CN107870862A - Construction method, traversal method of testing and the computing device of new control forecast model - Google Patents
Construction method, traversal method of testing and the computing device of new control forecast model Download PDFInfo
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- CN107870862A CN107870862A CN201711130634.9A CN201711130634A CN107870862A CN 107870862 A CN107870862 A CN 107870862A CN 201711130634 A CN201711130634 A CN 201711130634A CN 107870862 A CN107870862 A CN 107870862A
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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
- G06F11/3684—Test management for test design, e.g. generating new test cases
Abstract
The invention discloses a kind of construction method of new control forecast model, and suitable for being performed in computing device, computing device is provided with traversal test application, and the application is suitable to carry out traversal test to multiple controls on interface of mobile terminal to be measured, and this method includes：Multiple controls on interface of mobile terminal to be measured are clicked on respectively, and count multiple attributive character values of each control respectively；Count each control respectively and be clicked front and rear former interface control and new interface control, and further determine that each control be clicked after new discovery control, and multiple attributive character values of each new discovery control of statistics；Using be respectively clicked multiple attributive character values of control as input, using the attributive character value of its all new discovery control after being clicked as output, the input and output are trained using pre-defined algorithm, obtain the new control forecast model.The invention also discloses a kind of on mobile terminals using the model come the traversal method of testing performed and corresponding mobile terminal.
Description
Technical field
The present invention relates to automatic test field, more particularly to a kind of construction method of new control forecast model, traversal are surveyed
Method for testing, mobile terminal and computing device.
Background technology
In automatic test field, traversal test has been widely used among each class testing, and is played important
Effect.Traversal test should go to find the path of tested application as far as possible, and the coverage rate in path is more complete, is more possible to sudden and violent
Dew is tested the problem of application, therefore the coverage rate for improving traversal test is extremely necessary.But there is not intelligent selection traversal at present
The method in path, even if after being superimposed by various simple algorithms (such as simple random and traversal), to a certain extent
Improve coverage rate, but do not have yet it is a kind of can be according to the tested method using self character intelligent selection path.
Accordingly, it is desirable to provide a kind of traversal method that can effectively improve traversal Test coverage degree, to improve traversal test
Efficiency.
The content of the invention
Therefore, the present invention provides a kind of construction method of new control forecast model, traversal method of testing, mobile terminal and meter
Equipment is calculated, is existed above to try hard to solve the problems, such as or at least alleviate.
According to an aspect of the present invention, there is provided a kind of construction method of new control forecast model, suitable in computing device
Middle execution, computing device are provided with traversal test application, and the application is suitable to enter multiple controls on interface of mobile terminal to be measured
Row traversal test, this method include：Multiple controls on interface of mobile terminal to be measured are clicked on respectively, and statistics is each respectively
Multiple attributive character values of control；Each control is counted respectively and is clicked front and rear former interface control and new interface control, goes forward side by side one
Walk the new discovery control after each control of determination is clicked, and multiple attributive character values of each new discovery control of statistics；With each quilt
The multiple attributive character values for clicking on control are input, using the attributive character value of its all new discovery control after being clicked to be defeated
Go out, the input and output are trained using pre-defined algorithm, obtain new control forecast model.
Alternatively, in the construction method of the new control forecast model according to the present invention, in addition to step：New control is pre-
Survey model to be passed in mobile terminal to be measured, and define new control anticipation function to perform the model；And whenever to shifting to be measured
Before control on dynamic terminal interface carries out traversal click, predict that each control is by point on the interface using the new control anticipation function
New discovery control number after hitting, and choose the most control of new discovery control number and carry out traversal click.
Alternatively, in the construction method of the new control forecast model according to the present invention, multiple attributive character include following
One or more in feature：Activity titles, control type, whether have control ID, whether have control description, whether can point
Hit, be whether selected, whether slidably, whether in border center.
Alternatively, in the construction method of the new control forecast model according to the present invention, for some attributive character, if its
On the contrary attribute is yes, then corresponds to attributive character value as 1, then be 0.
Alternatively, in the construction method of the new control forecast model according to the present invention, in addition to step：Reflected using predetermined
The content of text of the Activity titles of each control and/or control type is converted to digital content by shooting method.
Alternatively, in the construction method of the new control forecast model according to the present invention, pre-defined algorithm is convolutional Neural net
Network algorithm, it is suitable to perform under tensorflow frameworks, and predetermined mapping method is only hot method or TF-IDF methods.
Alternatively, in the construction method of the new control forecast model according to the present invention, multiple attributive character are suitable to pass through
Uiautomatorviewer instruments parse to obtain, and the Activity titles are suitable to by ordering dumpsys activity |
Grep mF are obtained, if having control ID to be suitable to according to resource-id determined properties, if having control description to be suitable to basis
Content-desc determined properties, the new control forecast model are suitable to preserve with pb files, and the new control anticipation function is
GetNewUiCounts functions.
According to a further aspect of the invention, there is provided a kind of computing device, including one or more processors, memory with
And one or more programs, wherein one or more program storages in memory and are configured as by one or more processors
Perform, one or more programs include being used to perform the instruction of the construction method of the new control forecast model according to the present invention.
According to a further aspect of the invention, a kind of computer-readable storage medium for storing one or more programs is also provided
Matter, one or more programs include instruction, and instruction is when executed by a computing apparatus so that computing device is according to the present invention's
The construction method of new control forecast model.
According to a further aspect of the invention, there is provided one kind traversal method of testing, it is mobile suitable for performing in the terminal
There is new control anticipation function defined in terminal, for performing new control forecast model, the model is using new control as described above
The construction method structure of forecast model, methods described include：Control on to interface of mobile terminal to be measured carries out traversal point
Before hitting, the new control of new discovery after each control is clicked on the interface is predicted using the new control anticipation function, and choose new
It was found that the most control of new control carries out traversal click.
According to a further aspect of the invention, there is provided a kind of mobile terminal, including one or more processors, memory with
And one or more programs, wherein one or more program storages in memory and are configured as by one or more processors
Perform, one or more programs include being used for the instruction for performing the traversal method of testing according to the present invention.
According to a further aspect of the invention, there is provided a kind of computer-readable storage medium for storing one or more programs
Matter, one or more programs include instruction, instructed when being performed by mobile terminal so that mobile terminal is performed according to the present invention's
Travel through method of testing.
Technique according to the invention scheme, collect data on the computing device first and train new control forecast model, root
Institute can newfound control number after effectively can often clicking on a control according to the model.Afterwards, it is the model transplantations are for example to be measured
It can be played a significant role in mobile terminal in traversal is tested.Before the traverse path of selection next step every time, all using should
Model calculates the new discovery control number after all controls of current interface are clicked, and then chooses new discovery control number pair
Traverse path of more controls as next step.By this method, the selection in path is become more intelligent, substantially increased
The validity and smog of test are traveled through, and then improves the whole efficiency of traversal test.
Brief description of the drawings
In order to realize above-mentioned and related purpose, some illustrative sides are described herein in conjunction with following description and accompanying drawing
Face, these aspects indicate the various modes that can put into practice principles disclosed herein, and all aspects and its equivalent aspect
It is intended to fall under in the range of theme claimed.Read following detailed description in conjunction with the accompanying drawings, the disclosure it is above-mentioned
And other purposes, feature and advantage will be apparent.Throughout the disclosure, identical reference generally refers to identical
Part or element.
Fig. 1 shows the structured flowchart of computing device 100 according to an embodiment of the invention；
Fig. 2 shows the flow chart of the construction method 200 of new control forecast model according to an embodiment of the invention；
Fig. 3 shows the schematic diagram of uiautomatorviewer operation interfaces according to an embodiment of the invention；And
Fig. 4 shows the boundary before and after " newly-built " control according to an embodiment of the invention clicked on terminal interface to be measured
Face schematic diagram.
Embodiment
The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although the disclosure is shown in accompanying drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
Limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
Completely it is communicated to those skilled in the art.
Fig. 1 is the block diagram of Example Computing Device 100.In basic configuration 102, computing device 100, which typically comprises, is
System memory 106 and one or more processor 104.Memory bus 108 can be used in processor 104 and system storage
Communication between device 106.
Depending on desired configuration, processor 104 can be any kind of processing, include but is not limited to：Microprocessor
(μ P), microcontroller (μ C), digital information processor (DSP) or any combination of them.Processor 104 can be included such as
The cache of one or more rank of on-chip cache 110 and second level cache 112 etc, processor core
114 and register 116.The processor core 114 of example can include arithmetic and logical unit (ALU), floating-point unit (FPU),
Digital signal processing core (DSP core) or any combination of them.The Memory Controller 118 of example can be with processor
104 are used together, or in some implementations, Memory Controller 118 can be an interior section of processor 104.
Depending on desired configuration, system storage 106 can be any type of memory, include but is not limited to：Easily
The property lost memory (RAM), nonvolatile memory (ROM, flash memory etc.) or any combination of them.System stores
Device 106 can include operating system 120, one or more apply 122 and routine data 124.In some embodiments,
It may be arranged to be operated using routine data 124 on an operating system using 122.Routine data 124 includes instruction, in root
In computing device 100 according to the present invention, routine data 124 includes the construction method 200 for performing new control forecast model
Instruction.
Computing device 100 can also include contributing to from various interface equipments (for example, output equipment 142, Peripheral Interface
144 and communication equipment 146) to basic configuration 102 via the communication of bus/interface controller 130 interface bus 140.Example
Output equipment 142 include graphics processing unit 148 and audio treatment unit 150.They can be configured as contributing to via
One or more A/V port 152 is communicated with the various external equipments of such as display or loudspeaker etc.Outside example
If interface 144 can include serial interface controller 154 and parallel interface controller 156, they can be configured as contributing to
Via one or more I/O port 158 and such as input equipment (for example, keyboard, mouse, pen, voice-input device, touch
Input equipment) or the external equipment of other peripheral hardwares (such as printer, scanner etc.) etc communicated.The communication of example is set
Standby 146 can include network controller 160, and it can be arranged to be easy to via one or more COM1 164 and one
The communication that other individual or multiple computing devices 162 pass through network communication link.
Network communication link can be an example of communication media.Communication media can be generally presented as in such as carrier wave
Or computer-readable instruction in the modulated data signal of other transmission mechanisms etc, data structure, program module, and can
With including any information delivery media." modulated data signal " can such signal, one in its data set or more
It is individual or it change can the mode of coding information in the signal carry out.As nonrestrictive example, communication media can be with
Include the wire medium of such as cable network or private line network etc, and it is such as sound, radio frequency (RF), microwave, infrared
(IR) the various wireless mediums or including other wireless mediums.Term computer-readable medium used herein can include depositing
Both storage media and communication media.
Computing device 100 can be implemented as server, such as file server, database server, application program service
Device and WEB server etc., a part for portable (or mobile) electronic equipment of small size, these electronic equipments can also be embodied as
Can be such as cell phone, personal digital assistant (PDA), personal media player device, wireless network browsing apparatus, individual
Helmet, application specific equipment or the mixing apparatus that any of the above function can be included.Computing device 100 can also be real
It is now to include desktop computer and the personal computer of notebook computer configuration.In certain embodiments, the quilt of computing device 100
It is configured to perform the construction method 200 of the new control forecast model according to the present invention.
In addition, the computing device of computing device 100 is provided with traversal test application, the application is suitable to mobile terminal circle to be measured
Multiple controls on face carry out traversal test.
Fig. 2 shows the flow chart of the construction method 200 of new control forecast model according to an embodiment of the invention, should
Method is suitable to, in computing device, such as perform in computing device 100 as described above.As shown in Fig. 2 this method starts from step
Rapid S220.
In step S220, multiple controls on interface of mobile terminal to be measured are clicked on respectively, and statistics is each respectively
Multiple attributive character values of control.
These attributive character are mainly the attribute that some may influence to travel through coverage rate.Usually, multiple attributive character bags
Include the one or more in following characteristics：Activity titles (ActName), control type (Class), whether there is control ID
(hasId), whether there is control description (hasDescription), whether can click on (isClickable), whether be selected
(isCheckable), whether slidably, whether border center.Certainly, these are exemplary illustration, can also be according to need
Add other attributive character, the invention is not limited in this regard.If have chosen wherein m attributive character, pass through the above method
These features will be can obtain after these attribute number values can form the set x=[x that a dimension is m dimensions1,x2,x3,……,
xm], wherein x1、x2Deng being respectively which corresponding attributive character value.
Usually, multiple attributive character are suitable to parse to obtain by uiautomatorviewer instruments, wherein Activity
Title can be by ordering dumpsys activity | and grep mF are obtained, if having control ID can be according to resource-id
Determined property, if having control description can be according to content-desc determined properties, moreover, for Activity titles and control
Both attributive character of part type, it is also necessary to be converted to the content of text of both controls in numeral using predetermined mapping method
Hold.And for other whether the attributive character of class, on the contrary if its attribute is yes, it is 1 to correspond to attributive character value, then be 0.So
The attributive character of one control can be indicated with numeric form.Wherein, predetermined mapping method can be that industry is conventional
Any textual data value method, such as only hot method or TD-IDF methods, the invention is not limited in this regard.
Fig. 3 shows uiautomatorviewer interface schematic diagrams according to an embodiment of the invention, its left side with
The contact person interface of the connected mobile terminal to be measured of computing device, right side is then the attributive character of control " correlation ".It is " new for this
Build " control, ActName is by ordering dumpsys activity | and grep mF obtain value and are
MeiosDialtactsActivity, then numeral is converted thereof into by certain mapping ruler, such as be converted to 9809.Control
Type class is TextView, and numeral is converted into by certain mapping ruler, it is assumed that is 3.Resource-id attribute non-NULLs
So hasId values are true, it is 1 for numerical value.Content-desc attributes non-NULL is so hasDescription values are
False, corresponding numerical value are 0.It is true that control, which can click on therefore isClickable values, is 1 for numerical value.Control is selected institute
Using isCheckable values as false, corresponding numerical value is 0.Will be i.e. available by each after these attribute number values by the above method
The set x=[9809,3,1,0,1,0 ...] of attributive character value composition.
Then, in step S240, each control is counted respectively and is clicked front and rear former interface control and new interface control, and
Further determine that each control be clicked after new discovery control, and multiple attributive character values of each new discovery control of statistics.
Here it is exactly the control being clicked with this on directly related page of control that new discovery control is actual.Generally, such as
New interface after fruit control is clicked is a brand-new interface, then new discovery control is the control on new interface.Such as in Fig. 4
After the control " newly-built " for clicking on left side, the out newly-built contact person interface on a brand-new the right, it is by a brand-new control
The control such as view, " cancellation " therein " completion " of part collection composition is exactly the new discovery control corresponding to left side control " newly-built ".
And if new interface is the small dialog box occurred on former interface basis, new discovery control is then in the dialog box
Control.The new discovery control of each control is can determine that by contrasting former interface control content and new interface control content, its is specific
Method can be according to those skilled in the art's sets itself, the invention is not limited in this regard.For example, for the small dialog box of latter
Situation, it is N to obtain the interface master control number of packages before clicking on control k respectivelybefore, click on the control sum on the interface after control k
For Nafter(it is really former interface control number NbeforeWith the summation of wicket control number), then newfound control number is
Nafter-Nbefore。
In addition, each new discovery control after certain control is clicked also equally has the attributive character of control
(ActName, class, hasId etc.), therefore can also use the method under above-mentioned set that control property quantizes.It is and every
Individual new discovery control has a corresponding attributive character value oiIf therefore have n new discovery control, this n new discovery control
The attributive character value of part may make up a set of matrices y=[o1,o2,…,oi,…on].Or with control " newly-built " above
Exemplified by, if xIt is newly-built=[9809,3,1,0,1,0 ...], yIt is newly-built=[o1, o2, o3 ...], wherein o1, o2 etc. represent " cancellation " respectively
The control property characteristic value such as " completion ", (x corresponding to one group is obtained after so clicking on " newly-built " controlIt is newly-built,yIt is newly-built).Equally
, if clicking on control " setting ", it can equally obtain (x corresponding to one groupSet,ySet), wherein xSetIt is the category of control " setting "
Property characteristic value, ySetIt is click on the set of the attributive character value of all new discovery controls after control " setting ".In once traveling through
(x, y) of all controls is all collected, you can the corresponding relation of multigroup (x, y) is obtained, furthermore it is also possible to carry out several times more
Other traversals, collected more (x, y) with as much as possible.
Then, in step S260, after being respectively clicked multiple attributive character values of control input, to be clicked with it
The attributive character value of all new discovery controls is output, and the input and output are trained using pre-defined algorithm, is obtained described
New control forecast model.
It should be appreciated that the pre-defined algorithm can be existing arbitrary model training algorithm, such as various deep learning algorithms,
Depending on specific algorithms selection can combine business scenario data, and parameter required for each algorithm etc. can be by people in the art
Member is voluntarily set, and the present invention is without limitation.According to one embodiment, can be instructed using convolutional neural networks algorithm
Practice, the parameters such as convolutional layer, pond layer, full articulamentum needed for convolution are set, and those skilled in the art are voluntarily set, this hair
It is bright without limitation.In addition, the training to model can perform under tensorflow frameworks, and model is saved as into pb texts
Part.Tensorflow whole DFD is saved in pb files, so if new data (input data) flow into
During to DFD, it is possible to calculated and exported by pb files.
According to one embodiment, also each input and output value can be configured to characteristic vector, such as be stored as libsvm forms
Vector.Afterwards, this feature vector is trained and can obtain above-mentioned resume processing delay model.In addition, carrying out model instruction
When practicing, all (x, y) can also be configured to sample set, and according to predetermined ratio (such as according to 7:3 ratio) by the sample
Collection is divided into training set and test set.Afterwards, model training is carried out to training set using pre-defined algorithm, it is pre- obtains above-mentioned new control
Survey model.Then, the new control forecast model trained is tested using test set, i.e., it is each x values in test set is defeated
Enter into the model trained, respectively obtain the y ＇ values of model prediction, the y ＇ values are made comparisons and can assessed with the y values of reality
Go out the robustness of the model.If how low the phase recency of two values is, the parameter of new control forecast model can be suitably adjusted, and
Continue optimization training.
After new control forecast model is built, so that it may carry out traversal test to terminal to be measured using the model.Here, may be used
To be tested with computing device itself terminal to be measured, i.e., traditional method of testing for being connected PC with terminal to be measured.Now,
Computing device to the control on interface of mobile terminal to be measured before traversal click is carried out every time, all using above-mentioned new control prediction mould
Type predicts the new control of new discovery after each control is clicked on the interface, and chooses the most control of the new control of new discovery and carry out time
Go through click.In the present invention, input data is to want the control property characteristic value of decision-making, and output is new after the control is clicked
It was found that multiple attributive character values of control, and shared how many individual new discovery controls can be also further determined that from the output result.
In fact, the present invention when travel through the Path selection of test, mainly chooses new discovery control number maximum
Control carries out traversal click.But it is actual when traversing operation clicks on control, typically gone to search control with the attribute of control, then
Click on again.Therefore,, can not if only counting attribute of the quantity of new discovery control without counting control in training pattern
It is determined which next to click on, it is also possible to computing repeatedly for some controls can be caused, therefore the present invention uses new discovery control
Attributive character value for output, so can guarantee that new discovery control specific aim statistics.Certainly, according to one of present invention implementation
Example, the model training stage is being carried out, can also directly count the number of each new discovery control, and as the output of model
Value, forecast period so is being traveled through, is inputting the attributive character value of respectively control to be clicked, it is possible to directly obtain and be respectively clicked control
The number of new discovery control corresponding to part.
According to one embodiment of present invention, traversal test can perform in mobile terminal to be measured, not have to thus every
It is secondary to be all connected terminal to be measured to be tested with PC, test technology complexity is reduced, improves test scene universality.Therefore,
Method 200 also includes step：New control forecast model is passed in mobile terminal to be measured, and defines new control anticipation function
Perform the model；And before the control on to interface of mobile terminal to be measured carries out traversal click, predicted using the new control
New discovery control number after each control is clicked on the function prediction interface, and choose the most control of new discovery control number
Carry out traversal click.In practical operation, that is, model pb files are deposited to traversal to the asset for testing apk source code engineerings
Under catalogue, and tesorflow so libraries are combined, model is applied to android ends, defined a function and clicked on to predict
Control kiThe new control number of discovery estimated afterwards is.Wherein, new control anticipation function can be getNewUiCounts, certainly
Can be other function names, as long as being able to carry out the new control forecast model of the present invention.It should be appreciated that new control prediction
Function can be equally implanted in mobile terminal to be measured after computing device end is generated.Moreover, when carrying out new control prediction,
For those controls being clicked in current interface, then new control prediction is no longer carried out, and only those are not yet clicked
Control carry out new control prediction.
If t is clicks on control every time in traversal test, as t=j-1, control k is just completed(j-1)Click,
Then during t=j, if current control collection to be traveled through is K, calculated by above-mentioned control anticipation function getNewUiCounts in K
Newfound control number corresponding to each control, and select the maximum control K of control numberymaxAs the j moment is optimal
Path.As moment t=j-1=10-1=9, the click of the 9th control is completed.For example, as t=j=10, the 10th is clicked on
Control, but current page has a lot of control (assuming that there is 3, being represented with ABC), clicks on which control can reach if wondering
To highest coverage rate, so that it may by training obtained new control forecast model to go to predict, it is assumed that the result predicted is A controls
It can be found that 3 new controls, B controls can be found that 5 new controls, and it is 8 new controls that C controls, which are can be found that, then to be clicked on
The 10th control be exactly C.And when needing to click on the 11st control, equally it is to enter other current all remaining controls
The new control prediction of row, to choose the most control of new control number as the 11st control.
In addition, present invention also offers a kind of mobile terminal and the traversal method of testing performed in the mobile terminal,
There is new control anticipation function defined in the mobile terminal, for performing new control forecast model, and the model uses such as method 200
The construction method structure of described new control forecast model.The traversal method of testing includes：Whenever to interface of mobile terminal to be measured
On control carry out traversal click before, the new hair after each control is clicked on the interface is predicted using above-mentioned new control anticipation function
Now new control, and choose the most control of the new control of new discovery and carry out traversal click.On the present invention traversal method of testing, its
Detail is disclosed in detail in the description of method 200, will not be repeated here.
The partial code example of the present invention is as follows：
public int[]getNewUiCounts(UiComponent ki){
// it is input data assignment
Inputs [0]=ki.getX ()；
// by data feed to tensorflow
Trace.beginSection("feed")；
inferenceInterface.feed(inputName,inputs,WIDTH,HEIGHT)；
Trace.endSection()；
// prediction
Trace.beginSection("run")；
String [] outputNames=new String [] { outputName }；
inferenceInterface.run(outputNames)；
Trace.endSection()；
// output is stored in outputs
Trace.beginSection("fetch")；
inferenceInterface.fetch(outputName,outputs)；
Trace.endSection()；
return outputs；
Technique according to the invention scheme, using a kind of ergodic algorithm with deep learning, by deep learning algorithm application
In being tested to traversal, after training, it can be directed to and apply the characteristic of itself, intelligent selection coverage rate highest path,
So as to which the selection in path is become into more intelligent, the validity of traversal test is substantially increased.
A6, the method as any one of A1-A5, wherein, the pre-defined algorithm is convolutional neural networks algorithm, and it is suitable
Performed under tensorflow frameworks, the predetermined mapping method is only hot method or TF-IDF methods.
A7, the method as any one of A1-A5, wherein, multiple attributive character are suitable to pass through
Uiautomatorviewer instruments parse to obtain, and the Activity titles are suitable to by ordering dumpsys activity |
Grep mF are obtained, if having control ID to be suitable to according to resource-id determined properties, if having control description to be suitable to basis
Content-desc determined properties, the new control forecast model are suitable to preserve with pb files, and the new control anticipation function is
GetNewUiCounts functions.
In the specification that this place provides, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the present invention
Example can be put into practice in the case of these no details.In some instances, known method, knot is not been shown in detail
Structure and technology, so as not to obscure the understanding of this description.
Similarly, it will be appreciated that in order to simplify the disclosure and help to understand one or more of each inventive aspect,
Above in the description to the exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：I.e. required guarantor
The application claims of shield are than the feature more features that is expressly recited in each claim.More precisely, as following
As claims reflect, inventive aspect is all features less than single embodiment disclosed above.Therefore, abide by
Thus the claims for following embodiment are expressly incorporated in the embodiment, wherein each claim is in itself
Separate embodiments as the present invention.
Those skilled in the art should be understood the module or unit or group of the equipment in example disclosed herein
Between can be arranged in equipment as depicted in this embodiment, or alternatively can be positioned at and the equipment in the example
In different one or more equipment.Module in aforementioned exemplary can be combined as a module or be segmented into addition multiple
Submodule.
Those skilled in the art, which are appreciated that, to be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more equipment different from the embodiment.Can be the module or list in embodiment
Member or group between be combined into one between module or unit or group, and can be divided into addition multiple submodule or subelement or
Between subgroup.In addition at least some in such feature and/or process or unit exclude each other, it can use any
Combination is disclosed to all features disclosed in this specification (including adjoint claim, summary and accompanying drawing) and so to appoint
Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power
Profit requires, summary and accompanying drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation
Replace.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included some features rather than further feature, but the combination of the feature of different embodiments means in of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment claimed is appointed
One of meaning mode can use in any combination.
In addition, be described as herein can be by the processor of computer system or by performing for some in the embodiment
The method or the combination of method element that other devices of the function are implemented.Therefore, have and be used to implement methods described or method
The processor of the necessary instruction of element forms the device for implementing this method or method element.In addition, device embodiment
Element described in this is the example of following device：The device is used to implement as in order to performed by implementing the element of the purpose of the invention
Function.
Various technologies described herein can combine hardware or software, or combinations thereof is realized together.So as to the present invention
Method and apparatus, or some aspects of the process and apparatus of the present invention or part can take embedded tangible media, such as soft
The form of program code (instructing) in disk, CD-ROM, hard disk drive or other any machine readable storage mediums,
Wherein when program is loaded into the machine of such as computer etc, and is performed by the machine, the machine becomes to put into practice this hair
Bright equipment.
In the case where program code performs on programmable computers, computing device generally comprises processor, processor
Readable storage medium (including volatibility and nonvolatile memory and/or memory element), at least one input unit, and extremely
A few output device.Wherein, memory is arranged to store program codes；Processor is arranged to according to the memory
Instruction in the described program code of middle storage, perform the construction method of the new control forecast model of the present invention.
By way of example and not limitation, computer-readable medium includes computer-readable storage medium and communication media.Calculate
Machine computer-readable recording medium includes computer-readable storage medium and communication media.Computer-readable storage medium storage such as computer-readable instruction,
The information such as data structure, program module or other data.Communication media is typically modulated with carrier wave or other transmission mechanisms etc.
Data-signal processed passes to embody computer-readable instruction, data structure, program module or other data including any information
Pass medium.Any combination above is also included within the scope of computer-readable medium.
As used in this, unless specifically stated so, come using ordinal number " first ", " second ", " the 3rd " etc.
Description plain objects are merely representative of the different instances for being related to similar object, and are not intended to imply that the object being so described must
Must have the time it is upper, spatially, in terms of sequence or given order in any other manner.
Although describing the present invention according to the embodiment of limited quantity, above description, the art are benefited from
It is interior it is clear for the skilled person that in the scope of the present invention thus described, it can be envisaged that other embodiments.Additionally, it should be noted that
The language that is used in this specification primarily to readable and teaching purpose and select, rather than in order to explain or limit
Determine subject of the present invention and select.Therefore, in the case of without departing from the scope and spirit of the appended claims, for this
Many modifications and changes will be apparent from for the those of ordinary skill of technical field.For the scope of the present invention, to this
The done disclosure of invention is illustrative and not restrictive, and it is intended that the scope of the present invention be defined by the claims appended hereto.
Claims (10)
1. a kind of construction method of new control forecast model, suitable for being performed in computing device, the computing device is provided with time
Test application is gone through, the application is suitable to carry out traversal test to multiple controls on interface of mobile terminal to be measured, and this method includes：
Multiple controls on interface of mobile terminal to be measured are clicked on respectively, and count multiple attributive character of each control respectively
Value；
Each control is counted respectively and is clicked front and rear former interface control and new interface control, and further determines that each control is clicked
New discovery control afterwards, and multiple attributive character values of each new discovery control of statistics；
Using be respectively clicked multiple attributive character values of control as input, it is special with the attribute of its all new discovery control after being clicked
Value indicative is output, and the input and output are trained using pre-defined algorithm, obtain the new control forecast model.
2. the method for claim 1, wherein also include step：
The new control forecast model is passed in mobile terminal to be measured, and defines new control anticipation function to perform the mould
Type；And
, should using the new control anticipation function prediction before control on to interface of mobile terminal to be measured carries out traversal click
New discovery control number after each control is clicked on interface, and choose the most control of new discovery control number and carry out traversal point
Hit.
3. the method for claim 1, wherein multiple attributive character include the one or more in following characteristics：
Activity titles, control type, whether have control ID, whether there is control describe, whether can click on, be whether selected,
Whether slidably, whether in border center.
4. method as claimed in claim 3, wherein, for some attributive character, if its attribute is yes, correspond to attributive character
It is worth for 1, it is on the contrary then be 0.
5. method as claimed in claim 3, wherein, in addition to step：
The content of text of the Activity titles of each control and/or control type is converted in numeral using predetermined mapping method
Hold.
6. a kind of computing device, including：
One or more processors；
Memory；And
One or more programs, wherein one or more of program storages are in the memory and are configured as by described one
Individual or multiple computing devices, one or more of programs include being used to perform in the method according to claim 1-5
Either method instruction.
7. a kind of computer-readable recording medium for storing one or more programs, one or more of programs include instruction,
The instruction is when executed by a computing apparatus so that in method of the computing device according to claim 1-5
Either method.
8. one kind traversal method of testing, suitable for performing in the terminal, there is new control prediction letter defined in the mobile terminal
Number, for performing new control forecast model, the model is using the new control forecast model as any one of claim 1-5
Construction method structure, methods described includes：
, should using the new control anticipation function prediction before control on to interface of mobile terminal to be measured carries out traversal click
New discovery control number after each control is clicked on interface, and choose the most control of new discovery control number and carry out traversal point
Hit.
9. a kind of mobile terminal, including：
One or more processors；
Memory；And
One or more programs, wherein one or more of program storages are in the memory and are configured as by described one
Individual or multiple computing devices, one or more of programs include being used to perform in the method according to claim 11
Instruction.
10. a kind of computer-readable recording medium for storing one or more programs, one or more of programs include instruction,
The instruction by mobile terminal when being performed so that the mobile terminal performs the method according to claim 11.
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