CN109101414A - Based on the magnanimity UI Self -adaptive method and device thereof for burying point data - Google Patents
Based on the magnanimity UI Self -adaptive method and device thereof for burying point data Download PDFInfo
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- CN109101414A CN109101414A CN201810615205.9A CN201810615205A CN109101414A CN 109101414 A CN109101414 A CN 109101414A CN 201810615205 A CN201810615205 A CN 201810615205A CN 109101414 A CN109101414 A CN 109101414A
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- point data
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- magnanimity
- test cases
- behavior
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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
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/451—Execution arrangements for user interfaces
Abstract
The present invention provides a kind of based on the magnanimity UI Self -adaptive method and device thereof for burying point data, belongs to software testing technology field.It solves the problems such as prior art design is unreasonable.Include: to bury point data modeling based on the magnanimity UI Self -adaptive method and device thereof for burying point data, acquires user data；As a result conversion check obtains and platform-independent test cases model；UI test cases generates, and data output is obtained in point data modeling and result conversion check as test cases using burying.It is based on the advantages of magnanimity UI Self -adaptive method and device thereof for burying point data: solves the problems, such as that PIT depends on PIM unduly, and the PIT is capable of emulation user's usage behavior of high level.
Description
Technical field
The invention belongs to software testing technology fields, more particularly, to a kind of based on the magnanimity UI Self -adaptive for burying point data
Method and device thereof.
Background technique
With the rapid development of mobile Internet, the competition between internet product is also more shown especially.Therefore, is produced from internet
The ease for use and stability of product will become public one of the important consideration point for whether selecting the product.Test method based on UI
It is closest to the testing scheme of user group, more can intuitively observe whether the product is stable in use.Institute
Using even back end test personnel also can by UI means of testing as an important functional verification scheme in regression test, but
The upper limitation due to personnel and time, the existing test verifying means based on UI there are cases it is few, time-consuming it is more can not mould
The actual use situation for intending various real users leads to still have part BUG omission, seriously affects user experience.
Of the existing technology in order to solve the problems, such as, people have carried out long-term exploration, propose miscellaneous solution
Scheme.Wherein model-driven testing is exactly a kind of improved software testing technology, and model-driven testing is a kind of according to function need
Specification is sought, model is first established to program to be tested, then by analyzing this model, generates test case.Based on model
Drive the Test cases technology process of measuring technology as shown in fig. 6, wherein PIM is platform-independent system model figure, PIT model
It is platform-independent test model, it is last according to obtained test model and phase by PIM by the available PIT of level conversion
The test data that the tester answered provides, automatically generates test cases, Nmodle be on the market a comparative maturity based on
Model-driven test case Auto-Generation Tool, the principle of model creation is: 1. programs are for handling data, data
It may also be referred to as state (State)；2. user handles data by the operation interface that program provides, operation interface can also claim
Act (Action)；3. the change of data influences whether some movements can execute in turn again.
It when tester carries out PIM modeling, needs to act and state abstraction comes out, such as user pays program under scene
State should be as follows: 1. program states: operating status and not running state；2. User Status: logging in and be not logged in state；3.
It pays: remaining sum payment, card payment and revocation payment；4. pay status: paying and successfully fail with payment.Movement should include: 1. choosings
Select the means of payment；2. confirmation payment and revocation payment.And tester needs to compile above-mentioned movement and state using c# language
It is written as PIM model, then using Nmodle tool generation test model, the test data that last binding test personnel provide, from
It is dynamic to generate test cases.
Above-mentioned scheme improves the subproblem of the prior art to a certain extent, and still, the program also at least exists
Following defect: tester is not only needed to have certain generation based on model-driven testing method testing case Auto
Code writes ability, while it is more detailed abstract to need tester to have test scene and state, if be abstracted not accurate enough
It is not comprehensive enough, will lead to generate come test cases it is incomplete, meanwhile, automation generate come test cases be all based on mould
Type generates, can not analog subscriber using product truth the problems such as.
Summary of the invention
In view of this, regarding the issue above, the present invention provides a kind of tested based on the magnanimity UI for burying point data
Generation method and its device require software test personnel to have stronger abstracting power and written in code in the prior art to solve
Ability, the problem of fidelity difference, not only allows for user's operation step under normal circumstances, while will use when analog subscriber operates
The family operation dead time is also included in test cases.
The present invention provides a kind of based on the magnanimity UI Self -adaptive method for burying point data, comprising: buries point data modeling, adopts
Collect user data；As a result conversion check obtains and platform-independent test cases model；UI test cases generates, and counts burying
Test cases is used as according to data output is obtained in modeling and result conversion check.
In the methods described above, in burying point data modeling, user behavior probability histogram and residence time probability are obtained
Histogram.
In the methods described above, user behavior probability histogram and residence time probability histogram are for unified user
Behavior.
In the methods described above, burying the acquisition user data in point data modeling includes the behavior letter for specific user
The temporal information that breath, the corresponding result information of behavior bring of user and user behavior occur capture, handle, sending and
Its implementation process.
In the methods described above, as a result in conversion check, the behavioural information of user is a, and user is alternative in next step
Behavioural matrix is A={ a1,a2,a3…,an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=1), stop
Stay time matrix of consequence T={ t1,t2,t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn](∑n i=
1mi=1).
In the methods described above, the test cases model as a result in conversion check includes Anext=A [rand (n)], wherein
Rand (n) meets probability histogram X, and Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.
In the methods described above, during UI test cases generates, judge result information that user generates under specific behavior and
The precondition information of the behavior obtains the result information of specific behavior information and its generation of the user in extraordinary situation.
In the methods described above, while the test cases in the generation of UI test cases exports, specific user need to be referred to
The residence time information of behavior.So as to the operation of more true analog subscriber
In the methods described above, while the test cases in the generation of UI test cases exports, reference histograms number is needed
According to.To carry out priority ranking to test cases.
The present invention also provides a kind of based on the magnanimity UI Self -adaptive device for burying point data, comprising: buries point data modeling
Unit, for acquiring user data；As a result conversion check unit, for obtaining and platform-independent test cases model；UI is surveyed
Case generation unit is tried, is buried for and obtains data output in point data modeling and result conversion check as test cases.
In above-mentioned device, in burying point data modeling unit, user behavior probability histogram and residence time are obtained
Probability histogram.
In above-mentioned device, user behavior probability histogram and residence time probability histogram are for unified user
Behavior.
In above-mentioned device, burying the acquisition user data in point data modeling unit includes the behavior for specific user
The temporal information that information, the corresponding result information of behavior bring of user and user behavior occur is captured, handles, is sent
And its implementation process.
In above-mentioned device, as a result in conversion check unit, the behavioural information of user is a, and user is in next step for choosing
The behavioural matrix selected is A={ a1,a2,a3…,an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=
1), residence time matrix of consequence T={ t1,t2,t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn]
(∑n I=1mi=1).
In above-mentioned device, as a result the test cases model in conversion check unit includes Anext=A [rand (n)],
Wherein rand (n) meets probability histogram X, and Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.
In above-mentioned device, in UI test cases generation unit, the result letter that user generates under specific behavior is judged
The precondition information of breath and the behavior obtains the result letter of specific behavior information and its generation of the user in extraordinary situation
Breath.
In above-mentioned device, while the test cases in UI test cases generation unit exports, it need to refer to specific
The residence time information of user behavior.So as to the operation of more true analog subscriber
In above-mentioned device, while the test cases in UI test cases generation unit exports, histogram need to be referred to
Diagram data.To carry out priority ranking to test cases.
Compared with prior art, it is based on the advantages of magnanimity UI Self -adaptive method and device thereof for burying point data:
1, solve the problems, such as that PIT depends on PIM unduly, and the PIT is capable of emulation user's usage behavior of high level, this method and its
PIT in device learns from burying in point data completely, does not need tester to be abstracted PIM, solves since PIM leads to PIT
Incomplete problem；2, this method and its test data of device are made of the behavior of real user, and in the user of consideration
In the case that the operation residence time may affect, the test model that the user's operation residence time is included in makes to generate and
Test cases it is more authentic and valid analog subscriber operation；3, in addition, this method and its device can also be according to user behavior knots
Fruit data determine the priority orders of test cases.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 provides the flow chart of the method in the embodiment of the present invention.
Fig. 2 provides the exemplary user behavior histogram for burying point data modeling in the method in the embodiment of the present invention
Figure.
Fig. 3 provides the exemplary residence time histogram for burying point data modeling in the method in the embodiment of the present invention
Figure.
Fig. 4 provides the behavior array and residence time number buried in point data modeling in the method in the embodiment of the present invention
The data acquisition flow chart of group.
Fig. 5 provides the working principle diagram of the device in the embodiment of the present invention.
Fig. 6 provides the flow chart of Test cases technology process in the prior art.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawing and by embodiment, and following embodiment is to this hair
Bright explanation and the invention is not limited to following embodiments.
As shown in Figure 1, based on the magnanimity UI Self -adaptive method for burying point data, comprising: bury point data modeling, acquisition is used
User data；As a result conversion check obtains and platform-independent test cases model；UI test cases generates, and builds point data is buried
Data output is obtained in mould and result conversion check as test cases
Specifically, here bury point data modeling in, obtain user behavior probability histogram and residence time probability be straight
Fang Tu；Here user behavior probability histogram and residence time probability histogram is for unified user behavior；Here
Bury point data modeling in acquisition user data include be directed to specific user behavioural information, the behavior bring of user it is corresponding
The temporal information that result information and user behavior occur is captured, handled, sent and its implementation process.
Bury point data modeling in an example as shown in Figures 2 and 3, it is assumed that have after A behavior tetra- kinds of behaviors of B, C, D, E and
Frequency is respectively 5,6,7,8 times, and assumes that A behavior is followed successively by 3s, 5s, 6s, 7s away from the time of next step, and number then divides
It Wei not be 3,6,5,3 times.
Further, in result conversion check here, the behavioural information of user is a, and user is alternative in next step
Behavioural matrix is A={ a1,a2,a3…,an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=1), stop
Stay time matrix of consequence T={ t1,t2,t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn](∑n I=1mi
=1)；Here the test cases model in result conversion check includes Anext=A [rand (n)], and wherein rand (n) meets
Probability histogram X, Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.However it can be sent out in real operation
Existing, matrix of consequence in reality can by burying point data, to learn resulting matrix A small than us.Assuming that behavior a is the upper of behavior b
One walking is, and R={ r1,r2…,rnIt is different caused by a behavior as a result, can be easy to know, not every r is equal
It can lead to the generation of behavior b.In order to solve this problem, we obtain the precondition of different behaviors by result-reverse-checking.
Further, during UI test cases here generates, judge result information that user generates under specific behavior and
The precondition information of the behavior obtains the result information of specific behavior information and its generation of the user in extraordinary situation；This
In UI test cases generation in test cases output while, need to refer to specific user's behavior residence time information,
So as to the operation of more true analog subscriber；Here it while the test cases in the generation of UI test cases exports, needs to refer to
Histogram data, to carry out priority ranking to test cases.
Working principle: in burying point data modeling, burying point data statistics with histogram first is created for each behavior
One next step behavior array ArrayList<String>A, residence time array ArrayList<float>B and two
A ArrayList<Integer>C, ArrayList<Integer>D is used to statistic histogram data, and traversal is all to bury point data,
When encountering the behavior, next movement a of the behavior is obtained1, check a1With the presence or absence of array a, a is then obtained if it exists1Place
Subscript index, if it does not exist then by a1It is put into array A, and records and works as presubscript index, while corresponding histogram array
Cindex=Cindex+ 1, secondly, getting next movement a2Residence time, repeat the above steps, finally obtain the residence time
Histogram D, detailed process is as shown in Figure 4；In result conversion check, first be creation one Hash table HashMap <
Point data is buried in String, String > E, reading, obtains current behavior a1, current behavior state r and user's next step behavior a2, will
Current state and user's next step behavior are put into Hash array, and wherein key is behavior；In the generation of UI test cases, it will bury a little
Data and specific behavior obtained in the histogram data and result conversion check that bury specific behavior obtained in point data modeling
Precondition combine, loop through the specific behavior of each, mark it occur premise and generation as a result, and hair
Raw possibility duration information then carries out text to it and reports.
As shown in figure 5, based on the magnanimity UI Self -adaptive device for burying point data, comprising: bury point data modeling unit, use
In acquisition user data；As a result conversion check unit, for obtaining and platform-independent test cases model；UI test cases is raw
At unit, is buried for and obtain data output in point data modeling and result conversion check as test cases.
Specifically, here in burying point data modeling unit, obtain user behavior probability histogram and the residence time be general
Rate histogram；Here user behavior probability histogram and residence time probability histogram is for unified user behavior；This
In the acquisition user data buried in point data modeling unit include being brought for the behavior of behavioural information, user of specific user
Corresponding result information and the temporal information that occurs of user behavior captured, handled, being sent and its implementation process.
Further, in result conversion check unit here, the behavioural information of user is a, and user is in next step for choosing
The behavioural matrix selected is A={ a1,a2,a3…,an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=
1), residence time matrix of consequence T={ t1,t2,t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn]
(∑n I=1mi=1)；Here the test cases model in result conversion check unit includes Anext=A [rand (n)], wherein
Rand (n) meets probability histogram X, and Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.
Further, in UI test cases generation unit here, judge the result letter that user generates under specific behavior
The precondition information of breath and the behavior obtains the result letter of specific behavior information and its generation of the user in extraordinary situation
Breath；Here while the test cases in UI test cases generation unit exports, the stop of specific user's behavior need to be referred to
Temporal information, so as to the operation of more true analog subscriber；Here the test cases output in UI test cases generation unit
While, reference histograms data are needed, to carry out priority ranking to test cases.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
In generation, however, it does not deviate from the spirit of the invention or beyond the scope of the appended claims.
Claims (18)
1. a kind of based on the magnanimity UI Self -adaptive method for burying point data, it is characterised in that: include:
Point data modeling is buried, user data is acquired；
As a result conversion check obtains and platform-independent test cases model；
UI test cases generates, and data output is obtained in point data modeling and result conversion check as test cases using burying.
2. according to claim 1 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that described
It buries in point data modeling, obtains user behavior probability histogram and residence time probability histogram.
3. according to claim 2 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that the use
Family behavior probability histogram and residence time probability histogram are for unified user behavior.
4. according to claim 1 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that described buries
Point data modeling in acquisition user data include be directed to specific user behavioural information, the behavior bring of user tie accordingly
The temporal information that fruit information and user behavior occur is captured, handled, sent and its implementation process.
5. according to claim 2 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that the knot
In fruit conversion check, the behavioural information of user is a, and alternative behavioural matrix is A={ a to user in next step1,a2,a3…,
an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=1), residence time matrix of consequence T={ t1,t2,
t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn](∑n I=1mi=1).
6. according to claim 5 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that the knot
Test cases model in fruit conversion check includes Anext=A [rand (n)], and wherein rand (n) meets probability histogram X,
Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.
7. according to claim 1 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that the UI
Test cases judges the precondition information for the result information and the behavior that user generates under specific behavior, obtains in generating
The result information of specific behavior information and its generation of the user in extraordinary situation.
8. according to claim 1 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that described
While test cases in the generation of UI test cases exports, with reference to the residence time information of specific user's behavior.
9. according to claim 2 based on the magnanimity UI Self -adaptive method for burying point data, which is characterized in that described
While test cases in the generation of UI test cases exports, reference histograms data.
10. a kind of based on the magnanimity UI Self -adaptive device for burying point data, it is characterised in that: include:
Point data modeling unit is buried, for acquiring user data；
As a result conversion check unit, for obtaining and platform-independent test cases model；
UI test cases generation unit, for bury point data modeling and result conversion check in obtain data output as test
Case.
11. according to claim 10 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
Bury in point data modeling unit, obtain user behavior probability histogram and residence time probability histogram.
12. according to claim 11 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
User behavior probability histogram and residence time probability histogram are for unified user behavior.
13. according to claim 10 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
Burying the acquisition user data in point data modeling unit includes behavioural information, the behavior bring phase of user for specific user
The temporal information that the result information and user behavior answered occur is captured, handled, sent and its implementation process.
14. according to claim 11 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
As a result in conversion check unit, the behavioural information of user is a, and alternative behavioural matrix is A={ a to user in next step1,a2,
a3…,an, corresponding histogram data is X=[x1,x2,x3…,xn](∑n I=1xi=1), residence time matrix of consequence T=
{t1,t2,t3…,tnAnd corresponding dwell histogram M=[m1,m2,m3…,mn](∑n I=1mi=1).
15. according to claim 14 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
As a result the test cases model in conversion check unit includes Anext=A [rand (n)], and wherein rand (n) meets probability histogram
Scheme X, Tnext=T [rand (n)], wherein rand (n) meets probability histogram M.
16. according to claim 10 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
In UI test cases generation unit, the precondition letter for the result information and the behavior that user generates under specific behavior is judged
Breath, obtains the result information of specific behavior information and its generation of the user in extraordinary situation.
17. according to claim 10 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
UI test cases generation unit in test cases output while, with reference to the residence time information of specific user's behavior.
18. according to claim 11 based on the magnanimity UI Self -adaptive device for burying point data, which is characterized in that described
UI test cases generation unit in test cases output while, reference histograms data.
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