mapping relation between the touch parameter and the operation instruction;
acquiring an operation instruction set corresponding to the target authority information;
and when the operating instruction set comprises the target operating instruction, executing corresponding operation on the target brain graph according to the target operating instruction.
6. The method according to any one of claims 1-3, wherein when the target brain map comprises a sequence brain map, after the generating the target brain map according to the attribute information of the at least one test file, the method further comprises:
determining the content capacity corresponding to each brain map in the sequence brain map to obtain a plurality of content capacities;
determining a target playing parameter according to the plurality of content capacities;
and playing the sequence brain graph according to the target playing parameters.
7. The method of claim 6, wherein the determining a target playback parameter according to the plurality of content capacities comprises:
determining a content capacity fraction between the plurality of content capacities;
determining the playing time length of each brain graph in the sequence brain graph according to the content capacity ratio;
and determining the playing time sequence of the sequence brain graph according to the playing duration, and taking the playing time sequence as the target playing parameter.
8. A test case handling apparatus, the apparatus comprising: a first obtaining unit, a second obtaining unit, a determining unit, a third obtaining unit, a screening unit and a generating unit, wherein,
the first obtaining unit is used for obtaining a target test case, and the target test case comprises at least one test file;
the second acquisition unit is used for acquiring target display parameters of the brain picture to be generated;
the determining unit is used for determining a target attribute identifier corresponding to the target display parameter according to a mapping relation between a preset display parameter and an attribute identifier;
the third obtaining unit is configured to obtain an attribute information set of the at least one test file, where the attribute information set includes a plurality of attribute information, and each attribute information corresponds to an attribute identifier;
the screening unit is used for screening the attribute information set according to the target attribute identification to obtain the attribute information of the at least one test file;
the generating unit is used for generating a target brain graph according to the attribute information of the at least one test file, and the target brain graph is used for displaying the target test case.
9. An electronic device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps of the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113312265A (en) * | 2021-06-08 | 2021-08-27 | 富途网络科技(深圳)有限公司 | Application method of test case and related product |
| CN114757156A (en) * | 2022-06-14 | 2022-07-15 | 成都飞机工业（集团）有限责任公司 | Method, device, equipment and medium for compiling aircraft system test instruction |
| CN116304399A (en) * | 2023-05-19 | 2023-06-23 | 建信金融科技有限责任公司 | Visual processing method, device and system for test cases |
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2020
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113312265A (en) * | 2021-06-08 | 2021-08-27 | 富途网络科技(深圳)有限公司 | Application method of test case and related product |
| CN114757156A (en) * | 2022-06-14 | 2022-07-15 | 成都飞机工业（集团）有限责任公司 | Method, device, equipment and medium for compiling aircraft system test instruction |
| CN114757156B (en) * | 2022-06-14 | 2022-10-25 | 成都飞机工业（集团）有限责任公司 | Method, device, equipment and medium for compiling aircraft system test instruction |
| CN116304399A (en) * | 2023-05-19 | 2023-06-23 | 建信金融科技有限责任公司 | Visual processing method, device and system for test cases |
| CN116304399B (en) * | 2023-05-19 | 2023-08-11 | 建信金融科技有限责任公司 | Visual processing method, device and system for test cases |
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