CN109343853A - A kind of abnormality recognition method and equipment of application program - Google Patents
A kind of abnormality recognition method and equipment of application program Download PDFInfo
- Publication number
- CN109343853A CN109343853A CN201810942567.9A CN201810942567A CN109343853A CN 109343853 A CN109343853 A CN 109343853A CN 201810942567 A CN201810942567 A CN 201810942567A CN 109343853 A CN109343853 A CN 109343853A
- Authority
- CN
- China
- Prior art keywords
- application program
- program
- abnormal
- value
- indicator identifiers
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/40—Transformation of program code
- G06F8/41—Compilation
- G06F8/44—Encoding
- G06F8/443—Optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- Debugging And Monitoring (AREA)
Abstract
The present invention is suitable for technical field of information processing, provides the abnormality recognition method and equipment of a kind of application program, comprising: obtain the program file of application program, and abnormal indicator identifiers are added in program file；Adjust the parameter value of abnormal indicator identifiers；Abnormality monitoring thread is created, and is added in the program identification to eavesdropping target's list of abnormality monitoring thread of application program；If detecting, any program identifies corresponding application program launching in eavesdropping target's list, calls abnormality monitoring thread to identify the abnormal indicator identifiers of the application program；If abnormal indicator identifiers are the second place value, generate about the information closed for illustrating application exception.The present invention is when starting next time, determine whether last operation is normally closed by abnormal indicator identifiers, so that the accuracy of the assessment of anomalous identification and stability is improved, convenient for optimizing adjustment to application program, loophole existing for program is reduced, the safety of application program is improved.
Description
Technical field
The invention belongs to the abnormality recognition methods and equipment of technical field of information processing more particularly to a kind of application program.
Background technique
With the continuous development of mobile device technology, critical function carrier of the application program as mobile device is stablized
Property and reliability directly affect the performance of mobile device.And index one of of the abnormal rate as measurement application program stability,
Accurately identifying abnormal conditions and generating exception record is particularly important.The abnormality recognition method of existing application program, mainly
An exception record is created when application program is abnormal, but when there are larger abnormal conditions, such as program is transported on backstage
When row because device resource occupy it is excessively high, and when leading to abnormal exit, application program there is no and by enough asset creations it is abnormal
Record, the frequency of abnormity for causing statistics to obtain can have biggish difference, the standard of anomalous identification with the frequency of abnormity actually occurred
True property is lower, to reduce the accuracy of the assessment for stability, is unfavorable for optimizing application program adjustment.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of abnormality recognition method of application program and equipment, it is existing to solve
The abnormality recognition method of some application programs, cause the obtained frequency of abnormity of statistics can exist with the frequency of abnormity actually occurred compared with
The accuracy of big difference, anomalous identification is lower, to reduce the accuracy of the assessment for stability, is unfavorable for application
Program optimizes the problem of adjustment.
The first aspect of the embodiment of the present invention provides a kind of abnormality recognition method of application program, comprising:
The program file of application program is obtained, and abnormal indicator identifiers are added in described program file；Wherein, institute
The default value for stating abnormal indicator identifiers is the first place value；
The operating status of application program described in real-time monitoring, if detecting, the application program switches from foreground operating status
To background operation state, then adjusting the abnormal indicator identifiers is the second place value；If detecting the application program from backstage
Operating status switches to front stage operation state, then adjusting the abnormal indicator identifiers is the first place value；
Abnormality monitoring thread is created, and adds the program identification of the application program to the monitoring of the abnormality monitoring thread
In list object；
If detecting, any program identifies corresponding application program launching in eavesdropping target's list, is called described different
Normal listening thread identifies the abnormal indicator identifiers of the application program；
If the exception indicator identifiers are the second place value, generate about for illustrating that the application exception is closed
Information.
The second aspect of the embodiment of the present invention provides a kind of anomalous identification equipment of application program, including memory, place
The computer program managing device and storage in the memory and can running on the processor, the processor execute institute
Each step of first aspect is realized when stating computer program.
The third aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer program, and each step of first aspect is realized when the computer program is executed by processor.
The abnormality recognition method and equipment for implementing a kind of application program provided in an embodiment of the present invention have below beneficial to effect
Fruit:
The embodiment of the present invention is abnormal by adding in the program file to the destination application for needing to carry out anomalous identification
Indicator identifiers, and the exception indicator identifiers are adjusted according to preset switching adjustment algorithm, destination application each time
When being activated, the value of the exception indicator identifiers is detected by creating obtained abnormality monitoring thread, so that it is determined that the target is answered
Whether it is normally closed in upper primary operational process with program；Destination application is normally closed usually in foreground
Operating status terminates the operation of destination application by out code, at this time since destination application is in foreground fortune
Row state, therefore abnormal indicator identifiers can be the first place value；If destination application is during running background, because of resource
It is insufficient and lead to abnormal closing, at this time since destination application last time handover operation is from foreground running state conversion to rear
Platform operating status, therefore abnormal indicator identifiers will be the second place value；It can be seen that when destination application is restarted
When, if abnormality monitoring thread detect the exception identifier be the second place value, can determine the destination application be
What backstage was closed extremely, so that anomalous identification can be realized by the value of abnormal identifier.With the exception of existing application
Recognition methods is compared, and is not relying on application program and is created exception information in abnormal cases, but when starting next time, pass through
Abnormal indicator identifiers determine whether last operation is normally closed, to improve the accuracy of anomalous identification, further
The accuracy of the assessment of stability is improved, convenient for optimizing adjustment to application program, reduces the existing leakage of application program
The risk that hole and reduction criminal distort application program, substantially increases the safety of application program.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of implementation flow chart of the abnormality recognition method for application program that first embodiment of the invention provides；
Fig. 2 is a kind of abnormality recognition method S102 specific implementation flow for application program that second embodiment of the invention provides
Figure；
Fig. 3 is a kind of abnormality recognition method S101 specific implementation flow for application program that third embodiment of the invention provides
Figure；
Fig. 4 is a kind of abnormality recognition method specific implementation flow chart for application program that fourth embodiment of the invention provides；
Fig. 5 is a kind of specific implementation flow of the abnormality recognition method for application program that fifth embodiment of the invention provides
Figure；
Fig. 6 is a kind of structural block diagram of the anomalous identification equipment for application program that one embodiment of the invention provides；
Fig. 7 be another embodiment of the present invention provides a kind of application program anomalous identification equipment schematic diagram.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The embodiment of the present invention is abnormal by adding in the program file to the destination application for needing to carry out anomalous identification
Indicator identifiers, and the exception indicator identifiers are adjusted according to preset switching adjustment algorithm, destination application each time
When being activated, the value of the exception indicator identifiers is detected by creating obtained abnormality monitoring thread, so that it is determined that the target is answered
Whether it is normally closed in upper primary operational process with program；Destination application is normally closed usually in foreground
Operating status terminates the operation of destination application by out code, at this time since destination application is in foreground fortune
Row state, therefore abnormal indicator identifiers can be the first place value；If destination application is during running background, because of resource
It is insufficient and lead to abnormal closing, at this time since destination application last time handover operation is from foreground running state conversion to rear
Platform operating status, therefore abnormal indicator identifiers will be the second place value；It can be seen that when destination application is restarted
When, if abnormality monitoring thread detect the exception identifier be the second place value, can determine the destination application be
What backstage was closed extremely, so that anomalous identification can be realized by the value of abnormal identifier, solve existing application program
Abnormality recognition method, cause the obtained frequency of abnormity of statistics that can have biggish difference with the frequency of abnormity actually occurred, it is different
The other accuracy of common sense is lower, to reduce the accuracy of the assessment for stability, is unfavorable for carrying out application program excellent
The problem of changing adjustment.
In embodiments of the present invention, the executing subject of process is the anomalous identification equipment of application program.The application program
Anomalous identification equipment includes but is not limited to: server, computer, smart phone and tablet computer etc. have the different of application program
The equipment of normal identification function.Fig. 1 shows the realization of the abnormality recognition method of the application program of first embodiment of the invention offer
Flow chart, details are as follows:
In S101, the program file of application program is obtained, and abnormal indicator identifiers are added to described program file
It is interior；Wherein, the default value of the abnormal indicator identifiers is the first place value.
In the present embodiment, the anomalous identification equipment of application program is to monitor the abnormal conditions of application program, needs pair
The program file of application program detected adds an abnormal indicator identifiers, by the ginseng for detecting the exception indicator identifiers
Numerical value, it is determined whether be abnormal situation.Therefore, in the S101 the step of, anomalous identification equipment can be based on the journey of application program
Sequence mark, inquires the corresponding program file of the program identification out of anomalous identification equipment memory space.Particularly, if the exception
Identification equipment is an external equipment, i.e., the terminal and anomalous identification equipment that the required application program detected is installed are in not
With equipment when, in this case, anomalous identification equipment can be established logical by the terminal that serial line interface and application program be installed
Letter connection, and communicated by the terminal bus that serial line interface is connected with the storage unit of terminal, and the journey based on application program
Sequence mark, determines its corresponding program file.
In the present embodiment, anomalous identification equipment, can be in the program file after obtaining the program file of application program
The abnormal indicator identifiers of middle addition one can be by identifying the exception indicator identifiers in starting application file every time
Parameter value determine it is last run the application program during, if the case where abnormal bolt down procedure has occurred.Specifically,
Extension functional areas are contained in the program file of each application program, can be in application program during version updating, it will
The function distributing of required addition is based on this, anomalous identification equipment can be by the exception indicator identifiers in the extension functional areas
It is added in the extension functional areas, so that the function to the application program expands.Optionally, abnormal sign is being added
When running the application program after symbol for the first time, application program can read the data of the extension functional areas, be added to exception if detecting
Indicator identifiers then can configure corresponding adjustment thread for the exception indicator identifiers, by adjusting thread to the abnormal index
The parameter value of identifier is adjusted.
In the present embodiment, due to that can start to detect the exception indicateing arm when starting application program in anomalous identification equipment
The parameter value of symbol is known to determine whether last application program is closed extremely, therefore in order to guarantee to be added to abnormal sign
When starting application program after symbol for the first time, application program can be operated normally, the default value of the exception indicator identifiers can be provided with
First place value.
In S102, the operating status of application program described in real-time monitoring, if detecting, the application program is transported from foreground
Row state switches to background operation state, then adjusting the abnormal indicator identifiers is the second place value；If detecting the application
Program switches to front stage operation state from background operation state, then adjusting the abnormal indicator identifiers is the first place value.
In the present embodiment, abnormal indicator identifiers can be by preset adjustment algorithm to the abnormal indicateing arm of application program
The parameter value for knowing symbol is adjusted.Specifically, preset adjustment algorithm are as follows: if detecting application program from foreground operating status
It is switched to background operation state, then abnormal indicator identifiers can be adjusted to the second place value by the first place value；If detecting application
Program switches to front stage operation state from background operation state, then abnormal indicator identifiers is adjusted to first by the second place value
Value, in other words, when application program is during normal operation, i.e., there is no the abnormal conditions such as abnormal closing or equipment delay machine
Under, for application program in the state of front stage operation, which can be the first place value；And when application program is on backstage
In the state of operation, which can be the second place value.And application program the case where being normally closed is specifically to use
Family terminates the operation of application program by initiating out code in the state that application program is in front stage operation, and at this time
Application program is necessarily in front stage operation state, i.e. the parameter value of the exception indicator identifiers is the first place value.It is possible thereby to really
It is fixed, if in the state that application program is normally closed, which can be always held at the first place value, until next
After secondary starting, from foreground, operating status, which is switched to background operation state just, can change the parameter value of the exception indicator identifiers.
In the present embodiment, anomalous identification equipment can create an identifier adjustment thread in main thread, and need to
The program identification for each application program to be carried out abnormality detection is added in the adjustment list of identifier adjustment thread, thus
When the operating status for detecting any application program in the adjustment list switches, thread pair can be adjusted by the identifier
The parameter value of its abnormal indicator identifiers is adjusted.
In S103, abnormality monitoring thread is created, and adds the program identification of the application program to the abnormality monitoring
In eavesdropping target's list of thread.
In the present embodiment, anomalous identification equipment will create an abnormality monitoring thread, which is used for
When application program is activated, the parameter value of the abnormal identifier of each application program is detected, to judge application program upper one
Whether closed extremely during secondary operation.Since the number of the application program run in anomalous identification equipment is more, but
Not each application program be required to carry out anomalous identification, therefore, anomalous identification equipment in order to improve the efficiency of detection with
And the monitoring load of abnormality monitoring thread is reduced, each program identification for needing the application program monitored can be added to monitoring pair
As in list, and the incidence relation between abnormality monitoring thread and eavesdropping target's list is established, to realize abnormality monitoring line
Journey carries out abnormality detection operation to the application program in eavesdropping target's list.
In the present embodiment, the detailed process for executing abnormality detection operation can be with are as follows: when anomalous identification equipment detects certain
When one application program is activated, the program identification of the application program can be obtained, judges whether the application identities arrange in eavesdropping target
In table, and if it exists, then activate abnormality monitoring thread, and execute the relevant operation of S104；Conversely, if it does not exist, then directly initiating
The application program.
In S104, if detecting, any program identifies corresponding application program launching in eavesdropping target's list,
The abnormality monitoring thread is called to identify the abnormal indicator identifiers of the application program.
It in the present embodiment, can if anomalous identification equipment detects that the application program in eavesdropping target's list is activated
Abnormality monitoring thread is activated, and the exception sign in the program file of the application program is read by the abnormality monitoring thread
The parameter value of symbol.If the parameter value of the exception indicator identifiers is the first place value, then it represents that the last normal pass of the application program
It closes, the application program can be directly initiated；Conversely, executing the correlation of S105 if the exception indicator identifiers are the second place value
Operation.
In S105, if the exception indicator identifiers are the second place value, generate about described using journey for illustrating
The information that sequence is closed extremely.
In the present embodiment, when anomalous identification equipment detects a certain application program launching, abnormal indicator identifiers
Place value be the second place value, then it represents that the state when closing application program is background operation state, i.e., not by normal
Closing means close the application program, therefore anomalous identification equipment can generate one for illustrating application exception
The information of closing, so that the number for the information that the administrator of application program can be closed extremely by statistics, determines application program
Collapse rate and stability, and whether need to optimize application program based on above-mentioned two parameter decision.
Optionally, which may include: to be abnormal program identification, the exception of the application program of situation
Time of origin and anomaly analysis information.Wherein, the acquisition modes of abnormal time of origin can be with are as follows: due to provided in this embodiment
Anomalous identification is the process of postposition identification, i.e., exception information is not produced at the time of abnormal conditions occur, therefore,
In order to obtain abnormal time of origin, anomalous identification equipment can obtain all running logs of the application program, and choose with it is current
Moment starts the time as object run log, and according to the application recorded in object run log at a distance of nearest running log
And runing time is applied, determine the stop time of the application program, and the stop time is identified as abnormal hair
The raw time.Wherein it is determined that the concrete mode of anomaly analysis information can be with are as follows: anomalous identification equipment is remembered according in object run log
The parameter presets such as the resources occupation rate, processing speed, the equipment entirety occupancy that are loaded with, determining that this is closed extremely is due to equipment
Caused by load excessive or be application program itself there are caused by loophole, thus obtain an anomaly analysis as a result,
And anomaly analysis information is generated according to above-mentioned relevant parameter and the anomaly analysis result.
Above as can be seen that a kind of abnormality recognition method of application program provided in an embodiment of the present invention by need into
Abnormal indicator identifiers are added in the program file of the destination application of row anomalous identification, and are adjusted and calculated according to preset switching
Method adjusts the exception indicator identifiers, when destination application is activated each time, by creating obtained abnormality monitoring line
Journey detects the value of the exception indicator identifiers, so that it is determined that whether the destination application is normal in upper primary operational process
It closes；Destination application is normally closed usually in front stage operation state, is answered by out code to terminate target
With the operation of program, at this time since destination application is in front stage operation state, abnormal indicator identifiers can be first
Place value；If destination application during running background, leads to abnormal closing because of inadequate resource, at this time since target is answered
It is from foreground running state conversion to background operation state with program last time handover operation, therefore abnormal indicator identifiers will
For the second place value；It can be seen that when destination application is restarted, if abnormality monitoring thread detects that the exception identifies
When symbol is the second place value, then it can determine that the destination application is closed extremely on backstage, to pass through abnormal mark
Anomalous identification can be realized in the value of symbol.Compared with the abnormality recognition method of existing application, application program is not relying on different
Exception information is created in normal situation, but when starting next time, whether last operation is determined by abnormal indicator identifiers
Be normally closed, to improve the accuracy of anomalous identification, further improve the accuracy of the assessment of stability, convenient for pair
Application program optimizes adjustment, reduces loophole existing for application program and reduces criminal and usurps to application program
The risk changed substantially increases the safety of application program.
Fig. 2 shows the specific realities of the abnormality recognition method S102 of application program of second embodiment of the invention offer a kind of
Existing flow chart.It is shown in Figure 2, embodiment, a kind of anomalous identification side of application program provided in this embodiment are stated relative to Fig. 1
S102 includes: S1021~S1024 in method, and specific details are as follows:
In S1021, start-up operation counter and pausing operation counter are configured for the application program；It is detecting
When enabled instruction about the application program, increase the first numerical value of the start-up operation counter；It is detecting about institute
When stating the pause instruction of application program, increase the second value of the pausing operation counter.
In the present embodiment, the anomalous identification equipment of application program is in addition to being added to application program for abnormal indicator identifiers
Program data packet outside, can also for the application program configure two counters, respectively start-up operation counter and pause behaviour
Make counter, by the size of the clocking value of above-mentioned two counter, determines that application program is in front stage operation state or is
In background operation state.
In the present embodiment, anomalous identification equipment generates a starting about application program in detecting equipment and refers to
When enabling, i.e., expression user activates the application program, then carries out to the start-up operation counter plus one operates, and updates starting behaviour
Make the count value of counter.It should be noted that being transported when application program switches to open state from closed state, and from backstage
Row state switches to during front stage operation state two, can generate enabled instruction to activate the application program.
In the present embodiment, anomalous identification equipment generates a pause about application program in detecting equipment and refers to
When enabling, pausing operation counter can be carried out plus one operates, and update the count value of the pausing operation counter.It needs to illustrate
When being that when application program is during front stage operation, user needs to operate other applications, or returning to main interface, meeting
A pause instruction is generated so that the operating parameter of current application program is stored in buffer area, and suspends the operation of application program.
In conclusion application program during being switched to open state from closed state, can adjust starting counter
Count value, i.e., starting counter count value can prior to pause counter be adjusted, i.e., when application program runs on foreground
Under state, the count value for starting counter can be greater than the count value of pause counter；And when application program runs on background state
Under, the count value for starting counter can be identical as the pause count value of counter, i.e., anomalous identification equipment passes through detection above-mentioned two
The numerical values recited of a counter then can recognize the operating status of application program.
In S1022, if current time meets preset monitoring running state condition, whether first numerical value is judged
Greater than the second value.
In the present embodiment, monitoring running state condition has can be set in anomalous identification equipment, when detecting current time
When meeting preset monitoring running state condition, then the relevant operation of S1022 can be executed.Wherein, the monitoring running state condition
Can be, when detect generate operational order about application program in equipment when, then execute the relevant operation of S1022, due to
Switchover operation state must rely on operational order, therefore the operation of S1022 is executed when detecting operational order, can be instant
Determine that the running state recognition of application program changes, so as to adjust the place value of abnormal indicator identifiers.Certainly, abnormal
Identify equipment can also with preset monitoring cycle, the count value of the above-mentioned two counter of interval acquiring, judge the first numerical value with
And the size relation between second value.
In the present embodiment, if the first numerical value is greater than second value, the relevant operation of S1023 is executed；If the first numerical value
Less than or equal to second value, then the relevant operation of S1024 is executed.It should be noted that can be weighed when application program is closed
The value for setting above-mentioned two counter sets 0 for the value of start-up operation counter and pausing operation counter.
In S1023, if first numerical value be greater than the second value, identify the application program state be from
Background operation state switches to front stage operation state.
In the present embodiment, since the first numerical value is greater than second value, then it represents that the number for executing start-up operation, which is greater than, to be held
The number of row pausing operation is in front stage operation state so as to judge that application program is presently at starting state, because
This can determine application program from background operation state switching value front stage operation state.
In S1024, if first numerical value is less than or equal to the second value, the shape of the application program is identified
State is to switch to background operation state from foreground operating status.
In the present embodiment, since the first numerical value is less than or equal to second value, then it represents that execute the number of start-up operation
Less than or equal to the number for executing pausing operation, and start-up operation is inevitable prior to pausing operation execution, therefore may determine that application
Program is in background operation state, it can determines application program from foreground operating status switching value background operation state.
In embodiments of the present invention, by configure starting counter and pause counter, and compare two count values it
Between size, realize recognition application be operate in foreground or be operate in backstage, implementation is quick, to improve
The efficiency of Application Status identification.
Fig. 3 shows the specific reality of the abnormality recognition method S101 of application program of third embodiment of the invention offer a kind of
Existing flow chart.It is shown in Figure 3, relative to embodiment described in Fig. 1, a kind of anomalous identification of application program provided in this embodiment
S101 includes S1011~S1013 in method, and specific details are as follows:
In S1011, the code data of the launching process of the application program is obtained from described program file.
In the present embodiment, the anomalous identification equipment of application program, can be right after obtaining the program file of application program
The program file is parsed, and the code data corresponding to the launching process of acquisition application program from the program file.By
It is one and non-declarative symbol, in order to subsequent when adding for the first time in needing abnormal indicator identifiers to be added
In operation, application program can be adjusted by parameter value of the preset adjustment algorithm to the exception indicator identifiers, therefore
It needs in application program launching, legitimacy statement is carried out to the exception indicator identifiers, and the operation is to pass through application program
Launching process execute.Based on this, anomalous identification equipment needs are adjusted the launching process of the application program, therefore need
Program file is parsed, determines the code data of the launching process.
In S1012, the registration paragraph of the abnormal indicator identifiers is added in the code data.
In the present embodiment, anomalous identification equipment, can be by abnormal indicateing arm after obtaining the code data of launching process
The registration paragraph for knowing symbol is added in the code data, and specifically, which is added to parameter declaration mould in code data
Block number is in, to execute together with the registration of interface each in application program and parameter operation.
In the present embodiment, the concrete mode that anomalous identification equipment obtains the registration paragraph of abnormal indicator identifiers can be with
Are as follows: the registration paragraph of either interface or parameter in parsing code data, and interface name or parameter name are deleted from registration paragraph,
Registration paragraph template is obtained, abnormal indicator identifiers are added in the registration paragraph template, to obtain the exception sign
Accord with corresponding registration paragraph.
Optionally, anomalous identification equipment can also be connected with host computer server, send and register to the host computer server
Paragraph acquisition request then receives the registration paragraph about abnormal indicator identifiers that host computer server is sent, and is added
It is added in the code data.
In S1013, the catalogue of the operation host process of the application program is inquired, and is added under the catalogue for adjusting
The operation subprocess of the whole abnormal indicator identifiers.
In the present embodiment, due to after being configured with abnormal indicator identifiers, it is also necessary to pass through preset adjustment algorithm pair
The exception indicator identifiers are adjusted, and the operation adjusted is also that application program is transferred to execute, in order to apply journey
Sequence realizes the parameter value change operation of abnormal indicator identifiers during starting, anomalous identification equipment can be in the fortune of application program
An operation subprocess is added in row host process.Wherein, the code data for running each operation subprocess under host process can be remembered
It records in running under the catalogue where host process, to create one during running host process after application program activates
For adjusting the operation sub thread of the exception indicator identifiers.
In embodiments of the present invention, by the way that abnormal indicator identifiers are added in the launching process of application program, with logical
It crosses launching process and legitimacy registration is carried out to abnormal indicator identifiers, it is then different by one adjustment of creation under operation host process
The operation subprocess of normal indicator identifiers realizes that the parameter of abnormal indicator identifiers adjusts operation, improves the standard of anomalous identification
True rate.
Fig. 4 shows a kind of specific implementation stream of the abnormality recognition method of application program of fourth embodiment of the invention offer
Cheng Tu.It is shown in Figure 4, relative to embodiment described in Fig. 1-Fig. 3, a kind of anomalous identification of application program provided in this embodiment
Method is after the generation is about the information of the application program closed extremely, further includes: S401~S404, it is specific to be described in detail
It is as follows:
Further, after the generation is about the information of the application program closed extremely, further includes:
In S401, the current time generated information closed extremely is obtained；Extremely the information closed includes different
Normal time of origin.
In the present embodiment, anomalous identification equipment will create an abnormal pass when every identification obtains an abnormal conditions
The information closed has recorded abnormal time of origin in the information closed extremely, if application program is repeatedly different in the process of running
It often closes, then S401 can acquire a plurality of information closed extremely.Wherein it is determined that the concrete mode of abnormal time of origin can be with
As described in S105, no longer illustrate one by one herein.
Optionally, in the present embodiment, the mode for triggering S401 can be with are as follows: time triggering mode and event triggering side
Formula.Time triggering mode specifically: anomalous identification equipment is provided with multiple exception levels and determines that node or exception level determine week
Phase then executes the relevant operation of S401 when detecting that current time reaches above-mentioned node or determines corresponding time point in period；
Event triggered fashion specifically: if receiving preset instruction, such as server is sent or Client-initiated exception level determines
When instruction or anomalous identification equipment generate the information closed extremely, then the relevant operation of S401 is executed.
In S402, the number of the generated information closed extremely is counted, and determines first based on the number
Outlier factor.
In the present embodiment, since the number for being abnormal closing is more, then it represents that the intensity of anomaly of the application program is got over
It is more, therefore anomalous identification equipment can count the number for the information of the current time application locks product closed extremely, and base
The first Outlier factor of the exception level for calculating application program is obtained in the number.
In S403, according to each abnormal time of origin, the abnormal occurrence frequency of the application program is determined, it will be described different
Normal occurrence frequency is identified as the second Outlier factor.
In the present embodiment, anomalous identification equipment can be counted according to the abnormal time of origin in each information closed extremely
The abnormal occurrence frequency of the application program is calculated, specific calculation can and exception hair earliest for the abnormal time of origin of acquisition
Two information closed extremely of raw time the latest determine the time span between information that two are closed extremely, when being based on this
Between the number of span and the information closed extremely, determine the exception occurrence frequency；Two genetic sequence phases can also be obtained
Two adjacent information closed extremely determine the occurrence frequency between information that two are closed extremely, to be based on each generation
Abnormal occurrence frequency of the mean value of frequency as the application program, and it is different to determine that obtained abnormal occurrence frequency is identified as second
Constant factor.
In S404, the first Outlier factor and second Outlier factor are imported into exception level transformation model, really
The exception level of the fixed application program；The exception level transformation model specifically:
ErrorLevel=10lg (Weight1*ErrorFactor1+Weight2*ErrorFactor2)
Wherein, ErrorLevel is the exception level；ErrorFactor1For first Outlier factor；
ErrorFactor2For second Outlier factor；Weight1、Weight2For predetermined coefficient.
In the present embodiment, anomalous identification equipment imports the first Outlier factor being calculated and the second Outlier factor
Into preset exception level transformation model, the exception level of the application program is determined, wherein in order to improve exception level identification
Accuracy, the first Outlier factor and the second Outlier factor can configure there are two predetermined coefficient, to above-mentioned two parameter value into
Row adjustment, the predetermined coefficient can be adjusted to obtain by anomalous identification equipment by neural network learning, can also be by user voluntarily
Setting.
In embodiments of the present invention, the first Outlier factor and the second Outlier factor are determined by the information closed extremely,
And the exception level of application program is calculated, so that exception level is capable of the intensity of anomaly of accurate identification application program, it is convenient for
The administrative staff of application program assess the stability of application program.
Fig. 5 shows a kind of specific implementation stream of the abnormality recognition method of application program of fifth embodiment of the invention offer
Cheng Tu.It is shown in Figure 5, relative to embodiment described in Fig. 4, a kind of abnormality recognition method of application program provided in this embodiment
First Outlier factor and second Outlier factor are imported into exception level transformation model described, determine that the target is answered
After the exception level of program, further includes: S501~S502, specific details are as follows:
In S501, if the exception level is more than preset outlier threshold, the journey of the application program is re-downloaded
Preface part.
In the present embodiment, the anomalous identification equipment of application program is after calculating the exception level of application program, can be with
By being compared with preset outlier threshold, judge whether the operating index of the application program is more than normal range (NR), due to answering
With program when being run in equipment, it is contemplated that the problem with the compatibility in equipment between other applications is to allow centainly
Abnormal closing rate.Therefore, if the exception level and being less than outlier threshold, then it represents that the application program is still in normal model
Interior work is enclosed, in this case, without carrying out exception response processing to the application program；Conversely, if the exception level is more than pre-
If outlier threshold, then it represents that the abnormal closing rate of the application program is excessive, it may be possible to which the program file of application program occurs
Caused by exception, in this case, anomalous identification equipment can obtain the program file of the application program from server again.
In S502, the application program is unloaded, and run the described program file re-downloaded, it is described to reinstall
Application program.
In the present embodiment, anomalous identification equipment can unload after the program file for obtaining the application program re-downloaded
The application program being installed in equipment, and the program file re-downloaded by operation are carried, the application program is reinstalled, to repair
The abnormal conditions of the multiple application program, improve the stability of application program operation.
In embodiments of the present invention, by reinstalling application in the case where exception level is more than default outlier threshold
Program improves the stability of application program operation the case where often closing extremely with repairing applications.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Fig. 6 shows a kind of structural block diagram of the anomalous identification equipment of application program of one embodiment of the invention offer, should
The each unit that the anomalous identification equipment of application program includes is used to execute each step in the corresponding embodiment of Fig. 1.Please specifically it join
Read the associated description in embodiment corresponding to Fig. 1 and Fig. 1.For ease of description, portion related to the present embodiment is illustrated only
Point.
Referring to Fig. 6, the anomalous identification equipment of the application program includes:
Program file acquiring unit 61 is added for obtaining the program file of application program, and by abnormal indicator identifiers
Into described program file；Wherein, the default value of the abnormal indicator identifiers is the first place value；
Abnormal indicator identifiers adjustment unit 62, for the operating status of application program described in real-time monitoring, if detecting
The application program switches to background operation state from foreground operating status, then adjusting the abnormal indicator identifiers is second
Value；If detecting, the application program switches to front stage operation state from background operation state, adjusts the abnormal indicateing arm
Knowing symbol is the first place value；
Abnormality monitoring thread creation unit 63 for creating abnormality monitoring thread, and adds the program of the application program
In mark to eavesdropping target's list of the abnormality monitoring thread；
Abnormal indicator identifiers recognition unit 64, if for detecting any program mark pair in eavesdropping target's list
The application program launching answered then calls the abnormality monitoring thread to identify the abnormal indicator identifiers of the application program；
Abnormal closing information generation unit 65, if being the second place value for the abnormal indicator identifiers, generate about
The information closed for illustrating the application exception.
Optionally, abnormal indicator identifiers adjustment unit 62 includes:
Counter configuration unit, for configuring start-up operation counter and pausing operation counting for the application program
Device；When detecting the enabled instruction about the application program, increase the first numerical value of the start-up operation counter；It is examining
When measuring the pause instruction about the application program, increase the second value of the pausing operation counter；
Clocking value comparing unit judges described if meeting preset monitoring running state condition for current time
Whether one numerical value is greater than the second value；
Foreground judging unit identifies the application program if being greater than the second value for first numerical value
State is to switch to front stage operation state from background operation state；
Backstage judging unit identifies the application if being less than or equal to the second value for first numerical value
The state of program is to switch to background operation state from foreground operating status.
Optionally, described program file obtaining unit 61 includes:
Code data acquiring unit, the code of the launching process for obtaining the application program from described program file
Data；
Code data adding unit, for the registration paragraph of the abnormal indicator identifiers to be added to the code data
It is interior；
Operation subprocess adjustment unit, the catalogue of the operation host process for inquiring the application program, and in the mesh
The lower addition of record is for adjusting the operation subprocess of the abnormal indicator identifiers.
Optionally, the anomalous identification equipment of the application program further include:
Abnormal closing information acquiring unit, for obtaining the current time generated information closed extremely；The exception
The information of closing includes abnormal time of origin；
First Outlier factor computing unit for counting the number of the generated information closed extremely, and is based on
The number determines the first Outlier factor；
Second Outlier factor computing unit, for determining the exception of the application program according to each abnormal time of origin
The abnormal occurrence frequency is identified as the second Outlier factor by occurrence frequency；
Exception level determination unit, for the first Outlier factor and second Outlier factor to be imported into exception level
Transformation model determines the exception level of the application program；The exception level transformation model specifically:
ErrorLevel=10lg (Weight1*ErrorFactor1+Weight2*ErrorFactor2)
Wherein, ErrorLevel is the exception level；ErrorFactor1For first Outlier factor；
ErrorFactor2For second Outlier factor；Weight1、Weight2For predetermined coefficient.
Optionally, the anomalous identification equipment of the application program further include:
Exception response unit re-downloads the application if being more than preset outlier threshold for the exception level
The program file of program；
Application program re-mounts unit, for unloading the application program, and runs the described program file re-downloaded,
To reinstall the application program.
Therefore, the anomalous identification equipment of application program provided in an embodiment of the present invention can equally work as destination application quilt
When restarting, if abnormality monitoring thread detects that the exception identifier is the second place value, the target application can be determined
Program is closed extremely on backstage, so that anomalous identification can be realized by the value of abnormal identifier.Journey is applied with existing
The abnormality recognition method of sequence is compared, and is not relying on application program and is created exception information in abnormal cases, but opens next time
When dynamic, determine whether last operation is normally closed by abnormal indicator identifiers, to improve the accurate of anomalous identification
Property, the accuracy of the assessment of stability is further improved, convenient for optimizing adjustment to application program.
Fig. 7 be another embodiment of the present invention provides a kind of application program anomalous identification equipment schematic diagram.Such as Fig. 7 institute
Show, the anomalous identification equipment 7 of the application program of the embodiment includes: processor 70, memory 71 and is stored in the storage
In device 71 and the computer program 72 that can be run on the processor 70, such as the anomalous identification program of application program.It is described
Processor 70 realizes the step in the abnormality recognition method embodiment of above-mentioned each application program when executing the computer program 72
Such as S101 shown in FIG. 1 to S105 suddenly,.Alternatively, the processor 70 realized when executing the computer program 72 it is above-mentioned each
The function of each unit in Installation practice, such as the function of module 61 to 65 shown in Fig. 6.
Illustratively, the computer program 72 can be divided into one or more units, one or more of
Unit is stored in the memory 71, and is executed by the processor 70, to complete the present invention.One or more of lists
Member can be the series of computation machine program instruction section that can complete specific function, and the instruction segment is for describing the computer journey
Implementation procedure of the sequence 72 in the anomalous identification equipment 7 of the application program.For example, the computer program 72 can be divided
At program file acquiring unit, abnormal indicator identifiers adjustment unit, abnormality monitoring thread creation unit, abnormal indicator identifiers
Recognition unit and abnormal closing information generation unit, each unit concrete function are as described above.
The anomalous identification equipment 7 of the application program can be desktop PC, notebook, palm PC and cloud clothes
Business device etc. calculates equipment.The anomalous identification equipment of the application program may include, but be not limited only to, processor 70, memory 71.
It will be understood by those skilled in the art that Fig. 7 is only the example of the anomalous identification equipment 7 of application program, do not constitute to application
The restriction of the anomalous identification equipment 7 of program may include components more more or fewer than diagram, or combine certain components, or
The different component of person, such as the anomalous identification equipment of the application program can also be set including input-output equipment, network insertion
Standby, bus etc..
Alleged processor 70 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 71 can be the internal storage unit of the anomalous identification equipment 7 of the application program, such as using
The hard disk or memory of the anomalous identification equipment 7 of program.The anomalous identification that the memory 71 is also possible to the application program is set
Standby 7 External memory equipment, such as the plug-in type hard disk being equipped in the anomalous identification equipment 7 of the application program, intelligent storage
Block (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card) etc..
Further, the memory 71 can also both including the application program anomalous identification equipment 7 internal storage unit or
Including External memory equipment.The memory 71 is used to store the anomalous identification of the computer program and the application program
Other programs and data needed for equipment.The memory 71, which can be also used for temporarily storing, have been exported or will export
Data.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of abnormality recognition method of application program characterized by comprising
The program file of application program is obtained, and abnormal indicator identifiers are added in described program file；Wherein, described different
The default value of normal indicator identifiers is the first place value；
The operating status of application program described in real-time monitoring, if after detecting that the application program is switched to from foreground operating status
Platform operating status, then adjusting the abnormal indicator identifiers is the second place value；If detecting the application program from running background
State switches to front stage operation state, then adjusting the abnormal indicator identifiers is the first place value；
Abnormality monitoring thread is created, and adds the program identification of the application program to the eavesdropping target of the abnormality monitoring thread
In list；
If detecting, any program identifies corresponding application program launching in eavesdropping target's list, calls the abnormal prison
Thread is listened to identify the abnormal indicator identifiers of the application program；
If the exception indicator identifiers are the second place value, generate about the letter closed for illustrating the application exception
Breath.
2. abnormality recognition method according to claim 1, which is characterized in that the fortune of application program described in the real-time monitoring
Row state, comprising:
Start-up operation counter and pausing operation counter are configured for the application program；It is detecting about described using journey
When the enabled instruction of sequence, increase the first numerical value of the start-up operation counter；It is detecting about the temporary of the application program
When stop instruction, increase the second value of the pausing operation counter；
If current time meets preset monitoring running state condition, judge whether first numerical value is greater than second number
Value；
If first numerical value is greater than the second value, identify that the state of the application program is to cut from background operation state
Shift to front stage operation state；
If first numerical value is less than or equal to the second value, identify that the state of the application program is from front stage operation
State switches to background operation state.
3. abnormality recognition method according to claim 1, which is characterized in that described that abnormal indicator identifiers are added to institute
It states in program file, comprising:
The code data of the launching process of the application program is obtained from described program file；
The registration paragraph of the abnormal indicator identifiers is added in the code data；
The catalogue of the operation host process of the application program is inquired, and addition is indicated for adjusting the exception under the catalogue
The operation subprocess of identifier.
4. abnormality recognition method according to claim 1-3, which is characterized in that answered in the generation about described
After the information of program closed extremely, further includes:
Obtain the current time generated information closed extremely；Extremely the information closed includes abnormal time of origin；
The number of the generated information closed extremely is counted, and the first Outlier factor is determined based on the number；
According to each abnormal time of origin, the abnormal occurrence frequency of the application program is determined, the abnormal occurrence frequency is known
It Wei not the second Outlier factor；
First Outlier factor and second Outlier factor are imported into exception level transformation model, determine the application program
Exception level；The exception level transformation model specifically:
ErrorLevel=10lg (Weight1*ErrorFactor1+Weight2*ErrorFactor2)
Wherein, ErrorLevel is the exception level；ErrorFactor1For first Outlier factor；ErrorFactor2
For second Outlier factor；Weight1、Weight2For predetermined coefficient.
5. abnormality recognition method according to claim 4, which is characterized in that described by the first Outlier factor and described
Second Outlier factor imported into exception level transformation model, after the exception level for determining the destination application, further includes:
If the exception level is more than preset outlier threshold, the program file of the application program is re-downloaded；
The application program is unloaded, and runs the described program file re-downloaded, to reinstall the application program.
6. a kind of anomalous identification equipment of application program, which is characterized in that the anomalous identification equipment of the application program includes depositing
Reservoir, processor and storage in the memory and the computer program that can run on the processor, the processing
Device realizes following steps when executing the computer program:
The program file of application program is obtained, and abnormal indicator identifiers are added in described program file；Wherein, described different
The default value of normal indicator identifiers is the first place value；
The operating status of application program described in real-time monitoring, if after detecting that the application program is switched to from foreground operating status
Platform operating status, then adjusting the abnormal indicator identifiers is the second place value；If detecting the application program from running background
State switches to front stage operation state, then adjusting the abnormal indicator identifiers is the first place value；
Abnormality monitoring thread is created, and adds the program identification of the application program to the eavesdropping target of the abnormality monitoring thread
In list；
If detecting, any program identifies corresponding application program launching in eavesdropping target's list, calls the abnormal prison
Thread is listened to identify the abnormal indicator identifiers of the application program；
If the exception indicator identifiers are the second place value, generate about the letter closed for illustrating the application exception
Breath.
7. anomalous identification equipment according to claim 6, which is characterized in that the fortune of application program described in the real-time monitoring
Row state, comprising:
Start-up operation counter and pausing operation counter are configured for the application program；It is detecting about described using journey
When the enabled instruction of sequence, increase the first numerical value of the start-up operation counter；If detecting about the application program
When pause instruction, increase the second value of the pausing operation counter；
If current time meets preset monitoring running state condition, judge whether first numerical value is greater than second number
Value；
If first numerical value is greater than the second value, identify that the state of the application program is to cut from background operation state
Shift to front stage operation state；
If first numerical value is less than or equal to the second value, identify that the state of the application program is from front stage operation
State switches to background operation state.
8. anomalous identification equipment according to claim 6, which is characterized in that described that abnormal indicator identifiers are added to institute
It states in program file, comprising:
The code data of the launching process of the application program is obtained from described program file；
The registration paragraph of the abnormal indicator identifiers is added in the code data；
The catalogue of the operation host process of the application program is inquired, and addition is indicated for adjusting the exception under the catalogue
The operation subprocess of identifier.
9. according to the described in any item anomalous identification equipment of claim 6-8, which is characterized in that answered in the generation about described
After the information of program closed extremely, the processor also realizes following steps when executing the computer program:
Obtain the current time generated information closed extremely；Extremely the information closed includes abnormal time of origin；
The number of the generated information closed extremely is counted, and the first Outlier factor is determined based on the number；
According to each abnormal time of origin, the abnormal occurrence frequency of the application program is determined, the abnormal occurrence frequency is known
It Wei not the second Outlier factor；
First Outlier factor and second Outlier factor are imported into exception level transformation model, determine the application program
Exception level；The exception level transformation model specifically:
ErrorLevel=10lg (Weight1*ErrorFactor1+Weight2*ErrorFactor2)
Wherein, ErrorLevel is the exception level；ErrorFactor1For first Outlier factor；ErrorFactor2
For second Outlier factor；Weight1、Weight2For predetermined coefficient.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810942567.9A CN109343853B (en) | 2018-08-17 | 2018-08-17 | Abnormality identification method and device for application program |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810942567.9A CN109343853B (en) | 2018-08-17 | 2018-08-17 | Abnormality identification method and device for application program |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109343853A true CN109343853A (en) | 2019-02-15 |
| CN109343853B CN109343853B (en) | 2023-08-04 |
Family
ID=65291721
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810942567.9A Active CN109343853B (en) | 2018-08-17 | 2018-08-17 | Abnormality identification method and device for application program |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109343853B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110007981A (en) * | 2019-02-28 | 2019-07-12 | Oppo广东移动通信有限公司 | Start method, apparatus, electronic equipment and the medium of application program |
| CN110347565A (en) * | 2019-05-24 | 2019-10-18 | 平安科技（深圳）有限公司 | A kind of exception analysis method and device, electronic equipment of application program |
| CN110825396A (en) * | 2019-10-31 | 2020-02-21 | Oppo（重庆）智能科技有限公司 | Exception handling method and related equipment |
| CN112148547A (en) * | 2019-06-26 | 2020-12-29 | 北京百度网讯科技有限公司 | Application starting frequency monitoring method, device, equipment and readable storage medium |
| CN114666390A (en) * | 2022-05-19 | 2022-06-24 | 云账户技术(天津)有限公司 | Page monitoring method and device of application program, electronic equipment and storage medium |
| CN117130809A (en) * | 2023-03-09 | 2023-11-28 | 荣耀终端有限公司 | Method and device for detecting running state of application |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100287414A1 (en) * | 2009-05-06 | 2010-11-11 | Microsoft Corporation | Exception raised notification |
| CN106874753A (en) * | 2016-12-30 | 2017-06-20 | 中国建设银行股份有限公司 | The method and device at the abnormal interface of identification |
| CN107168699A (en) * | 2017-04-28 | 2017-09-15 | 北京五八信息技术有限公司 | application program repairing method and terminal device |
| CN107526638A (en) * | 2017-08-01 | 2017-12-29 | 广东欧珀移动通信有限公司 | Applied program processing method, device, mobile terminal and storage medium |
-
2018
- 2018-08-17 CN CN201810942567.9A patent/CN109343853B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100287414A1 (en) * | 2009-05-06 | 2010-11-11 | Microsoft Corporation | Exception raised notification |
| CN106874753A (en) * | 2016-12-30 | 2017-06-20 | 中国建设银行股份有限公司 | The method and device at the abnormal interface of identification |
| CN107168699A (en) * | 2017-04-28 | 2017-09-15 | 北京五八信息技术有限公司 | application program repairing method and terminal device |
| CN107526638A (en) * | 2017-08-01 | 2017-12-29 | 广东欧珀移动通信有限公司 | Applied program processing method, device, mobile terminal and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 张伟: "网络核心节点异常流量检测与控制技术研究", 《中国博士学位论文全文数据库 (信息科技辑)》, no. 03, pages 139 - 10 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110007981A (en) * | 2019-02-28 | 2019-07-12 | Oppo广东移动通信有限公司 | Start method, apparatus, electronic equipment and the medium of application program |
| CN110347565A (en) * | 2019-05-24 | 2019-10-18 | 平安科技（深圳）有限公司 | A kind of exception analysis method and device, electronic equipment of application program |
| CN110347565B (en) * | 2019-05-24 | 2022-06-03 | 平安科技（深圳）有限公司 | Application program abnormity analysis method and device and electronic equipment |
| CN112148547A (en) * | 2019-06-26 | 2020-12-29 | 北京百度网讯科技有限公司 | Application starting frequency monitoring method, device, equipment and readable storage medium |
| CN112148547B (en) * | 2019-06-26 | 2024-04-02 | 北京百度网讯科技有限公司 | Method, device and equipment for monitoring application starting times and readable storage medium |
| CN110825396A (en) * | 2019-10-31 | 2020-02-21 | Oppo（重庆）智能科技有限公司 | Exception handling method and related equipment |
| CN114666390A (en) * | 2022-05-19 | 2022-06-24 | 云账户技术(天津)有限公司 | Page monitoring method and device of application program, electronic equipment and storage medium |
| CN114666390B (en) * | 2022-05-19 | 2022-08-05 | 云账户技术(天津)有限公司 | Page monitoring method and device of application program, electronic equipment and storage medium |
| CN117130809A (en) * | 2023-03-09 | 2023-11-28 | 荣耀终端有限公司 | Method and device for detecting running state of application |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109343853B (en) | 2023-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109343853A (en) | A kind of abnormality recognition method and equipment of application program | |
| CN110224858B (en) | Log-based alarm method and related device | |
| US20190095266A1 (en) | Detection of Misbehaving Components for Large Scale Distributed Systems | |
| CN110362455B (en) | Data processing method and data processing device | |
| CN108600034B (en) | Service pressure management method, device, equipment, system and storage medium | |
| CN101369933A (en) | Automatic test method and system | |
| CN106330588B (en) | BFD detection method and device | |
| CN113726566B (en) | Service gateway device | |
| CN109462502A (en) | Configuration information saves control method, device and the SDN controller of instruction | |
| CN110178121A (en) | A kind of detection method and its terminal of database | |
| US20180225063A1 (en) | Device, system and method to provide categorized trace information | |
| CN115185777A (en) | Abnormity detection method and device, readable storage medium and electronic equipment | |
| CN115529232A (en) | Control method and device for convergence and distribution equipment and storage medium | |
| CN113704117A (en) | Algorithm testing system, method and device | |
| CN110674149B (en) | Service data processing method and device, computer equipment and storage medium | |
| JP2011523734A (en) | Method and system for monitoring energy consumption in an ICT environment | |
| CN117234859B (en) | Performance event monitoring method, device, equipment and storage medium | |
| US11455293B2 (en) | Counting method, counter and storage medium | |
| CN113791792A (en) | Application calling information acquisition method and device and storage medium | |
| CN111159009B (en) | Pressure testing method and device for log service system | |
| US8917602B2 (en) | System and method for detecting rogue traffic using flow statistics with a list of authorized engines | |
| CN115941441A (en) | System link automation monitoring operation and maintenance method, system, equipment and medium | |
| CN115378841A (en) | Method and device for detecting state of equipment accessing cloud platform, storage medium and terminal | |
| CN105991687B (en) | A kind of service management and device | |
| US20200174868A1 (en) | Detection of event storms |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |