CN110162245A - Analysis method, device, electronic equipment and the storage medium of graphic operation - Google Patents
Analysis method, device, electronic equipment and the storage medium of graphic operation Download PDFInfo
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- CN110162245A CN110162245A CN201910290996.7A CN201910290996A CN110162245A CN 110162245 A CN110162245 A CN 110162245A CN 201910290996 A CN201910290996 A CN 201910290996A CN 110162245 A CN110162245 A CN 110162245A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/0706—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment
- G06F11/0712—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment in a virtual computing platform, e.g. logically partitioned systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/079—Root cause analysis, i.e. error or fault diagnosis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/0793—Remedial or corrective actions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/04845—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
-
- 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 disclosure is directed to a kind of analysis method of graphic operation, device, electronic equipment and storage medium, the analysis method of the graphic operation includes: to intercept the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program；Record the triggering sequencing for the multiple graphic operation instruction intercepted；The multiple graphic operation instruction and the triggering sequencing are input to the neural network model for being used to carry out graphic operation instruction collapse analysis trained in advance, to obtain the crash data and repair data of graphic operation；The crash data and the repair data are exported.The code that the disclosure is executed according to application program searches the loophole (bug) for being likely to result in application crash in real time, and neural network model can carry out targeted bug identification to the multiple graphic operations instruction being performed, and improve the efficiency and accuracy rate of positioning bug.
Description
Technical field
This disclosure relates to which technical field of software development more particularly to a kind of analysis method of graphic operation, device, electronics are set
Standby and storage medium.
Background technique
The graphical development of application program does not consider the internal structure of program generally in black box, as long as the program of exploitation is full
Sufficient functional requirement.Wherein, when graphical development code starts a leak (bug), it be easy to cause application crash.
Currently, in the method that the development phase solves application crash, mainly by developer according to exploitation and test
Experience determines that collapse case is generally caused by which function code, then, then searches this in background source code and may cause
The function code of collapse, artificial examination test whether the function code is bug, then carry out code in the case where determination is bug
Debugging and reparation.
But the scheme of the bug by manually rule of thumb searching graphic operation software, the developer's that places one's entire reliance upon opens
Hair experience, and search mode be manually to search, therefore, the efficiency for positioning bug is lower, and the accuracy rate of the bug positioned also compared with
It is low.
Summary of the invention
For overcome in the related technology manually search graphic operation software bug scheme present in positioning bug efficiency compared with
It is low, and the relatively low problem of accuracy rate of the bug positioned, the disclosure provide a kind of analysis method of graphic operation, device, electricity
Sub- equipment and storage medium.
According to the first aspect of the embodiments of the present disclosure, a kind of analysis method of graphic operation is provided, comprising:
Intercept the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program；
Record the triggering sequencing for the multiple graphic operation instruction intercepted；
The multiple graphic operation instruction and the triggering sequencing are input to trained in advance be used for figure
Shape operational order carries out the neural network model of collapse analysis, to obtain the crash data and repair data of graphic operation；
The crash data and the repair data are exported.
It is described to intercept corresponding to the graphic plotting request being triggered in application program in a kind of possible embodiment
Multiple graphic operation instructions, comprising:
Receive the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program；
The multiple graphic operation instruction is successively cached according to triggering sequencing；
It, will be before receiving the default end signal when receiving default end signal relevant to graphic operation
The multiple graphic operation instruction of caching is intercepted.
In a kind of possible embodiment,
The crash data includes one of the first information and the second information, and/or, third information:
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application program to collapse
It bursts；
Second information indicates that the multiple graphic operation instructs corresponding combination of function that the application program is caused to collapse
It bursts；
The third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
The application crash.
In a kind of possible embodiment, when the crash data includes the first information, the repair data
Triggering sequencing after reparation including the multiple graphic operation instruction；
When the crash data includes second information, the repair data includes that the graphic plotting request corresponds to
Reparation after combination of function；
When the crash data includes the third information, the repair data includes at least one described graphic operation
Parameter after the reparation of instruction.
It is described that the multiple graphic operation instruction and the triggering sequencing is defeated in a kind of possible embodiment
Enter to trained in advance for carrying out the neural network model of collapse analysis to graphic operation instruction, to obtain graphic operation
Crash data and repair data after, the method also includes:
In the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction, according to the reparation number
It modifies according to the multiple graphic operation instruction intercepted, and/or, the touching according to the repair data to record
Hair sequencing is modified；
If the triggering sequencing is modified and the multiple graphic operation instruction is not modified, in sandbox program
According to the modified triggering sequencing, execute the multiple graphic operation instruction of interception, the figure drawn；
If the multiple graphic operation instruction is modified and the triggering sequencing is not modified, in sandbox program
According to record the triggering sequencing, execute modified the multiple graphic operation instruction, the figure drawn；
If the triggering sequencing and the multiple graphic operation instruction modified, in sandbox program according to
The modified triggering sequencing executes modified the multiple graphic operation instruction, the figure drawn.
According to the second aspect of an embodiment of the present disclosure, a kind of analytical equipment of graphic operation is provided, comprising:
Blocking module is configured as intercepting the corresponding multiple figures behaviour of the graphic plotting request being triggered in application program
It instructs；
Logging modle is configured as the triggering sequencing for the multiple graphic operation instruction that record is intercepted；
Module is obtained, is configured as instructing the multiple graphic operation and the triggering sequencing is input to preparatory warp
The neural network model for being used to carry out graphic operation instruction collapse analysis of training is crossed, to obtain the crash data of graphic operation
And repair data；
Module is provided, is configured as exporting the crash data and the repair data.
In a kind of possible embodiment, the blocking module includes:
Receiving submodule is configured as receiving the corresponding multiple figures of the graphic plotting request being triggered in application program
Operational order；
Cache sub-module is configured as according to triggering sequencing successively caching the multiple graphic operation instruction；
Submodule is intercepted, is configured as when receiving default end signal relevant to graphic operation, will receive
The multiple graphic operation instruction cached before the default end signal is intercepted.
In a kind of possible embodiment, the crash data includes one of the first information and the second information, and/or,
Third information:
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application program to collapse
It bursts；
Second information indicates that the multiple graphic operation instructs corresponding combination of function that the application program is caused to collapse
It bursts；
The third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
The application crash.
In a kind of possible embodiment, when the crash data includes the first information, the repair data
Triggering sequencing after reparation including the multiple graphic operation instruction；
When the crash data includes second information, the repair data includes that the graphic plotting request corresponds to
Reparation after combination of function；
When the crash data includes the third information, the repair data includes at least one described graphic operation
Parameter after the reparation of instruction.
In a kind of possible embodiment, described device further include:
Modified module is configured as the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction
Under, it modifies according to the repair data to the multiple graphic operation instruction intercepted, and/or, according to the reparation
Data modify to the triggering sequencing of record；
First execution module, if being configured as, the triggering sequencing is modified and the multiple graphic operation instructs
It is not modified, then executes the multiple figure behaviour of interception according to the modified triggering sequencing in sandbox program
It instructs, the figure drawn；
Second execution module is modified and the triggering sequencing if being configured as the multiple graphic operation instruction
It is not modified, then executes modified the multiple figure behaviour according to the triggering sequencing of record in sandbox program
It instructs, the figure drawn；
Third execution module, if be configured as the triggering sequencing and the multiple graphic operation instruction repaired
Change, then executes modified the multiple graphic operation according to the modified triggering sequencing in sandbox program and refer to
It enables, the figure drawn.
According to the third aspect of an embodiment of the present disclosure, a kind of electronic equipment is provided, comprising:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to executing the analysis method to realize graphic operation described in above-mentioned any one
Performed operation.
According to a fourth aspect of embodiments of the present disclosure, a kind of non-transitorycomputer readable storage medium is provided, when described
When instruction in storage medium is executed by the processor of electronic equipment, so that electronic equipment is able to carry out one kind to realize as above-mentioned
Operation performed by the analysis method of graphic operation described in any one.
According to a fifth aspect of the embodiments of the present disclosure, a kind of application program is provided, the application program is by electronic equipment
When processor executes, so that electronic equipment is able to carry out a kind of analysis to realize the graphic operation as described in above-mentioned any one
Operation performed by method.
The technical scheme provided by this disclosed embodiment can include the following benefits:
In this way, the embodiment of the present disclosure is by intercepting the corresponding multiple figures of the graphic plotting being triggered in application program request
Shape operational order；And record the triggering sequencing for the multiple graphic operations instruction intercepted；And multiple graphic operations are instructed
It is input to triggering sequencing trained in advance for carrying out the neural network mould of collapse analysis to graphic operation instruction
Type, it is hereby achieved that the crash data and repair data of graphic operation；Finally, crash data and repair data are exported.?
It searches on graphic operation bug, can be searched and be likely to result in real time according to the code of execution in application program operational process
The bug of application crash, and neural network model can carry out targetedly the multiple graphic operations instruction being performed
Bug identification, improves the efficiency and accuracy rate of positioning bug；In addition, the neural network model can also be provided for crash data
Repair data, consequently facilitating developer rationally judges crash data.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.
Fig. 1 is a kind of flow chart of the analysis method of graphic operation shown according to an exemplary embodiment；
Fig. 2 is a kind of flow chart of the analysis method of graphic operation shown according to an exemplary embodiment；
Fig. 3 is a kind of structural block diagram of the analytical equipment of graphic operation shown according to an exemplary embodiment；
Fig. 4 is a kind of block diagram of the device of analysis for graphic operation shown according to an exemplary embodiment；
Fig. 5 is a kind of block diagram of the device of analysis for graphic operation shown according to an exemplary embodiment.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
Fig. 1 is a kind of flow chart of the analysis method of graphic operation shown according to an exemplary embodiment, figure behaviour
The analysis method of work can be applied to the developing instrument of application program, and this method can specifically include following steps:
Step 101, the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program is intercepted；
Wherein, the application program of the embodiment of the present disclosure has graphic drawing function, such as the beautiful Yan Gongneng to image.
In one example, the realization of U.S. face function successively may include grind skin, by grind skin after image merged with original image,
Fused image is highlighted, original image is sharpened, the image by the image after sharpening and after highlighting is merged, to fusion
Image afterwards increases the graphics operations steps such as filter.
For any one graphic operation step in above-mentioned graphic operation step, multiple figures can be divided into
Draw request.For example, the realization of mill skin operation needs to trigger multiple graphic plotting requests, for any one graphic plotting
Request can correspond to one section of complete graphic operation instruction, and (including multiple graphic operations instruct, wherein each graphic operation
Instruction can be understood as a graphic operation function).
Therefore, after user's operation application triggers graphic plotting is requested, the available graphic plotting of application program
The corresponding multiple graphic operations instruction of request, and multiple graphic operations instruction is handed down to driving, by GPU (graphics processor,
Graphics Processing Unit) successively execute multiple graphic operation instruction progress graphic plotting.
But since a graphic plotting requests any one graphic operation in corresponding multiple graphic operation instructions to refer to
It enables that occur graphic plotting abnormal, all may result in application crash, for the ease of developer to causing application crashes
Crash reason carries out fixation and recognition, in the embodiments of the present disclosure can be right to the graphic plotting request institute being triggered in application program
(multiple graphic operation instruction is for responding one section of graphic plotting request complete figure for the multiple graphic operations instruction answered
Shape operational order) it is intercepted, thus by step 103, by the graphic operation instruction input of interception to trained in advance
Neural network model, to get in this section of complete graphic operation instruction with the presence or absence of the bug for be easy to causeing application crashes
(loophole), and to the repair data that the bug is repaired.
In a kind of possible embodiment, when executing step 101, it can be realized by method shown in Fig. 2:
Step 201, the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program is received；
Wherein, after user operates application program and triggers graphic plotting request, the side of the embodiment of the present disclosure
Method can receive the corresponding multiple graphic operation instructions of graphic plotting request.
Step 202, the multiple graphic operation is instructed and is successively cached according to triggering sequencing；
Wherein, as described above, multiple graphic operation instruction is one section of complete and continuous graphic operation instruction, because
This, multiple graphic operation instruction is corresponding with triggering sequencing.Here it is possible to will successively be connect according to the triggering sequencing
The multiple graphic operation instruction buffers received.Wherein, the triggering sequencing of multiple graphic operation instructions can be multiple figure
The reception sequence of shape operational order.
Step 203, when receiving default end signal relevant to graphic operation, the default end will received
The multiple graphic operation instruction cached before signal is intercepted.
Wherein, after the corresponding multiple graphic operation instructions of a graphic plotting request issue, one can all be issued
A default end signal relevant to graphic operation, in this way, when the method for the embodiment of the present disclosure receives the default end signal,
It can then determine that multiple graphic operations instruction of the graphic plotting request of this triggering has received, in a kind of possible reality
It applies in mode, hook (hook) technology can be used, it is described more by what is cached before receiving the default end signal
A graphic operation instruction is intercepted.Certainly, hold-up interception method is not limited to hook technology, can also be that any one intercepts instruction
Method.
Wherein, it includes but is not limited to following several for presetting end signal: Draw series of functions, Flush function, Finish letter
Number, SwapBuffer and its equivalent functions, BlitCommandBuffer and its equivalent functions, SyncObject and its letter of equal value
Number etc..
Successively delay in this way, the embodiment of the present disclosure passes through the multiple graphic operations instruction that will be received according to triggering sequencing
It deposits, and in the case where receiving default end signal, it is described more by what is cached before receiving the default end signal
A graphic operation instruction is intercepted, so as to corresponding multiple to each graphic plotting request being triggered in application program
Graphic operation instruction is checked, is checked that multiple graphic operation instruction whether there is and is be easy to cause application crash
Bug, it is ensured that collapse the efficiency and accuracy rate of Code location.
In a kind of possible embodiment, the above-mentioned default end signal received can also be suitable according to the reception of data
Sequence is sequentially stored in caching.Such as two graphic plottings request in application program is successively triggered, graphic plotting requests 1 pair
1~3 and default end signal 1 should be instructed in graphic operation, graphic plotting request 2 corresponds to graphic operation instruction 4~6.That
The method of the embodiment of the present disclosure successively caches graphic operation and instructs 1, graphic operation when caching to the data received
Instruction 2, graphic operation instruction 3, default end signal 1, graphic operation instruction 4, graphic operation instruction 5, graphic operation instruction 6,
Default end signal 2.
Such as the graphic plotting request being triggered in step 101 is graphic plotting request 2, then the embodiment of the present disclosure is being blocked
It, then can be multiple between two default end signals being most recently received from will be stored in caching when screenshot shape operational order
Graphic operation instruction intercepts, that is, here be stored in default end signal 1 and the default graphic operation instruction 4 terminated between 2,
Graphic operation instruction 5, graphic operation instruction 6 are intercepted.
In addition, in a kind of possible embodiment, according to the size cases of free memory, the method for the embodiment of the present disclosure
Multiple graphic operations in caching can also be instructed and default end signal sequentially stores in queue, to reduce internal
The occupancy deposited.
Step 102, the triggering sequencing for the multiple graphic operation instruction intercepted is recorded；
Wherein, the embodiment of the present disclosure can recorde the multiple figures behaviour being intercepted after intercepting graphic operation instruction
Make the triggering sequencing instructed, in the embodiments of the present disclosure, to the interception sequence of graphic operation instruction, receives in other words suitable
Sequence, triggering sequencing as here.
In a kind of possible embodiment, multiple graphic operations of interception can be instructed according to triggering sequencing
Be sequentially stored in caching.
Step 103, the multiple graphic operation instruction and the triggering sequencing are input to trained in advance
For carrying out the neural network model of collapse analysis to graphic operation instruction, to obtain the crash data of graphic operation and repair number
According to；
Wherein, the complete graphic operation instruction of the section, i.e., multiple graphic operations instruction here may have bug,
Bug can be not present；So when the bug that may cause application crash is not present in multiple graphic operations instruction, then should
The crash data and repair data of neural network model output, which are sky or crash data, and repair data is indicates not deposit
In the 4th information of bug.So when there is the bug that may cause application crash in multiple graphic operations instruction, the mind
Crash data can be exported through network model, so-called crash data can be the bug data that may cause application crash,
In addition, the neural network model can also export the repair data for being repaired to the bug.
Optionally, the crash data may include one of the first information and the second information, and/or, third information.
That is, the crash data may include the first information or the second information or third information；
Alternatively, the crash data may include the first information and third information；
Alternatively, the crash data may include the second information and third information.
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application program to collapse
It bursts；
Specifically, when the corresponding multiple graphic operation instructions (can be understood as multiple functions) of a graphic plotting request
Triggering sequencing it is wrong when, in other words, in the case where the calling wrong order of multiple function, be then likely to result in application
Program crashing, therefore, if the neural network model pass through it is successively suitable to multiple graphic operations of input instruction and its triggering
Sequence is analyzed, and is determined that it triggers sequencing inaccuracy, then can be exported the first information, which indicates the multiple figure
The triggering sequencing of shape operational order can cause the application crash.That is, this can be navigated to using journey
Sequence is wrong there may be the calling of multiple function sequence and causes the bug of application crashes.
Second information indicates that the multiple graphic operation instructs corresponding combination of function to cause the application crash；
Specifically, as described above, multiple graphic operation instruction can be understood as multiple functions, and a figure is drawn
System request its corresponding multiple function be it is known, and neural network model by training learnt be to which combination of function
Not will cause application crash and which combination of function will cause the knowledge of application crash.Therefore, if this is more
A graphic operation instructs corresponding combination of function to will cause application crashes, can export the second information in neural network model,
In, the second information indicates that the multiple graphic operation instructs corresponding combination of function that can cause the application crash.
Such as it is respectively f1, f2, f3 that multiple graphic operations, which instruct corresponding function, wherein f1 and f3 is X-Y scheme
Drafting function, and f2 is 3 D image drawing function, and neural network model learns to two-dimensional pattern drafting function and three-dimensional figure
Shape drafting function, which is applied in combination, will cause application crashes, and therefore, can export indicates that the combination of function of f1, f2, the f3 will cause
Second information of application crash.
It is described that third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
Application crash.
Specifically, each graphic operation instruction, i.e., each function can carry parameter, and the parameter type that function carries
Mistake, Parameter Conditions mistake etc., will also result in the execution mistake of the function, so that the mistake for causing the graphic plotting to request is rung
It answers, graphic plotting is caused to fail, further result in application crash.Therefore, the neural network model of the embodiment of the present disclosure is also
Entrained parameter can be instructed to check whether check parameter entrained by each function each graphic operation of input
Meet the parameter request of the function, if do not met, export third information, wherein third information indicates the multiple figure
The parameter that at least one graphic operation instructs in operational order can cause the application crash.
For the above-mentioned first information, the second information, the form of expression of third information, it can be text, voice, code etc. and appoint
It anticipates a kind of performance information, the disclosure is without limitation.
In this way, multiple figures that the embodiment of the present disclosure is corresponding to each graphic plotting request being triggered in application program
Operational order, which carries out it, whether there is the inspection for causing the bug of application crashes, by means of preparatory trained neural network mould
Type can check the parameter of graphic operation instruction each in multiple graphic operations of input instruction, grasp to multiple figures
Triggering sequencing between instructing is checked, and instructs corresponding combination of function to examine multiple graphic operations
It looks into, the bug for causing application crashes is checked in terms of three, the bug of application crashes is caused if there is any one, then
Corresponding crash data is exported, in addition, exporting corresponding repair data also directed to the crash data, improves bug location efficiency,
And since neural network model first passes through training in advance and restrains, by means of the standard for the bug that the neural network model is positioned
True rate is also higher.
In a kind of possible embodiment, when the crash data includes the touching for indicating the multiple graphic operation instruction
When hair sequencing causes the first information of the application crash, the repair data includes that the multiple graphic operation refers to
Triggering sequencing after the reparation of order；
Continue with above-described embodiment for example, such as corresponding three functions of the graphic plotting being triggered request, are pressed
It is followed successively by f1, f2 and f3 according to triggering sequencing, and neural network model first passes through the study of crash reason in advance, f1 is arrived in study
Executing before f2 will cause application crashes, in addition, f1 is executed after f3 will also result in application crashes, therefore, needs are pressed
Reparation adjustment is carried out according to triggering sequencing of the knowledge learnt in advance to three functions.Triggering sequencing after reparation according to
Secondary is f2, f1 and f3.Wherein, the triggering sequencing after reparation here will not be made for what neural network model learnt in advance
At the triggering sequencing between the function of application crashes.
In a kind of possible embodiment, when the crash data includes indicating that the multiple graphic operation instruction corresponds to
Combination of function when causing the second information of the application crash, the repair data includes the graphic plotting request pair
Combination of function after the reparation answered；
Continue with above-described embodiment for example, such as corresponding three functions of the graphic plotting being triggered request, divide
It Wei f1, f2 and f3, wherein f1 and f3 is two-dimensional pattern drafting function, and f2 is 3 D image drawing function, and nerve net
Network model first passes through the study of crash reason in advance, and study makes to two-dimensional pattern drafting function and 3 D image drawing combination of function
With will cause application crashes, therefore, neural network model needs to generate the repair data to f2, such as f2 is revised as with phase
With the two-dimensional function f2 ' of graphic drawing function, therefore, neural network model can export repair data, specially combination of function
F1, f2 ' and f3.
In a kind of possible embodiment, when the crash data includes indicating in the multiple graphic operation instruction extremely
When the parameter of few graphic operation instruction causes the third information of the application crash, the repair data includes described
Parameter after the reparation of at least one graphic operation instruction.
Continue with above-described embodiment for example, such as corresponding three functions of the graphic plotting being triggered request, divide
It Wei f1, f2 and f3, wherein the neural network model of the embodiment of the present disclosure can instruct each graphic operation of input and be taken
Whether the parameter of band is checked (such as mating between parameter type inspection, Parameter Conditions inspection, the parameter and corresponding function
Inspection etc., these factors are all the reason of may cause application crashes, therefore are required to check), if that check to
The parameter of a few function does not meet the parameter request of the function, then the neural network model of the embodiment of the present disclosure not only can be with
Above-mentioned third information is exported, can also be repaired at least one function for carrying the parameter for not meeting parameter request, output
Complex data, the repair data include the parameter after the reparation of at least one function, wherein the parameter after reparation is to meet the letter
The parameter of several parameter requests.
Such as the parameter a that f1 is carried is int (integer), and neural network model learns to f1 when carrying the parameter of int,
It will cause application crashes, and it not will cause application crashes then when carrying the parameter of float (floating-point) type, therefore, repair
Data include the parameter a that f1 carries float type.
In this way, multiple figures that the embodiment of the present disclosure is corresponding to each graphic plotting request being triggered in application program
Operational order, which carries out it, whether there is the inspection for causing the bug of application crashes, by means of preparatory trained neural network mould
Type can check the parameter of graphic operation instruction each in multiple graphic operations of input instruction, grasp to multiple figures
Triggering sequencing between instructing is checked, and instructs corresponding combination of function to examine multiple graphic operations
It looks into, the bug for causing application crashes is checked in terms of three, the bug of application crashes is caused if there is any one, then
Corresponding crash data is exported, in addition, exporting corresponding repair data also directed to the crash data, the repair data exported is
It is provided for crash data, improves bug location efficiency, and since neural network model first passes through training in advance and restrains,
Therefore, the accuracy rate of the bug positioned by means of the neural network model is also higher.
In a kind of possible embodiment, before executing step 101, the method for the embodiment of the present disclosure further includes to upper
The step of neural network model is trained is stated, can specifically include:
Firstly, obtaining training sample set, wherein training sample set may include multiple positive samples and multiple negative samples；
Wherein, one group of sample includes a positive sample and multiple negative samples；
With positive sample 1 for example:
Positive sample 1 can be for by the graphic plotting request correspondence that not will cause application crash of manual verification
Multiple graphic operations instruction；
The corresponding negative sample 1 of positive sample 1 are as follows: the triggering sequencing for instructing graphic operations multiple in the positive sample 1
The negative sample upset；
The corresponding negative sample 2 of positive sample 1 are as follows: by least one of graphic operation multiple in positive sample 1 instruction figure
The corresponding function of shape operational order be revised as the function that another can not be unmodified with other be combined use function (such as
Former three functions are f4, f5 and f6, wherein f4 is revised as f1, wherein f1 can not be applied in combination by verifying with f5 and f6)
Negative sample；
The corresponding negative sample 3 of positive sample 1 are as follows: at least one graphic operation in positive sample 1 is instructed into corresponding function
Parameter is revised as not meeting the negative sample of another parameter of the parameter request of the function.
Wherein, the triggering being labelled in positive sample 1 between the multiple graphic operations instruction that not will cause application crash
Sequencing, each graphic operation instruct corresponding function name (i.e. multiple graphic operations instruct corresponding combination of function), each
Graphic operation instructs the parameter information of corresponding function, and the three classes data marked in positive sample 1 can instruct neural network model
Study generates repair data；
In negative sample 1, being labelled with, which indicates between multiple graphic operations instruction that triggering sequencing will cause application program, collapses
Routed crash data, in negative sample 2, being labelled with indicates that multiple graphic operations instruct corresponding combination of function to will cause application program
In the crash data of collapse, negative sample 3, it is labelled with some graphic operation and the parameter information of corresponding function is instructed to will cause application
The crash data of program crashing.
Then, training sample is concentrated to each group of sample for having labeled data, i.e. a positive sample and the positive sample pair
At least three negative samples answered, which are separately input into neural network model, to be trained, so that the neural network model after training can
To learn not will cause application crash to which triggering sequencing between multiple functions, which triggering sequencing meeting
Application crash is caused, and learns to which function to be combined to use and not will cause application crash, which function
Being combined use will cause application crash, and study instructs corresponding function (i.e. graphic operation letter to graphic operation
Number) parameter request.
It is so updated by more wheel iteration to neural network model, until neural network model is restrained, this is by training
Neural network model may be used for graphic operation instruct carry out collapse analysis.To refer to multiple graphic operations of input
Triggering sequencing between order and multiple graphic operation instruction is made whether there is the bug for causing application crash,
If it is present output crash data and the repair data for the crash data.
Wherein, the network structure of the neural network model can be any one Artificial Neural Network Structures, the disclosure pair
This with no restrictions, such as convolutional neural networks model, deep neural network model etc..
Step 104, the crash data and the repair data are exported.
It is not empty situation in crash data and repair data wherein it is possible to provide the interface UI (User Interface)
Under, crash data and repair data are exported.In one example, developer can be supplied in such a way that information is shown to look into
See so that developer recognized in the application program and checking crash data which section code because why reason meeting
The collapse of application program is caused, and checks the repair data for this section of code.
In this way, the embodiment of the present disclosure is by intercepting the corresponding multiple figures of the graphic plotting being triggered in application program request
Shape operational order；And record the triggering sequencing for the multiple graphic operations instruction intercepted；And multiple graphic operations are instructed
It is input to triggering sequencing trained in advance for carrying out the neural network mould of collapse analysis to graphic operation instruction
Type, it is hereby achieved that the crash data and repair data of graphic operation；Finally, crash data and repair data are exported.?
It searches on graphic operation bug, can be searched and be likely to result in real time according to the code of execution in application program operational process
The bug of application crash, and neural network model can carry out targetedly the multiple graphic operations instruction being performed
Bug identification, improves the efficiency and accuracy rate of positioning bug；In addition, the neural network model can also be provided for crash data
Repair data, consequently facilitating developer rationally judges crash data.
In a kind of possible embodiment, after step 103, it can also be wrapped according to the method for the embodiment of the present disclosure
It includes:
In the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction, according to the reparation number
It modifies according to the multiple graphic operation instruction intercepted, and/or, the touching according to the repair data to record
Hair sequencing is modified；
Wherein, the application development tool of the embodiment of the present disclosure, can after obtaining not for empty crash data and repair data
To provide the interface UI, prompt whether developer demonstrates the implementing result of the graphic plotting request after repairing.
If that receiving the execution of the graphic plotting request after exploitation arbitrarily repairs the instruction demonstration at the interface UI
As a result instruction, i.e., in the case that the target instruction target word of the multiple graphic operation instruction is repaired in expression here, then the disclosure
The method of embodiment can modify to multiple graphic operations of interception instruction according to the repair data acquired, and/
Or, modifying according to the triggering sequencing of the repair data to record.
If the triggering sequencing is modified and the multiple graphic operation instruction is not modified, that is to say, that when collapsing
Routed data include the above-mentioned first information, and the repair data includes the triggering elder generation after the reparation that the multiple graphic operation instructs
Afterwards in the case where sequence, then the multiple of interception is executed according to the modified triggering sequencing in sandbox program
Graphic operation instruction, the figure drawn；
Wherein, as described in above-described embodiment, when the crash data of acquisition includes the first information, then repair data includes institute
Triggering sequencing after stating the reparation of multiple graphic operation instructions, then above-mentioned steps can be according to repair data, to record
The triggering sequencing is modified, and in this step, then it can be successively suitable according to modified triggering in sandbox program
Triggering sequencing after sequence, such as reparation described in above-described embodiment is followed successively by f2, f1 and f3, successively holds in sandbox program
Row f2, f1 and f3, thus the figure drawn.Therefore, developer can be seen in the interface UI to the figure after reparation
The implementing result of request is drawn, i.e., the figure drawn here, so as to manual confirmation, whether the graphic plotting is abnormal.
If the multiple graphic operation instruction is modified and the triggering sequencing is not modified, that is to say, that when collapsing
Routed data include above-mentioned second information, and/or, third information, and the repair data includes that the graphic plotting request corresponds to
Reparation after combination of function, and/or, in the case where the parameter after the reparation of described at least one graphic operation instruction, then exist
According to the triggering sequencing of record in sandbox program, modified the multiple graphic operation instruction is executed, is drawn
The figure of system；
And since above-mentioned steps can modify according to repair data come the multiple graphic operation instruction to record,
For example, f2 is revised as f2 ', and/or, the type of the f1 parameter a carried is revised as float type from int type.
It, can be in sandbox program according to the triggering sequencing of record, in sandbox program successively so in this step
Execute modified f1, f2 ' and f3, thus the figure drawn.Therefore, developer can be seen in the interface UI to repairing
The implementing result of graphic plotting request after multiple, i.e., the figure drawn here, so as to manual confirmation, whether the graphic plotting is different
Often.
If the triggering sequencing and the multiple graphic operation instruction are modified, that is to say, that when collapse number
According to including the above-mentioned first information and third information (because the first information and the second information cannot exist simultaneously in crash data),
And the repair data include the multiple graphic operation instruction reparation after triggering sequencing, and, it is described at least one
It is in the case where parameter after the reparation of graphic operation instruction, then successively suitable according to the modified triggering in sandbox program
Sequence executes modified the multiple graphic operation instruction, the figure drawn.
And due to above-mentioned steps can according to repair data, come modify to the triggering sequencing of record (such as
Modified triggering sequencing is followed successively by f2, f1 and f3), and modify to the multiple graphic operation instruction of record
(for example, the type of the f1 parameter a carried is revised as float type from int type).
So in this step, can in sandbox program according to modified triggering sequencing, in sandbox program according to
Secondary execution f2, modified f1 and f3, thus the figure drawn.Therefore, developer can see pair in the interface UI
The implementing result of graphic plotting request after reparation, i.e., the figure drawn here, so as to manual confirmation, whether the graphic plotting is different
Often.
It should be noted that between each step executed after step 103 in the present embodiment and above-mentioned steps 104
Execute sequence, the disclosure is without limitation.
In this way, on the one hand the embodiment of the present disclosure instructs whether will appear figure to verify multiple graphic operations after repairing
Exception is drawn, if the execution of multiple graphic operations instruction on the other hand after the reparation causes drafting abnormal, in order to ensure not
The operation of the host process of application program is influenced, in the embodiments of the present disclosure, can execute being intercepted and pass through in sandbox program
The multiple graphic operations instruction repaired is crossed, thus the figure drawn, in this way, developer can identify the figure of drafting
Whether mistake or abnormal is occurred, consequently facilitating providing reference frame to manual analysis crash reason.
Since sandbox program is independently of above-mentioned application program, multiple figures after the reparation is executed in sandbox program
Shape operational order will not influence the normal operation of application program.
In a kind of possible embodiment, intercepted prompt can also be executed using sandbox program and there is collapse number
According to multiple graphic operations instruction promoted and figure grasped so that whether verify the judging result that neural network model provides accurate
Make the bug location efficiency and accuracy rate of software.For the drilling to the multiple graphic operations instruction intercepted using sandbox program pin
Show process, the demonstration in above-described embodiment, using sandbox program to multiple graphic operations instruction after the reparation intercepted
Journey is similar, and which is not described herein again.
Fig. 3 is a kind of structural block diagram of the analytical equipment of graphic operation shown according to an exemplary embodiment.Referring to figure
3, which includes:
Blocking module 301 is configured as intercepting the corresponding multiple figures of the graphic plotting request being triggered in application program
Shape operational order；
Logging modle 302 is configured as the triggering sequencing for the multiple graphic operation instruction that record is intercepted；
Module 303 is obtained, is configured as the multiple graphic operation instruction and the triggering sequencing being input to pre-
The trained neural network model for being used to carry out graphic operation instruction collapse analysis is first passed through, to obtain the collapse of graphic operation
Data and repair data；
Module 304 is provided, is configured as exporting the crash data and the repair data.
In a kind of possible embodiment, the blocking module 301 includes:
Receiving submodule is configured as receiving the corresponding multiple figures of the graphic plotting request being triggered in application program
Operational order；
Cache sub-module is configured as according to triggering sequencing successively caching the multiple graphic operation instruction；
Submodule is intercepted, is configured as when receiving default end signal relevant to graphic operation, will receive
The multiple graphic operation instruction cached before the default end signal is intercepted.
In a kind of possible embodiment, the crash data includes one of the first information and the second information, and/or,
Third information:
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application program to collapse
It bursts；
Second information indicates that the multiple graphic operation instructs corresponding combination of function that the application program is caused to collapse
It bursts；
The third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
The application crash.
In a kind of possible embodiment, when the crash data includes the first information, the repair data
Triggering sequencing after reparation including the multiple graphic operation instruction；
When the crash data includes second information, the repair data includes that the graphic plotting request corresponds to
Reparation after combination of function；
When the crash data includes the third information, the repair data includes at least one described graphic operation
Parameter after the reparation of instruction.
In a kind of possible embodiment, described device further include:
Modified module is configured as the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction
Under, it modifies according to the repair data to the multiple graphic operation instruction intercepted, and/or, according to the reparation
Data modify to the triggering sequencing of record；
First execution module, if being configured as, the triggering sequencing is modified and the multiple graphic operation instructs
It is not modified, then executes the multiple figure behaviour of interception according to the modified triggering sequencing in sandbox program
It instructs, the figure drawn；
Second execution module is modified and the triggering sequencing if being configured as the multiple graphic operation instruction
It is not modified, then executes modified the multiple figure behaviour according to the triggering sequencing of record in sandbox program
It instructs, the figure drawn；
Third execution module, if be configured as the triggering sequencing and the multiple graphic operation instruction repaired
Change, then executes modified the multiple graphic operation according to the modified triggering sequencing in sandbox program and refer to
It enables, the figure drawn.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
Fig. 4 is a kind of block diagram of the device 800 of analysis for graphic operation shown according to an exemplary embodiment.Example
Such as, device 800 can be mobile phone, computer, digital broadcasting terminal, messaging device, game console, and plate is set
It is standby, Medical Devices, body-building equipment, personal digital assistant etc..
Referring to Fig. 4, device 800 may include following one or more components: processing component 802, memory 804, electric power
Component 806, multimedia component 808, audio component 810, the interface 812 of input/output (I/O), sensor module 814, and
Communication component 816.
The integrated operation of the usual control device 800 of processing component 802, such as with display, telephone call, data communication, phase
Machine operation and record operate associated operation.Processing component 802 may include that one or more processors 820 refer to execute
It enables, to perform all or part of the steps of the methods described above.In addition, processing component 802 may include one or more modules, just
Interaction between processing component 802 and other assemblies.For example, processing component 802 may include multi-media module, it is more to facilitate
Interaction between media component 808 and processing component 802.
Memory 804 is configured as storing various types of data to support the operation in equipment 800.These data are shown
Example includes the instruction of any application or method for operating on device 800, contact data, and telephone book data disappears
Breath, picture, video etc..Memory 804 can be by any kind of volatibility or non-volatile memory device or their group
It closes and realizes, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM) is erasable to compile
Journey read-only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, flash
Device, disk or CD.
Power supply module 806 provides electric power for the various assemblies of device 800.Power supply module 806 may include power management system
System, one or more power supplys and other with for device 800 generate, manage, and distribute the associated component of electric power.
Multimedia component 808 includes the screen of one output interface of offer between described device 800 and user.One
In a little embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, screen
Curtain may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or more touch sensings
Device is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding action
Boundary, but also detect duration and pressure associated with the touch or slide operation.In some embodiments, more matchmakers
Body component 808 includes a front camera and/or rear camera.When equipment 800 is in operation mode, such as screening-mode or
When video mode, front camera and/or rear camera can receive external multi-medium data.Each front camera and
Rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 810 is configured as output and/or input audio signal.For example, audio component 810 includes a Mike
Wind (MIC), when device 800 is in operation mode, when such as call mode, recording mode, and voice recognition mode, microphone is matched
It is set to reception external audio signal.The received audio signal can be further stored in memory 804 or via communication set
Part 816 is sent.In some embodiments, audio component 810 further includes a loudspeaker, is used for output audio signal.
I/O interface 812 provides interface between processing component 802 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and lock
Determine button.
Sensor module 814 includes one or more sensors, and the state for providing various aspects for device 800 is commented
Estimate.For example, sensor module 814 can detecte the state that opens/closes of equipment 800, and the relative positioning of component, for example, it is described
Component is the display and keypad of device 800, and sensor module 814 can be with 800 1 components of detection device 800 or device
Position change, the existence or non-existence that user contacts with device 800,800 orientation of device or acceleration/deceleration and device 800
Temperature change.Sensor module 814 may include proximity sensor, be configured to detect without any physical contact
Presence of nearby objects.Sensor module 814 can also include optical sensor, such as CMOS or ccd image sensor, at
As being used in application.In some embodiments, which can also include acceleration transducer, gyro sensors
Device, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 816 is configured to facilitate the communication of wired or wireless way between device 800 and other equipment.Device
800 can access the wireless network based on communication standard, such as WiFi, carrier network (such as 2G, 3G, 4G or 5G) or them
Combination.In one exemplary embodiment, communication component 816 is received via broadcast channel from the wide of external broadcasting management system
Broadcast signal or broadcast related information.In one exemplary embodiment, the communication component 816 further includes near-field communication (NFC)
Module, to promote short range communication.For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) can be based in NFC module
Technology, ultra wide band (UWB) technology, bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, device 800 can be believed by one or more application specific integrated circuit (ASIC), number
Number processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array
(FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for executing the above method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 804 of instruction, above-metioned instruction can be executed by the processor 820 of device 800 to complete the above method.For example,
The non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk
With optical data storage devices etc..
In the exemplary embodiment, a kind of application program including instruction, the memory for example including instruction are additionally provided
804, above-metioned instruction can be executed by the processor 820 of device 800 to complete the above method.For example, the non-transitory computer
Readable storage medium storing program for executing can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk and optical data storage devices etc..
Fig. 5 is a kind of block diagram of the device 1900 of analysis for graphic operation shown according to an exemplary embodiment.
For example, device 1900 may be provided as a server.Referring to Fig. 5, device 1900 includes processing component 1922, is further wrapped
One or more processors and memory resource represented by a memory 1932 are included, it can be by processing component for storing
The instruction of 1922 execution, such as application program.The application program stored in memory 1932 may include one or one with
On each correspond to one group of instruction module.In addition, processing component 1922 is configured as executing instruction, to execute above-mentioned side
Method ...
Device 1900 can also include that a power supply module 1926 be configured as the power management of executive device 1900, and one
Wired or wireless network interface 1950 is configured as device 1900 being connected to network and input and output (I/O) interface
1958.Device 1900 can be operated based on the operating system for being stored in memory 1932, such as Windows ServerTM, Mac
OS XTM, UnixTM, LinuxTM, FreeBSDTM or similar.
It should be noted that the executing subject of the disclosure can be mobile phone, computer, digital broadcast terminal, message
Transceiver, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant etc.；It is also possible to server.
As electronic equipment such as mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, doctor
Treat equipment, body-building equipment, whens personal digital assistant etc., as shown in Figure 4.When electronic equipment is server, as shown in Figure 5.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
Its embodiment.The disclosure is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claim is pointed out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the accompanying claims.
Claims (10)
1. a kind of analysis method of graphic operation characterized by comprising
Intercept the corresponding multiple graphic operations instruction of the graphic plotting request being triggered in application program；
Record the triggering sequencing for the multiple graphic operation instruction intercepted；
The multiple graphic operation instruction and the triggering sequencing are input to trained in advance be used for figure behaviour
Make the neural network model that instruction carries out collapse analysis, to obtain the crash data and repair data of graphic operation；
The crash data and the repair data are exported.
2. the analysis method of graphic operation according to claim 1, which is characterized in that the crash data includes the first letter
One of breath and the second information, and/or, third information:
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application crash；
Second information indicates that the multiple graphic operation instructs corresponding combination of function to cause the application crash；
It is described that the third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
Application crash.
3. the analysis method of graphic operation according to claim 2, which is characterized in that
When the crash data includes the first information, the repair data includes repairing for the multiple graphic operation instruction
Triggering sequencing after multiple；
When the crash data includes second information, the repair data, which includes that the graphic plotting request is corresponding, to be repaired
Combination of function after multiple；
When the crash data includes the third information, the repair data includes at least one graphic operation instruction
Reparation after parameter.
4. the analysis method of graphic operation according to claim 3, which is characterized in that described by the multiple graphic operation
Instruction and the triggering sequencing are input to trained in advance for carrying out the mind of collapse analysis to graphic operation instruction
Through network model, after the crash data and repair data to obtain graphic operation, the method also includes:
In the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction, according to the repair data pair
The multiple graphic operation instruction intercepted is modified, and/or, it is first according to the triggering of the repair data to record
It sequentially modifies afterwards；
If the triggering sequencing is modified and the multiple graphic operation instruction is not modified, pressed in sandbox program
According to the modified triggering sequencing, the multiple graphic operation instruction of interception, the figure drawn are executed；
If the multiple graphic operation instruction is modified and the triggering sequencing is not modified, pressed in sandbox program
According to the triggering sequencing of record, modified the multiple graphic operation instruction, the figure drawn are executed；
If the triggering sequencing and the multiple graphic operation instruction are modified, according to modification in sandbox program
The triggering sequencing afterwards executes modified the multiple graphic operation instruction, the figure drawn.
5. a kind of analytical equipment of graphic operation characterized by comprising
Blocking module is configured as the corresponding multiple graphic operations of the graphic plotting request being triggered in interception application program and refers to
It enables；
Logging modle is configured as the triggering sequencing for the multiple graphic operation instruction that record is intercepted；
Module is obtained, is configured as instructing the multiple graphic operation and the triggering sequencing is input to and pre- first passes through instruction
The experienced neural network model for being used to carry out graphic operation instruction collapse analysis, to obtain the crash data of graphic operation and repair
Complex data；
Module is provided, is configured as exporting the crash data and the repair data.
6. the analytical equipment of graphic operation according to claim 5, which is characterized in that the crash data includes the first letter
One of breath and the second information, and/or, third information:
Wherein, the first information indicates that the triggering sequencing of the multiple graphic operation instruction causes the application crash；
Second information indicates that the multiple graphic operation instructs corresponding combination of function to cause the application crash；
It is described that the third information indicates that the parameter of at least one graphic operation instruction in the multiple graphic operation instruction causes
Application crash.
7. the analytical equipment of graphic operation according to claim 6, which is characterized in that
When the crash data includes the first information, the repair data includes repairing for the multiple graphic operation instruction
Triggering sequencing after multiple；
When the crash data includes second information, the repair data, which includes that the graphic plotting request is corresponding, to be repaired
Combination of function after multiple；
When the crash data includes the third information, the repair data includes at least one graphic operation instruction
Reparation after parameter.
8. the analytical equipment of graphic operation according to claim 7, which is characterized in that described device further include:
Modified module is configured as in the case where receiving the target instruction target word for indicating to repair the multiple graphic operation instruction,
It modifies according to the repair data to the multiple graphic operation instruction intercepted, and/or, according to the repair data
It modifies to the triggering sequencing of record；
First execution module, if be configured as the triggering sequencing modified and the multiple graphic operation instruction not by
Modification, then according to the modified triggering sequencing in sandbox program, the multiple graphic operation for executing interception refers to
It enables, the figure drawn；
Second execution module, if be configured as the multiple graphic operation instruction modified and the triggering sequencing not by
Modification then executes modified the multiple graphic operation and refers in sandbox program according to the triggering sequencing of record
It enables, the figure drawn；
Third execution module, if be configured as the triggering sequencing and the multiple graphic operation instruction modified,
Modified the multiple graphic operation instruction then is executed according to the modified triggering sequencing in sandbox program,
The figure drawn.
9. a kind of electronic equipment characterized by comprising
Processor；
For storing the memory of the processor-executable instruction；
Wherein, the processor is configured to executing to realize the figure as described in any one of claim 1 to claim 4
Operation performed by the analysis method of shape operation.
10. a kind of non-transitorycomputer readable storage medium, which is characterized in that when the instruction in the storage medium is by electronics
When the processor of equipment executes, so that the electronic equipment is able to carry out one kind to realize as in claim 1 to claim 4
Operation performed by the analysis method of graphic operation described in any one.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112631490A (en) * | 2020-12-30 | 2021-04-09 | 北京飞讯数码科技有限公司 | Display interface control method and device, computer equipment and storage medium |
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