CN110515835A - A kind of test method based on machine vision and DOM tree structure - Google Patents
A kind of test method based on machine vision and DOM tree structure Download PDFInfo
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Abstract
The test method based on machine vision and DOM tree structure that the invention discloses a kind of includes the following steps: S100, feature extraction and selection, identifies the feature of object element in test page；S200, the feature according to object element classify to the element in the page with similar characteristics, are extensive, obtaining extensive element；S300, it is tested, and is recorded automatically according to extensive element.The present invention can greatly reduce testing cost, testing time, can increase the robustness of testing scheme and automatically generating for testing scheme, and process robot understands the active of user behavior.It invention can be widely used in for webpage testing process, process robot etc., after the present invention, tester will not be again because of update of the developer for webpage, and need further to update test script, while primary recording or a script can operate all similar elements.Meanwhile there is the function of actively understanding for user behavior in process robot.
Description
Technical field
The present invention relates to webpage measuring technologies, more particularly to a kind of test side based on machine vision and DOM tree structure
Method.
Background technique
Required in software instantly, webpage, mobile terminal application and development or the automation of test it is higher and higher, for user's row
It is self-evident for the importance of understanding.Such as procedure robot automatic test field in other words, for example, in webpage
Automatic test field has had many test softwares that can record the operation of tester, can be continually performed later.
But the step of problem is, has during the test can " extensive ", for example for, North China 1, East China 2 ... ...,
These servers are of equal value for test process, while being also all is that need are to be tested, then being easy to propose one
Problem, i.e., can be when tester selects this server of North China 1, test platform or tool, it is possible to understand that this choosing
Select and extensive, so when test platform or tool go to this step, can be randomly selected other places server or
All servers of person's concurrent testing are so recorded or are write time of script to save tester, increase the complete of test
Face property.
In order to realize the target of this " extensive ", applicant has used machine vision and DOM tree structure to analyze two technologies
Realize this target, machine vision primarily in identification webpage icon, button characteristics of image, carry out similar
Match, and dom tree analysis method is that the structure of the position of object element and dom tree is found in HTML or XML by webpage
It can extensive element with dvielement.
Meanwhile it is to increase robustness that another, which is not so obvious benefit, i.e. fault-tolerant ability, is especially being surveyed
Examination field.Exactly testing after version iteration can continue, for example, in original testing tool or test script institute
In the test process of progress, 1 server of North China is offline, then entire test will be interrupted, causes the testing time to waste, simultaneously
Be also possible to cause the experience of client the unnecessary loss such as to decline, at the same tester's modification or write from the beginning script or
Recording is inevitable.And other server can be then automatically selected using the technology in the present invention, while can remain to survey in log recording
Examination personnel judge that this is normal condition or mistake, thus greatly improve testing efficiency (such as midnight this tester
Member is without stay-at-home situation aside), and reduce the workload of tester.
Summary of the invention
In view of the above drawbacks of the prior art, a kind of based on machine view the technical problem to be solved by the present invention is to propose
Feel the test method with DOM tree structure, there is " extensive " property, webpage testing efficiency can be greatly improved.
To achieve the above object, the test method based on machine vision and DOM tree structure that the present invention provides a kind of, including
Following steps:
S100, feature extraction and selection identify the feature of object element in test page；
S200, the feature according to object element, classify to the element with similar characteristics, are extensive, and extensive member is obtained
Element；
S300, it is tested, and is recorded automatically according to extensive element.
Preferably, in S100, including two ways, i.e. S110, machine vision method and S120, dom tree analysis method, two
Kind method can be carried out simultaneously, mutually be compared, can also be with single use；
The use environment of machine vision method is that webpage is clear, in the case where each icon edge clear, passes through knowledge
The general shape of other object element looks for similar icon either button in certain area, extensive to achieve the purpose that；
And dom tree analysis method is carried out by the structure of dom tree, analysis abide by it is assumed hereinafter that:
Assuming that 1. can be extensive same dvielement level it is centainly similar；
Assuming that 2. when same dvielement all finds nearest same father's element, non-same dvielement is not centainly this father member
Element.Under the premise of the two hypothesis, so that it may same dvielement can be found, achieved the purpose that extensive.
Preferably, S110, machine vision method, include the following steps:
S111, selection target element, this object element is icon or button, and identifies the feature of object element, for example just
Just identification box area, tilt angle, surplus etc. if frame；Its center of circle, radius are just identified for circle；Its coke is just identified for ellipse
Point, long axis, short axle etc.；
The edge of all elements in S112, the identification page；
S113, according to object element feature, all elements are screened in screening, obtain and object element similar characteristics
Graphic element obtains extensive element.
Wherein, S111-S112 can be realized by existing OCR technique, naturally it is also possible to be realized by following technology:
The image of test page is become bianry image first by the page edge of target by S112.1, because in this way may be used
To reinforce the important feature of image, the edge of icon or button is preferably detected, edge, the public affairs of edge detection are then detected
Formula:
Wherein:
Gx is horizontal gradient, and Gy: vertical gradient, Edge_Gradient (G) are edge gradient, and Angle (θ) inclines for edge
Angle；It can detecte edge all in page-out by this step, but also contain text edge；
S112.2 selects the edge of acquisition according to the feature of object element.If object element is rectangular boxes,
And know the length and width of this box, and a length of horizontal, width is vertical, therefore by (wide to unhorizontal, out of plumb, length, height
Degree) abnormal edge is filtered, and it is a plurality of straight obtained from so as to remove most text, unconventional edge
The coordinate of line beginning and end；
S112.3 takes intersection point, chooses the intersection point at each edge；
Each intersection point is carried out line by S112.4, chooses the shape similar with object element, then passes through object element
The removals such as area, radius, the Aspect Ratio inconsistent shape of feature therewith, remaining is exactly the same dvielement of object element,
Just object element is carried out good extensive, extensive element is then classified as same class.This method very simple, Er Qiexiao
Rate is very high, but when icon or unconspicuous button feature, it is necessary to dom tree analysis method is required general to obtain
Change result.
S120, dom tree analysis method, include the following steps:
S121, the path for finding object element；
S122, it is found according to the path searched out with the element under level-one path；
S123, incoherent element is rejected, it is extensive to object element progress, obtain extensive element；Rejecting mode is to find
To father's element (classification belonging to upper level element or object element) of object element, then according to same when all being found with dvielement
When one father's element, non-same dvielement is not centainly that this father's member usually excludes uncorrelated element.
The beneficial effects of the present invention are:
The present invention can greatly reduce testing cost, testing time, can increase the robustness and testing scheme of testing scheme
Automatically generate, process robot for user behavior active understand.
It invention can be widely used in for webpage testing process, process robot etc., after the present invention, tester is not
Test script can be needed further to update, while primary recording or one again because of update of the developer for webpage
Script can operate all similar elements.Meanwhile having in process robot for user behavior and actively managing
The function of solution.In use, recorded or the process of script according to normal, can automatic extensive element, automatically generate a series of surveys
Try process or process robot workflow.
Detailed description of the invention
Fig. 1 is test page schematic diagram in specific embodiment.
Fig. 2 is to carry out the schematic diagram after marginalisation to test page in specific embodiment.
Fig. 3 is in specific embodiment to needing to extract interested region after test page marginalisation.
Fig. 4 is the schematic diagram after selecting in specific embodiment edge.
Fig. 5 is the schematic diagram for taking intersection point in specific embodiment to the edge of selection.
Fig. 6 is that rectangular schematic diagram similar with object element is chosen in specific embodiment.
Fig. 7 is DOM tree structure schematic diagram in specific embodiment.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples:
Currently, the main prior art for carrying out page test is as follows:
1、Selenium
Selenium may be most popular open source automated test frame in web application.Just go out when 2,000 years
It is existing, have the developing history of more than ten years so far, Selenium becomes the selection of many Web automatic test personnel, especially that
There is the people of advanced programming and script technical ability a bit.
Selenium support multisystem environment (Windows, Mac, Linux) and a variety of browsers (Chrome,
FireFox, IE and browser without a head (not having interface)).Its script can be write by various programming languages, such as
Java, Groovy, Python, C#, PHP, Ruby and Perl.
Because of the flexibility of Selenium, it is each to cope with that tester can write various complexity, advanced test scripts
Kind of complicated problem, it need advanced programming skill and pay construct meet oneself demand automated test frame and
Library.
Certificate: open source
2、Katalon Studio
Katalon Studio is a powerful automatic test in terms of web application, movement and web service
Solution.Based on Selenium and Appium frame, Katalon Studio is integrated with these frames in software automation side
The advantages of face.
The test skill set of this tool support different levels.Non-programmers can also quickly go up one automatic test of hand
Project (as used spy's object record test script), while also saving programmer and advanced test personnel building Xin Ku and dimension
The time of spats sheet.
Katalon Studio is desirably integrated into during CI/CD, and compatible popular quality treatment tool, including
QTest, JIRA, Jenkins and Git.It provides a good function and analyzes Katalon, by index and chart to
User provides comprehensive test report.
Certificate: free
3、Uipath
UiPath Studio is integrated for application program and executes third party application automatically, and managerial IT appoints
The total solution of business and business IT process.
Project is the graphical representation of operation flow.It enables you to execute rule-based process automatically, and method is to allow you
Fully control the relationship between execution sequence and one group of customized step (activity in also referred to as UiPath Studio).Often
A activity all includes a little trick, such as click button, reads file or write-in log panel.
The main Types of supported project are:
Sequence-is suitable for linear process, so that you is successfully gone to another activity from an activity, without obscuring
Project.
Flow chart-is suitable for more complicated service logic, enables you by multiple branching logic operators with more various
The mode Integration Decision of change and connection activity.
State machine-is suitable for very big project；They use the state of limited quantity in commission, these states are by item
Part (conversion) or activity-triggered.
The shortcomings that Selenium is: element positioning method is single and not intelligent, and technical staff is needed to need advanced programming
Skill.Katalon Studio is the integration tool packet based on Selenium, uses the more friendly recording interface of user experience.
But the shortcomings that the two, is all that robustness is lower --- any renewal of the page or iteration maximum probability will lead to test crash, together
Shi Ruguo encounters tester in the case that same dvielement requires test and has many mechanical duplicate workloads, these are logical
It is completely soluble to cross this scheme.
And in terms of process robot, the still definition based on user for rule of the softwares such as uipath, rather than actively go
Understand user behavior.If using machine vision method of the invention and dom tree analysis method, it can extensive object element,
Similar element so is generated, so as to greatly increase the robustness of testing process, even if webpage iteration updates, test stream
Journey can still go on, and can also better understand user's operation.Greatly reduce tester simultaneously or user repeats
Labour.
The present invention is further expalined below in conjunction with Fig. 1-Fig. 6:
S110 machine vision method:
S111 selects Fig. 1 as test page, this is to need webpage to be tested, shown in that option of region
As soon as it is all dvielement in people, but complete different, the Asia-Pacific south 1 (Bombay) selected at present in test script, I
Wish that all regions are all tested.
S112.1, test page is become to black and white binary map, because can preferably detect icon or button in this way
Edge, subsequent figures are exactly the result of marginalisation.
All edges are detected by the formula of edge detection, formula is as follows:
Wherein: Gx: horizontal gradient；Gy: vertical gradient obtains Fig. 2.Then it is identified by the rectangular edge of object element
Interested region need to be extracted, is illustrated in fig. 3 shown below.
All frames just have been found by Fig. 3 in S112.2, but can see edge detection and not only detect
Gone out frame, also detected the edge of text, text be exactly we should not content.So needing to be added some decision conditions
Such as length, whether horizontal, whether vertical, marks in original image, be illustrated in fig. 4 shown below.
S112.3 obtained by S112.2 be a plurality of straight line beginning and end coordinate, in this way or can not judge which is straight
Line constitutes rectangle.The exact position of icon and button in order to obtain, the intersection point for needing to take each straight line (take intersection point), such as scheme
Shown in 5.
Each intersection point is carried out line by S112.4, then chooses rectangular border, excludes and target icon difference in areas obtains too
The inconsistent rectangle of more rectangles and length-width ratio.As shown in fig. 6, the extensive result of characteristics of image just obtains well.
But when working as icon or unconspicuous button feature, it is necessary to which method in addition is required extensive as a result, just to obtain
It is dom tree analysis method.
Referring to Fig. 7, simply observation can be seen that dom tree analysis method mainly pass through suitable div- > span- >
Div ... -> span can find object element, this process is defined as to the path in dom tree.So in general, together
Class, element path that can be extensive all should be consistent.
S121, the path for finding object element, it is assumed that our object element are as follows:
<span class="ng-scope ng-binding">east China 2</span>；
The path of available object element:
['div','span','div','div','div','div','div','div','div',
'dd','dl','form','div','div','div','div','div','div','di
v','div','div','div','div','div','div','div','body','htm
l','[document]']；
S122, the path according to object element, find element in turn:
<span class="ng-scope ng-binding">north China 2</span>
<span class="ng-scope ng-binding">east China 1</span>
<span class="ng-scope ng-binding">east China 2</span>
<span class="ng-scope ng-binding">south China 1</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 3 (Kuala Lumpur)</span>
<span class="ng-scope ng-binding">north China 5</span>
<span class="ng-scope ng-binding">1 (Silicon Valley) of U.S. west</span>
<span class="ng-scope ng-binding">singapore</span>
<span class="ng-scope ng-binding">asia-Pacific south 1 (Bombay)</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 5 (Jakarta)</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 2 (Sydney)</span>
<span class="ng-scope ng-binding">1 (Virginia) of U.S. east</span>
<span class="ng-scope ng-binding">north China 3</span>
<span class="ng-scope ng-binding">britain (London)</span>
<span class="ng-scope ng-binding">it calculates and stores integrated version</span>
<span class="ng-scope ng-binding">proprietary network</span>
<span class="ng-scope ng-binding">classic network</span>
<span class="ng-scope ng-binding">1C SSD</span>
<span class="ng-scope ng-binding">2C SSD</span>
<span class="ng-scope ng-binding">16C SSD</span>
<span class="ng-scope ng-binding">2</span>；
S123, some incoherent elements are had found according to path, it is possible to be assumed with Article 2: when same dvielement all
When finding same father's element, non-same dvielement is not centainly that this father's member usually excludes uncorrelated element.Use pseudo table
Show as follows:
Input: candidate's element (including object element), object element-are exactly (East China 2) in this example
Initialization:dic [father's element of candidate's element]=candidate's element
● while is comprising only having object element, i.e. dic [father father's .. father's member of object element in that dic of object element
Element]==object element:
■ dicTmp={ }
■ candiParents=[]
■ foriin candidate's element:
ocandiParents.append(i.parent)
oif i.parent not in dicTmp.keys():
OdicTmp [i.parent] +=dic [i]
■ dic=dicTmp
■ candidate's element=candiParents；
The result of acquisition is as follows:
<span class="ng-scope ng-binding">north China 2</span>
<span class="ng-scope ng-binding">east China 1</span>
<span class="ng-scope ng-binding">east China 2</span>
<span class="ng-scope ng-binding">south China 1</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 3 (Kuala Lumpur)</span>
<span class="ng-scope ng-binding">north China 5</span>
<span class="ng-scope ng-binding">1 (Silicon Valley) of U.S. west</span>
<span class="ng-scope ng-binding">singapore</span>
<span class="ng-scope ng-binding">asia-Pacific south 1 (Bombay)</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 5 (Jakarta)</span>
<span class="ng-scope ng-binding">the Asia-Pacific southeast 2 (Sydney)</span>
<span class="ng-scope ng-binding">1 (Virginia) of U.S. east</span>
<span class="ng-scope ng-binding">north China 3</span>
<span class="ng-scope ng-binding">britain (London)</span>.
Place is not described in detail by the present invention, is the well-known technique of those skilled in the art.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that those skilled in the art without
It needs creative work according to the present invention can conceive and makes many modifications and variations.Therefore, all technologies in the art
Personnel are available by logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Technical solution, all should be within the scope of protection determined by the claims.
Claims (8)
1. a kind of test method based on machine vision and DOM tree structure, which comprises the steps of:
S100, feature extraction and selection identify the feature of object element in test page；
S200, the feature according to object element, classify to the element with similar characteristics, are extensive, and extensive element is obtained；
S300, it is tested, and is recorded automatically according to extensive element.
2. test method as described in claim 1, which is characterized in that in S100, including two ways, i.e. S110, machine view
Feel method and S120, dom tree analysis method, the machine vision method and dom tree analysis method are selected one or are applied in combination.
3. test method as claimed in claim 2, which is characterized in that the use environment of machine vision method be webpage it is clear,
In the case where each icon edge clear, by identifying the general shape of object element, looked in certain area and its class
As icon either button, it is extensive to achieve the purpose that.
4. test method as claimed in claim 2, which is characterized in that dom tree analysis method be by the structure of dom tree come into
It is capable, analysis abide by it is assumed hereinafter that:
Assuming that 1. can be extensive same dvielement level it is centainly similar；
Assuming that 2. when same dvielement all finds nearest same father's element, non-same dvielement is not centainly this father's element.
5. test method as claimed in claim 3, which is characterized in that S110, machine vision method include the following steps:
S111, selection target element, this object element is icon or button, and carries out characteristic point detection to object element, is obtained
The feature of object element；
The edge of all elements in S112, the identification page；
S113, according to object element feature, all elements are screened in screening, obtain the figure with object element similar characteristics
Element obtains extensive element.
6. test method as claimed in claim 5, which is characterized in that in S112, include the following steps:
S112.1 is by the page edge of target, and the image of test page, which is carried out pretreatment, first becomes bianry image, then
Edge is detected, the formula of edge detection:
In formula (1): Gx is horizontal gradient, and Gy: vertical gradient, Edge_Gradient (G) are edge gradient, and Angle (θ) is
Edge inclination angle；
S112.2 screens the edge of acquisition according to object element feature；
S112.3 takes intersection point, chooses the intersection point at remaining edge；
Each intersection point is carried out line by S112.4, chooses the shape similar with object element, then pass through object element feature into
Row screening, it is remaining to be exactly the same dvielement of object element, to obtain extensive element.
7. test method as claimed in claim 4, which is characterized in that S120, dom tree analysis method include the following steps:
S121, the path for finding object element；
S122, it is found according to the path searched out with all elements under level-one path；
S123, incoherent element is rejected, it is extensive to object element progress, obtain extensive element.
8. test method as claimed in claim 7, which is characterized in that in S123, rejecting mode is to search out object element
Father's element, then according to " when same dvielement all finds same father's element, non-same dvielement is not centainly this father's element
To exclude uncorrelated element " this condition rejected.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111245917A (en) * | 2020-01-07 | 2020-06-05 | 广州市申迪计算机***有限公司 | Katalon-based work order entry device and implementation method thereof |
| CN113268431A (en) * | 2021-06-24 | 2021-08-17 | 深圳市凯莱特科技股份有限公司 | Learning method of RPA robot software |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101593184A (en) * | 2008-05-29 | 2009-12-02 | 国际商业机器公司 | The system and method for self-adaptively locating dynamic web page elements |
| US20110093773A1 (en) * | 2009-10-19 | 2011-04-21 | Browsera LLC | Automated application compatibility testing |
| 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 |
| CN104854546A (en) * | 2012-10-12 | 2015-08-19 | 微软技术许可有限责任公司 | Weighted focus navigation of graphical user interface |
| CN105204992A (en) * | 2015-08-28 | 2015-12-30 | 努比亚技术有限公司 | Test script generating device and method |
| CN106776301A (en) * | 2016-12-01 | 2017-05-31 | 广州酷狗计算机科技有限公司 | Daughter element method of testing and device |
| CN108009078A (en) * | 2016-11-01 | 2018-05-08 | 腾讯科技（深圳）有限公司 | A kind of application interface traversal method, system and test equipment |
| US20190096080A1 (en) * | 2017-08-25 | 2019-03-28 | Maker Trading Pte Ltd | Machine vision system and method for identifying locations of target elements |
-
2019
- 2019-07-30 CN CN201910695205.9A patent/CN110515835B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101593184A (en) * | 2008-05-29 | 2009-12-02 | 国际商业机器公司 | The system and method for self-adaptively locating dynamic web page elements |
| US20110093773A1 (en) * | 2009-10-19 | 2011-04-21 | Browsera LLC | Automated application compatibility testing |
| 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 |
| CN104854546A (en) * | 2012-10-12 | 2015-08-19 | 微软技术许可有限责任公司 | Weighted focus navigation of graphical user interface |
| CN105204992A (en) * | 2015-08-28 | 2015-12-30 | 努比亚技术有限公司 | Test script generating device and method |
| CN108009078A (en) * | 2016-11-01 | 2018-05-08 | 腾讯科技（深圳）有限公司 | A kind of application interface traversal method, system and test equipment |
| CN106776301A (en) * | 2016-12-01 | 2017-05-31 | 广州酷狗计算机科技有限公司 | Daughter element method of testing and device |
| US20190096080A1 (en) * | 2017-08-25 | 2019-03-28 | Maker Trading Pte Ltd | Machine vision system and method for identifying locations of target elements |
Non-Patent Citations (4)
| Title |
|---|
| 刘华玉等: "基于视觉注意的移动图书馆界面显示优化研究", 《巢湖学院学报》 * |
| 王海涛: "Web信息抽取网页自动浏览导航与集成规则研究", 《计算机科学与探索》 * |
| 穆琼: "基于视觉特征的网页清洗研究与实现", 《中国优秀硕士学位论文全文数据库 (信息科技辑)》 * |
| 飘哥: "利用计算机视觉来减少测试自动化盲点", 《HTTPS://ZHUANLAN.ZHIHU.COM/P/90943153》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111245917A (en) * | 2020-01-07 | 2020-06-05 | 广州市申迪计算机***有限公司 | Katalon-based work order entry device and implementation method thereof |
| CN111245917B (en) * | 2020-01-07 | 2022-04-19 | 广州市申迪计算机***有限公司 | Katalon-based work order entry device and implementation method thereof |
| CN113268431A (en) * | 2021-06-24 | 2021-08-17 | 深圳市凯莱特科技股份有限公司 | Learning method of RPA robot software |
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