CN113076243B - Method for optimizing automatic testing cost of image recognition - Google Patents
Method for optimizing automatic testing cost of image recognition Download PDFInfo
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- CN113076243B CN113076243B CN202110327965.1A CN202110327965A CN113076243B CN 113076243 B CN113076243 B CN 113076243B CN 202110327965 A CN202110327965 A CN 202110327965A CN 113076243 B CN113076243 B CN 113076243B
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- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000013515 script Methods 0.000 claims abstract description 91
- 239000011159 matrix material Substances 0.000 claims abstract description 10
- 238000012544 monitoring process Methods 0.000 claims 1
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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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Abstract
The invention relates to the field of automatic testing, and discloses a method for optimizing the automatic testing cost of image identification, which comprises the following steps: deploying the test script to a server, sending an instruction to the server from a client, executing the test script by the server, obtaining test result screenshot, obtaining test result original pixel data from the server, and obtaining a conclusion of whether the test is passed or not by comparing the number of bits of R, G, B components of pixel colors of an expected result and an actual result with a pixel matrix. According to the invention, the client side does not need to occupy the physical screen resources of the client side, the client side can send the instructions to a plurality of servers in batches, and the test scripts are executed on the servers concurrently, so that the automatic test efficiency is improved.
Description
Technical Field
The invention relates to the field of automatic testing, in particular to a method for optimizing the automatic testing cost of image identification.
Technical Field
With the development of IT industry, automatic testing is becoming more popular, and testing methods are becoming more diverse. Each automated test technique faces the problem of time cost and physical resource cost occupation. When repeated testing work can be realized through automation and excessive physical resources are needed, the cost can be saved and the initial aim of improving the efficiency is overcome with the automatic testing. The image recognition automatic test is an automatic test method commonly used in the prior art, the test automation is realized by using a control attribute recognition mode, a physical screen of a testing machine is required to be occupied and a large amount of processing resources are consumed in the test process, and the automatic test is arranged when the testing machine is idle in the current common method, so that the test efficiency is reduced.
Disclosure of Invention
Aiming at the defect that excessive resources are occupied during automatic testing in the prior art, the invention provides a method for optimizing the automatic testing cost of image identification.
The invention is specifically realized as follows:
The invention provides a method for optimizing the automatic test cost of image recognition, wherein a client communicates with a server through a network protocol, the client sends a test script and an operation instruction to the server, the server receives the operation instruction, executes the test script, the server captures an operation result and stores the operation result in a pixel data text form, the server stores the pixel data text of all the operation result captures into the test result, the server returns the test result to the client, the client compares the test result with a preset comparison file, and whether the test passes or not is judged according to the comparison result.
Further, the method for optimizing the image recognition automatic test cost specifically comprises the following steps:
step S1: the client side remotely deploys the test script to the server and sends an instruction for executing the test script to the server along with a message;
step S2: the server receives the instruction, executes the test script, captures an operation result, saves the operation result in a pixel data text form, and saves the pixel data text of all the operation result captures to the test result;
Step S3: the client acquires the execution state of the test script of the server at intervals, and when the client acquires the end of script execution, the client applies for acquiring a test result from the server;
step S4: the server transmits the test result to the client in the form of pixel data;
step S5: the client compares the received test result with pixel data of a comparison file preset at the client: if the two are the same, the test is passed; if the two are different, the test fails.
In order to better realize the invention, further, the client side simultaneously controls a plurality of servers, and the servers simultaneously run the test scripts.
Further, the test script in step S1 includes a functional script composed of a plurality of case texts and a main script for encapsulating the functional script, and when the server runs the test script, the server searches the functional script according to a path in the main script and executes the functional script in sequence.
Further, in the step S2, regardless of success or failure of running the case text, a screenshot, that is, a slice is saved, is saved for the running result of each case text; and finally, integrating the running results of all the case texts into a complete test result corresponding to the test script.
Further, the case text name is consistent with the pixel data text name.
Further, the text of the pixel data in the step S2 includes R, G, B component bits of the pixel array and a pixel matrix.
Further, the method for obtaining the execution state of the test script of the server in step S3 monitors the test script process for the server at a specified time interval for the client, and if the client monitors the test script process of the server, the test is not ended; and if the client does not monitor the test script process of the server, the test is ended.
Further, the comparing in step S5 specifically includes:
Step S5.1: comparing R, G, B component bit numbers in the two texts with the pixel matrix, if R, G, B component bit numbers are inconsistent during comparison, not comparing the pixel matrix, and directly judging that the two texts are inconsistent; if the number of R, G, B component bits is consistent during comparison, then comparing the pixel matrixes, and judging whether the two texts are consistent or not through the comparison of the pixel matrixes; if the comparison is successful, not recording; if the comparison fails, the text name is recorded into a designated text c;
step S5.2: when all the text comparison of the test result is completed, the whole comparison result is obtained;
Step S5.3: judging whether the text c has a record or not, and if the text c does not have the record, outputting a test passing prompt; if the record exists, outputting a test failure prompt.
Compared with the prior art, the invention has the following advantages:
(1) The client and the server are in one-to-many relation, the client can send instructions to a plurality of servers at the same time, and the servers execute a plurality of UI automatic test tasks simultaneously, so that the test execution efficiency and the flexibility are improved.
(2) Script operation and result storage of the automatic test are both put on a server, and a client only performs simple result comparison, so that occupation of client resources is reduced, and release of the client resources is realized.
Drawings
FIG. 1 is a flow chart of the present invention;
Fig. 2 is a flow chart of the business of the present invention.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it should be understood that the described embodiments are only some embodiments of the present invention, but not all embodiments, and therefore should not be considered as limiting the scope of protection. All other embodiments, which are obtained by a worker of ordinary skill in the art without creative efforts, are within the protection scope of the present invention based on the embodiments of the present invention.
Example 1:
the embodiment provides a method for optimizing the automatic test cost of image recognition, which is shown in fig. 1, and comprises the following steps:
Step S1: configuring a client and a server based on a VNC communication protocol, sending a test script to the server by the client, and sending a test script execution instruction to the server, wherein the instruction can be executed once or multiple times, for example: 1 execution instruction is sent to the server, 2 execution instructions and 3 … … execution instructions are sent to the server, and the like;
Step S2: after receiving the instruction, the server executes the test script according to the instruction times, for example: when receiving the execution instruction for 1 time, the server executes the test script once to finish running; when the multiple execution instructions are received, the server circularly executes the script until the execution times reach the received instruction times, finishes running the script, performs screenshot on the running result each time, and stores the test result according to the test times in a slicing way, for example: the first test result is stored in a folder 1, the second test result is stored in a folder 2 … …, and the nth test result is stored in a folder n;
Step S4: the client acquires the execution state of the test script of the server at intervals, and when the execution of the script is ended, the client applies for acquiring a test result from the server;
step S5: the server executes the test script for n times, namely, transmits n test results to the client;
step S6: after receiving the test results, the client side respectively compares the test results with the comparison file, and respectively outputs whether the test passes or not after the comparison is completed.
Example 2:
The present embodiment deploys a plurality of test scripts to a server on the basis of embodiment 1, including the steps of:
step S1: configuring a client and a server based on a VNC communication protocol, wherein the client presets a comparison file 1 and a comparison file 2 … … and a comparison file n;
Step S2: the client side remotely deploys the test script 1 and the test script 2 … … to the server, and sends a test script execution instruction to the server, and after receiving the instruction, the server sequentially executes the scripts, for example: the server executes the test script 1 and the test script 2 … … and the test script n in sequence; and screenshot is carried out on the operation result, and the test result is saved according to the test script, for example: the test script 1 test result is stored in a folder 1, the test script 2 test result is stored in a folder 2 … … test script n test result is stored in a folder n;
step S3: the client acquires the execution state of the test script of the server at intervals, and when all script execution ends are acquired, the client applies for acquiring a test result from the server;
step S4: the server executes n test scripts, namely, n test results are transmitted to the client;
Step S5: after receiving the test result, the client side respectively compares with the comparison file 1 and the comparison file 2 … … and the comparison file n, and respectively outputs whether the test passes or not after the comparison is completed.
Example 3:
the embodiment extends the client and the server to one-to-many connection based on embodiment 1, as shown in fig. 2, and specifically includes the following steps:
step S1: the client is connected with the server 1 and the server 2 … … and the server n, remotely controls the server, and presets the comparison file;
Step S2: the client side remotely deploys the test script to the server, the client side sends a test script execution instruction to the server, the server 1 and the server 2 … … server n execute the test script, and screenshot is saved on the running result;
Step S3: the client side obtains the execution states of the test scripts of the server 1 and the server 2 … … and the server n at intervals, and when the execution of the test scripts of the server 1 is finished, the client side applies for obtaining the test result to the server 1, and continues to obtain the execution states of the test scripts for the servers which do not finish the execution of the test scripts until the execution of all the servers is finished;
Step S4: the server 1 transmits the test result to the client, the client receives the test result and then compares the test result with the comparison file, and the output test is passed or not after the comparison is completed; the server 2 transmits a test result to the client, the client also compares the test result with the comparison file after receiving the test result, and outputs whether the test is passed or not after the comparison is completed; until the comparison of the test results transmitted by all the servers is completed.
Example 4:
the embodiment expands the client and the server into one-to-many based on embodiment 3 and as shown in fig. 2, and executes different test scripts, specifically including the following steps:
Step S1: the client is connected with the server 1 and the server 2 … … and the server n, the server is controlled by the client in a remote mode, and the client presets a comparison file 1 and a comparison file 2 … … and a comparison file n;
Step S2: the method comprises the steps that a client side remotely deploys a test script 1 to a server 1, remotely deploys a test script 2 to a server 2, remotely deploys a … … test script n to a server n, the client side sends a test script execution instruction to the server, the server 1 and the server 2 … … server n respectively execute the test script 1 and the test script 2 … … test script n, and screenshot is saved for operation results respectively;
Step S3: the client side obtains the execution states of the test scripts of the server 1 and the server 2 … … and the server n at intervals, and when the execution of the test scripts of the server 1 is finished, the client side applies for obtaining the test result to the server 1, and continues to obtain the execution states of the test scripts for the servers which do not finish the execution of the test scripts until the execution of all the servers is finished;
Step S4: the server 1 transmits the test result to the client, the client receives the test result and then compares the test result with the comparison file 1, and the test 1 is output after the comparison is completed; the server 2 transmits the test result to the client, the client compares the test result with the comparison file 2 after receiving the test result, and outputs whether the test 2 passes or not after the comparison is completed until the comparison of the test results transmitted by all the servers is completed.
Example 5:
This example was further optimized on the basis of examples 1-4, and specifically:
(1) The comparison file corresponds to the test script one by one, for example: comparing the test result of the test script 1 with the comparison file 1;
(2) The text names of the test results are in one-to-one correspondence with the case text names, for example: case text name a1, test result text name a1;
(3) Comparing the a1 text of the test result with the a1 text of the comparison file, specifically comparing R, G, B component digits in the two files with the pixel matrix, if the R, G, B component digits are inconsistent during comparison, not comparing the pixel matrix, and directly judging that the two files are inconsistent; if the number of R, G, B component bits is consistent during comparison, then comparing the pixel matrixes, and judging whether the two files are consistent or not through the comparison of the pixel matrixes. If the comparison is successful, not recording; if the comparison fails, recording the a1 file name into a designated text c;
(4) When all texts are compared with each other under the test result, the whole comparison is completed;
(5) Judging whether the text c has a record or not, and if the text c does not have the record, outputting a test to pass; if the record exists, outputting a test failure;
(6) Obtaining a case text corresponding to the failure through comparing the a1 text names which are recorded in the text c, and searching the execution log positioning problem of the case text on the server.
Term interpretation: the pixel array, each image can be converted into a three-dimensional array. The method comprises the steps of including coordinates of an image and R (Red), G (Green) and B (Blue) components, wherein each component corresponds to a two-dimensional matrix array respectively.
Claims (6)
1. The method for optimizing the automatic test cost of the image recognition is characterized in that a local operation environment client communicates with a server through a network protocol, the client sends a test script and an operation instruction to the server, the server receives the operation instruction and executes the test script, the server captures an operation result and stores the operation result in a pixel data text form, the server stores the pixel data text of all the operation result captures into a test result, the server returns the test result to the client, the client compares the test result with a preset comparison file, and whether the test passes or not is judged according to the comparison result; the client side simultaneously controls a plurality of servers, and the servers simultaneously run test scripts;
the method specifically comprises the following steps:
step S1: the client side remotely deploys the test script to the server and sends an instruction for executing the test script to the server along with a message;
step S2: the server receives the instruction, executes the test script, captures an operation result, saves the operation result in a pixel data text form, and saves the pixel data text of all the operation result captures to the test result;
Step S3: the client acquires the execution state of the test script of the server at intervals, and when the client acquires the end of script execution, the client applies for acquiring a test result from the server;
step S4: the server transmits the test result to the client in the form of pixel data;
Step S5: the client compares the received test result with pixel data of a comparison file preset at the client: if the two are the same, the test is passed; if the two are different, the test fails;
The step S5 specifically includes:
step S5.1: comparing R, G, B component bit numbers in the two texts with the pixel matrix, if R, G, B component bit numbers are inconsistent during comparison, not comparing the pixel matrix, and directly judging that the two texts are inconsistent; if the number of R, G, B component bits is consistent during comparison, then comparing the pixel matrixes, and judging whether the two texts are consistent or not through the comparison of the pixel matrixes; if the comparison is successful, not recording; if the comparison fails, the text name is recorded into a designated text c;
step S5.2: when all the text comparison of the test result is completed, the whole comparison result is obtained;
Step S5.3: judging whether the text c has a record or not, and if the text c does not have the record, outputting a test passing prompt; if the record exists, outputting a test failure prompt.
2. The method for optimizing automated testing costs of image recognition according to claim 1, wherein the test scripts in step S1 include a function script composed of a plurality of case texts and a main script for encapsulating the function script, and the server searches the function script according to a path in the main script and sequentially executes the function script when running the test script.
3. The method for optimizing the automated testing cost of image recognition according to claim 2, wherein in the step S2, regardless of the success or failure of running the case text, a screenshot, that is, a slice is saved for each running result of the case text; and finally, integrating the running results of all the case texts into a complete test result corresponding to the test script.
4. A method of optimizing automated test costs for image recognition as recited in claim 3, wherein the case text name is consistent with the pixel data text name.
5. The method for optimizing automated test costs of image recognition according to claim 4, wherein the text of the pixel data in step S2 includes a number of R, G, B component bits of the pixel array and a pixel matrix.
6. The method for optimizing the automated testing cost of image recognition according to claim 5, wherein the step S3 is a method for acquiring the execution state of the test script of the server, monitoring the test script process for the server at a specified time interval for the client, and if the client monitors the test script process of the server, indicating that the test is not finished; and if the client does not monitor the test script process of the server, the test is ended.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1832433A (en) * | 2005-03-08 | 2006-09-13 | 华为技术有限公司 | Distribution structure test system and testing method of the test system |
| CN101252471A (en) * | 2008-03-20 | 2008-08-27 | 中兴通讯股份有限公司 | Distributed automatization test system and method |
| CN102222042A (en) * | 2011-06-28 | 2011-10-19 | 北京新媒传信科技有限公司 | Automatic software testing method based on cloud computing |
| CN103729285A (en) * | 2012-10-11 | 2014-04-16 | 腾讯科技（深圳）有限公司 | Method, device and system for testing web page |
| CN104536888A (en) * | 2014-12-24 | 2015-04-22 | 网易（杭州）网络有限公司 | Game testing method and system for mobile devices |
| CN105335293A (en) * | 2015-11-30 | 2016-02-17 | 努比亚技术有限公司 | Automatic testing system and method based on parallel ports |
| CN106789393A (en) * | 2016-11-16 | 2017-05-31 | 武汉烽火网络有限责任公司 | A kind of CS frameworks communication equipment automatization test system and method |
| CN107015908A (en) * | 2017-03-31 | 2017-08-04 | 广州慧睿思通信息科技有限公司 | A kind of computer application software test system and method |
| CN108509343A (en) * | 2018-04-04 | 2018-09-07 | 浙江小泰科技有限公司 | Automated testing method based on image recognition technology and system |
| CN109408362A (en) * | 2018-08-21 | 2019-03-01 | 中国平安人寿保险股份有限公司 | Application compatibility test method, device, system and storage medium |
| CN109857652A (en) * | 2019-01-16 | 2019-06-07 | 深圳壹账通智能科技有限公司 | A kind of automated testing method of user interface, terminal device and medium |
| CN109885480A (en) * | 2019-01-14 | 2019-06-14 | 珠海金山网络游戏科技有限公司 | A kind of automatic interface compatibility test method and device based on debugging bridge |
| CN110347587A (en) * | 2019-05-30 | 2019-10-18 | 平安银行股份有限公司 | APP compatibility test method, device, computer equipment and storage medium |
| CN110399291A (en) * | 2019-06-20 | 2019-11-01 | 平安普惠企业管理有限公司 | User Page test method and relevant device based on image recognition |
| CN111522749A (en) * | 2020-04-26 | 2020-08-11 | 北京三快在线科技有限公司 | Page testing method and device, readable storage medium and electronic equipment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200034279A1 (en) * | 2018-07-24 | 2020-01-30 | Sap Se | Deep machine learning in software test automation |
| US11099972B2 (en) * | 2018-11-19 | 2021-08-24 | Microsoft Technology Licensing, Llc | Testing user interfaces using machine vision |
-
2021
- 2021-03-26 CN CN202110327965.1A patent/CN113076243B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1832433A (en) * | 2005-03-08 | 2006-09-13 | 华为技术有限公司 | Distribution structure test system and testing method of the test system |
| CN101252471A (en) * | 2008-03-20 | 2008-08-27 | 中兴通讯股份有限公司 | Distributed automatization test system and method |
| CN102222042A (en) * | 2011-06-28 | 2011-10-19 | 北京新媒传信科技有限公司 | Automatic software testing method based on cloud computing |
| CN103729285A (en) * | 2012-10-11 | 2014-04-16 | 腾讯科技（深圳）有限公司 | Method, device and system for testing web page |
| CN104536888A (en) * | 2014-12-24 | 2015-04-22 | 网易（杭州）网络有限公司 | Game testing method and system for mobile devices |
| CN105335293A (en) * | 2015-11-30 | 2016-02-17 | 努比亚技术有限公司 | Automatic testing system and method based on parallel ports |
| CN106789393A (en) * | 2016-11-16 | 2017-05-31 | 武汉烽火网络有限责任公司 | A kind of CS frameworks communication equipment automatization test system and method |
| CN107015908A (en) * | 2017-03-31 | 2017-08-04 | 广州慧睿思通信息科技有限公司 | A kind of computer application software test system and method |
| CN108509343A (en) * | 2018-04-04 | 2018-09-07 | 浙江小泰科技有限公司 | Automated testing method based on image recognition technology and system |
| CN109408362A (en) * | 2018-08-21 | 2019-03-01 | 中国平安人寿保险股份有限公司 | Application compatibility test method, device, system and storage medium |
| CN109885480A (en) * | 2019-01-14 | 2019-06-14 | 珠海金山网络游戏科技有限公司 | A kind of automatic interface compatibility test method and device based on debugging bridge |
| CN109857652A (en) * | 2019-01-16 | 2019-06-07 | 深圳壹账通智能科技有限公司 | A kind of automated testing method of user interface, terminal device and medium |
| CN110347587A (en) * | 2019-05-30 | 2019-10-18 | 平安银行股份有限公司 | APP compatibility test method, device, computer equipment and storage medium |
| CN110399291A (en) * | 2019-06-20 | 2019-11-01 | 平安普惠企业管理有限公司 | User Page test method and relevant device based on image recognition |
| CN111522749A (en) * | 2020-04-26 | 2020-08-11 | 北京三快在线科技有限公司 | Page testing method and device, readable storage medium and electronic equipment |
Non-Patent Citations (3)
| Title |
|---|
| Invariant-Based Automatic Testing of Modern Web Applications;Ali Mesbah 等;《IEEE Transactions on Software Engineering 》;20110310;第38卷(第1期);35-53 * |
| 图像识别云服务自动测试系统设计与实现;薛玉磊;《中国优秀硕士学位论文全文数据库 信息科技辑》;20190815(第8期);I138-867 * |
| 基于无线通信和图像识别的馈线自动化现场自动测试;刘彬 等;《无线电通信技术》;20180302;第44卷(第2期);202-206 * |
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