CN110267215B - Data detection method, equipment and storage medium - Google Patents
Data detection method, equipment and storage medium Download PDFInfo
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- CN110267215B CN110267215B CN201910422007.5A CN201910422007A CN110267215B CN 110267215 B CN110267215 B CN 110267215B CN 201910422007 A CN201910422007 A CN 201910422007A CN 110267215 B CN110267215 B CN 110267215B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H—ELECTRICITY
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/12—Messaging; Mailboxes; Announcements
- H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
Abstract
The embodiment of the invention discloses a data detection method, equipment and a storage medium, wherein the method is suitable for application of a test tool, and comprises the following steps: acquiring query object information and an application program identifier from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; and when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of pieces of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information. By adopting the method and the device, the labor cost can be reduced, and the time consumed for positioning the abnormal problems can be reduced.
Description
Technical Field
The present invention relates to the field of electronic technologies, and in particular, to a data detection method, device, and storage medium.
Background
At present, computer technology is more and more widely used, mobile terminals such as mobile phones and computers play an important role, even a bridge for communication, for example, a user can receive a push message sent by a message center through an application program in the mobile terminal, but at the same time, there are situations that the user may not receive the message after the message platform message is pushed, such as a certain credit card repayment short message or a certain important message reminding, when the user cannot receive the message, the user cannot connect with a database to inquire the message due to the database authority problem, the common way is to contact developers to inquire logs to judge whether the message is sent successfully or not and to inquire the reason of sending failure, but for some abnormal problems easy to analyze, the developers do manual detection without difference, the labor cost is greatly increased, and when the developers are busy, the abnormal problem can not be detected in time, so that the time consumption for positioning the abnormal problem is long.
Disclosure of Invention
Embodiments of the present invention provide a data detection method, device, and storage medium, which can reduce labor cost and reduce time consumed for locating an abnormal problem.
An aspect of an embodiment of the present invention provides a data detection method, which may include:
acquiring query object information and an application program identifier from the program script file;
acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result;
and when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of pieces of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
The acquiring a plurality of detection rule information from the query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the plurality of detection rule information to obtain an analysis result includes:
acquiring initial detection rule information from the plurality of detection rule information; the initial detection rule information is the detection rule information with the highest rule priority in the detection rule information which is not used for carrying out the anomaly analysis;
generating an analysis result for the query object information based on the initial detection rule information;
and if the analysis result corresponding to the initial detection rule information is a normal result, taking the next detection rule information as the initial detection rule information according to the rule priority order until the analysis result corresponding to the target detection rule information is an abnormal result or the analysis results corresponding to all the detection rule information are normal results.
Wherein obtaining an analysis result corresponding to the initial detection rule information based on the initial detection rule information includes:
inquiring whether a binding object set associated with the inquiry object information exists in a binding database according to the inquiry object information, and generating a first inquiry result;
if the first query result is that the binding object set does not exist in the binding relation database, outputting an analysis result as an abnormal result;
and if the first query result is that the binding object set exists in the binding relation database, outputting an analysis result as a normal result.
The querying whether a binding object set associated with the query object information exists in a binding database according to the query object information and generating a first query result includes:
acquiring user information corresponding to the query object information from a first database corresponding to the application program identifier;
and querying whether a binding object set corresponding to the user information exists or not from a binding database, and generating a first query result.
Wherein obtaining an analysis result corresponding to the initial detection rule information based on the initial detection rule information includes:
sending test information to address information corresponding to user information in a binding object set through a message pushing platform, acquiring a task identifier corresponding to the test information generated by the message pushing platform, and receiving receipt information corresponding to the test information;
if the receipt information is the sending failure information, outputting an analysis result as an abnormal result;
and if the receipt information is the information of successful transmission, outputting an analysis result as a normal result.
The sending, by the message push platform, test information to address information corresponding to the user information in the bound object set, obtaining a task identifier corresponding to the test information generated by the message push platform, and receiving receipt information corresponding to the test information includes:
acquiring a binding object set associated with the user information, and acquiring address information and an application program identifier corresponding to the user information from the binding object set;
acquiring test information corresponding to the application program identifier from the message pushing platform, and acquiring a task identifier corresponding to the test information generated by the message pushing platform;
and sending the test information to address information corresponding to the user information, and receiving receipt information corresponding to the test information.
Wherein obtaining an analysis result corresponding to the initial detection rule information based on the initial detection rule information includes:
detecting whether test information sent to address information through a message pushing platform exists in an information storage list or not, and outputting a second query result, wherein the information storage list is used for storing historical pushed and sent information;
if the second query result is that the test information does not exist in the information storage list, outputting an analysis result as an abnormal result;
and if the second query result is that the test information exists in the information storage list, outputting an analysis result as a normal result.
Wherein obtaining an analysis result corresponding to the initial detection rule information based on the initial detection rule information includes:
acquiring template information corresponding to the test information, and detecting whether a message sending strategy exists in the template information or not;
if the template information has a message sending strategy, outputting an analysis result as an abnormal result;
and if the message sending strategy does not exist in the template information, outputting the analysis result as a normal result.
Wherein, still include:
and when the analysis results corresponding to all the detection rule information in the plurality of detection rule information are normal results, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis results corresponding to the plurality of detection rule information, and outputting and displaying the error reason information.
An aspect of an embodiment of the present invention provides a data detection apparatus, which may include:
the information identifier acquisition module is used for acquiring query object information and an application program identifier from the program script file;
the anomaly analysis module is used for acquiring a plurality of detection rule information from the query database corresponding to the application program identifier, and sequentially performing anomaly analysis on the query object information according to the detection priorities respectively corresponding to the detection rule information to obtain an analysis result;
and the first abnormal reason display module is used for stopping performing abnormal analysis on the query object information when an analysis result corresponding to the target detection rule information is an abnormal result in the plurality of detection rule information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
Wherein the anomaly analysis module comprises:
a rule information acquisition unit configured to acquire initial detection rule information from the plurality of detection rule information; the initial detection rule information is the detection rule information with the highest rule priority in the detection rule information which is not used for carrying out the anomaly analysis;
an anomaly analysis unit configured to generate an analysis result for the query object information based on the initial detection rule information;
and the rule setting unit is used for taking the next detection rule information as the initial detection rule information according to the rule priority order if the analysis result corresponding to the initial detection rule information is a normal result until the analysis result corresponding to the target detection rule information is an abnormal result or the analysis results corresponding to all the detection rule information are normal results.
Wherein the abnormality analysis unit includes:
the first anomaly analysis subunit is used for inquiring whether a binding object set associated with the query object information exists in a binding database according to the query object information and generating a first inquiry result;
a first output subunit, configured to output an analysis result as an abnormal result if the first query result is that the binding object set does not exist in the binding relationship database; and if the first query result is that the binding object set exists in the binding relation database, outputting an analysis result as a normal result.
Wherein the first anomaly analysis subunit is specifically configured to:
acquiring user information corresponding to the query object information from a first database corresponding to the application program identifier;
and querying whether a binding object set corresponding to the user information exists or not from a binding database, and generating a first query result.
Wherein the abnormality analysis unit includes:
the second anomaly analysis subunit is used for sending test information to address information corresponding to the user information in the bound object set through the message pushing platform, acquiring a task identifier corresponding to the test information generated by the message pushing platform, and receiving receipt information corresponding to the test information;
the second output subunit is used for outputting an analysis result as an abnormal result if the receipt information is the transmission failure information; and if the receipt information is the information of successful transmission, outputting an analysis result as a normal result.
Wherein the second anomaly analysis subunit is specifically configured to:
acquiring a binding object set associated with the user information, and acquiring address information and an application program identifier corresponding to the user information from the binding object set;
acquiring test information corresponding to the application program identifier from the message pushing platform, and acquiring a task identifier corresponding to the test information generated by the message pushing platform;
and sending the test information to address information corresponding to the user information, and receiving receipt information corresponding to the test information.
Wherein the abnormality analysis unit includes:
the third anomaly analysis subunit is used for detecting whether test information sent to the address information by the message pushing platform exists in an information storage list and outputting a second query result, wherein the information storage list is used for storing historical information pushed and sent;
a third output subunit, configured to output an analysis result as an abnormal result if the second query result is that the test information does not exist in the information storage list; and if the second query result is that the test information exists in the information storage list, outputting an analysis result as a normal result.
Wherein the abnormality analysis unit includes:
the fourth anomaly analysis subunit is used for acquiring template information corresponding to the test information and detecting whether a message sending strategy exists in the template information or not;
a fourth output subunit, configured to output, if a message sending policy exists in the template information, an analysis result as an abnormal result; and if the message sending strategy does not exist in the template information, outputting the analysis result as a normal result.
Wherein, still include:
and the second abnormal reason display module is used for stopping abnormal analysis of the query object information when the analysis results corresponding to all the detection rule information in the plurality of detection rule information are normal results, determining error reason information according to the analysis results corresponding to the plurality of detection rule information, and outputting and displaying the error reason information.
An aspect of the embodiments of the present invention provides a computer storage medium, which stores a plurality of instructions adapted to be loaded by a processor and execute the above method steps.
In one aspect, an embodiment of the present invention provides a data detection device, including a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stopping abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, outputting and displaying the error reason information, adopting the plurality of detection rule information, sequentially performing abnormal analysis on the query object information according to the detection priority, and accurately positioning the problem that the mobile terminal cannot receive the push message.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a data detection method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another data detection method provided by the embodiment of the invention;
FIG. 3 is a schematic diagram illustrating an example of a data detection method according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a data detection apparatus according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of another data detection device provided in an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an anomaly analysis module according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an anomaly analysis unit according to an embodiment of the present invention;
FIG. 8 is a schematic structural diagram of another anomaly analysis unit provided in the embodiment of the present invention;
FIG. 9 is a schematic structural diagram of another anomaly analysis unit provided in the embodiment of the present invention;
FIG. 10 is a schematic structural diagram of another anomaly analysis unit provided in the embodiment of the present invention;
fig. 11 is a schematic structural diagram of another data detection apparatus provided in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The data detection method provided by the embodiment of the invention can be applied to problem location of the mobile terminal which cannot receive the push information, and specifically, the data detection equipment acquires query object information and an application program identifier from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stopping abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, outputting and displaying the error reason information, adopting the plurality of detection rule information, sequentially performing abnormal analysis on the query object information according to the detection priority, and accurately positioning the problem that the mobile terminal cannot receive the push message.
The data detection device related to the embodiment of the invention may include: the tablet computer, the Personal Computer (PC), the notebook computer, the palmtop computer, the terminal server, and the like are provided with terminal devices for performing abnormality analysis on query target information based on detection rule information.
Referring to fig. 1, a flow chart of a data detection method according to an embodiment of the present invention is schematically shown. As shown in fig. 1, the method of the embodiment of the present invention may include the following steps S101 to S104.
S101, acquiring query object information and an application program identifier from the program script file;
specifically, the data detection device obtains the query object information and the application program identification from the program script file, it is understood that the query object information is information associated with user information of the user in the application program, and may specifically be a mobile phone number of the user, the application program identifier is a unique tag corresponding to the application program, may be the name of the application, an application icon, or a unique identification code of the application, the program script file is a computer program that can be run on an information processing device, the program script file can include query object information and an application program identification therein, the program script file also can comprise a storage address corresponding to the query object information and the application program identifier, and the data detection equipment acquires the query object information and the application program identifier from the storage address.
S102, acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result;
specifically, the data detection device obtains a plurality of detection rule information from the query database corresponding to the application program identification, according to the detection priority levels respectively corresponding to the plurality of detection rule information, the abnormal analysis is sequentially carried out on the query object information to obtain an analysis result, it is to be understood that the query database is used for storing detection rule information, at least one detection rule information in the query database, the detection rule information is a detection condition for carrying out anomaly analysis on the query object information, the detection priority is the sequence of carrying out anomaly analysis on the query object information according to the detection rule information, the data detection equipment carries out anomaly analysis on the query object information in sequence from the detection rule information with the highest detection priority to obtain an analysis result, and the analysis result comprises an anomaly result and a normal result.
S103, when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
Specifically, the data detection device stops performing the abnormal analysis on the query object information when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of detection rule information, determines error cause information according to the analysis result corresponding to the target detection rule information, and outputs and displays the error cause information, it is understood that the target detection rule information is any one of the plurality of detection rule information, and when the analysis result corresponding to the target detection rule information is an abnormal result, stops performing the abnormal analysis on the query object information, determines error cause information according to the abnormal result, and outputs and displays the error cause information, the error cause information may be a specific error cause corresponding to the abnormal result or an error identifier corresponding to the abnormal result, and acquiring a specific error reason according to the error identifier.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stopping abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, outputting and displaying the error reason information, adopting the plurality of detection rule information, sequentially performing abnormal analysis on the query object information, and accurately positioning the problem that the mobile terminal cannot receive the push message.
Referring to fig. 2, a flow chart of a data detection method according to an embodiment of the invention is shown. As shown in fig. 2, the method of the embodiment of the present invention may include the following steps S201 to S206.
S201, obtaining query object information and an application program identifier from the program script file;
s202, acquiring initial detection rule information from the plurality of detection rule information; the initial detection rule information is the detection rule information with the highest rule priority in the detection rule information which is not used for carrying out the anomaly analysis;
specifically, the data detection device obtains initial detection rule information from the plurality of detection rule information; the initial detection rule information is the detection rule information with the highest rule priority in the detection rule information which is not used for carrying out the anomaly analysis.
S203, generating an analysis result aiming at the query object information based on the initial detection rule information;
specifically, the data detection device generates an analysis result for the query object information based on the initial detection rule information, and it can be understood that the data detection device performs an anomaly analysis on the query object information based on the initial detection rule information to obtain the analysis result.
When the initial detection rule information is a binding object set, the data detection equipment inquires whether the binding object set associated with the inquired object information exists from a binding database according to the inquired object information and generates a first inquiry result;
it can be understood that, a binding object set is stored in the binding database, the binding object set includes user information, address information corresponding to the user information, an application program identifier corresponding to the user information, and a binding relationship between the user information and the address information, the binding relationship is an association relationship, the query object information and the user information are in a one-to-one correspondence relationship, and the data detection device queries whether the binding object set associated with the query object information exists in the binding database according to the query object information, and generates a first query result;
specifically, the data detection device obtains user information corresponding to the query object information from a first database corresponding to the application program identifier; inquiring whether a binding object set corresponding to the user information exists in a binding database and generating a first inquiry result, wherein the first database stores inquiry object information and user information corresponding to the inquiry object information, the data detection equipment acquires the user information corresponding to the inquiry object information from the first database, inquires whether the binding object set corresponding to the user information exists in the binding database and generates the first inquiry result;
if the first query result is that the binding object set does not exist in the binding relation database, outputting an analysis result as an abnormal result; and if the first query result is that the binding object set exists in the binding relation database, outputting an analysis result as a normal result.
When the initial detection rule information is test information, the data detection equipment sends the test information to address information corresponding to user information in a binding object set through a message pushing platform, obtains a task identifier corresponding to the test information generated by the message pushing platform, and receives receipt information corresponding to the test information;
specifically, the data detection device acquires a binding object set associated with the user information, and acquires address information and an application program identifier corresponding to the user information from the binding object set; acquiring test information corresponding to the application program identifier from the message pushing platform, and acquiring a task identifier corresponding to the test information generated by the message pushing platform; sending the test information to address information corresponding to the user information, and receiving receipt information corresponding to the test information;
it can be understood that the data detection device obtains a binding object set associated with the user information, where the binding object set includes the user information and address information corresponding to the user information, the application identifier corresponding to the user information, and the address information is an address of a virtual terminal, and it can be specifically understood that the information transmission address is a virtual machine address, the data detection device obtains the address information and the application identifier corresponding to the user information from the binding object set, obtains test information corresponding to the application identifier from the message push platform, where the test information is to-be-sent information sent to the address information, where the test information may be preset information, a task identifier corresponding to the test information generated by the message push platform, and the data detection device sends the test information to the address information corresponding to the user information, receiving receipt information corresponding to the test message;
if the receipt information is the sending failure information, outputting an analysis result as an abnormal result; and if the receipt information is the information of successful transmission, outputting an analysis result as a normal result.
When the initial detection rule information is an information storage list, the data detection equipment detects whether test information sent to the address information through the message push platform exists in the information storage list or not, and outputs a second query result, wherein the information storage list is used for storing history information pushed and sent;
specifically, the history information in the information storage list carries user information, address information and task identifiers corresponding to the history information, and the data detection device detects whether the history information in which the user information, the address information and the task identifiers are the same as the test information exists in the information storage list, and outputs a second query result.
If the second query result is that the test information does not exist in the information storage list, outputting an analysis result as an abnormal result; and if the second query result is that the test information exists in the information storage list, outputting an analysis result as a normal result.
When the initial detection rule information is template information, the data detection equipment acquires the template information corresponding to the test information and detects whether a message sending strategy exists in the template information or not;
specifically, the data detection device obtains template information corresponding to the test information, and detects whether a message sending policy exists in the template information, where the message sending policy is a sending condition limitation carried by the template information, for example, the message sending policy may be "delayed sending", that is, after receiving a message sending request, the message is sent after delaying a preset time, and the message sending policy may be sending for a fixed software version.
If the template information has a message sending strategy, outputting an analysis result as an abnormal result; and if the message sending strategy does not exist in the template information, outputting the analysis result as a normal result.
S204, if the analysis result corresponding to the initial detection rule information is a normal result, taking the next detection rule information as the initial detection rule information according to the rule priority order until the analysis result corresponding to the target detection rule information is an abnormal result or the analysis results corresponding to all the detection rule information are normal results;
specifically, if the analysis result corresponding to the initial detection rule information is a normal result, the data detection device uses the next detection rule information as the initial detection rule information according to the rule priority order until the analysis result corresponding to the target detection rule information is an abnormal result or the analysis results corresponding to all the detection rule information are normal results, it can be understood that, if the analysis result corresponding to the initial detection rule information is a normal result, the data detection device obtains the detection rule information with the highest rule priority from the plurality of detection rule information not including the initial detection rule information as the initial detection rule information, and generates the analysis result for the query object information based on the initial detection rule information until the analysis result corresponding to the target detection rule information is an abnormal result or the analysis results corresponding to all the detection rule information are normal results.
S205, when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information;
and S206, when the analysis results corresponding to all the detection rule information in the detection rule information are normal results, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis results corresponding to the detection rule information, and outputting and displaying the error reason information.
Specifically, the data detection device stops performing the anomaly analysis on the query object information when the analysis results corresponding to all the detection rule information in the plurality of detection rule information are all normal results, determines the error reason information according to the analysis results corresponding to the plurality of detection rule information, and outputs and displays the error reason information, it is understood that the data detection device sequentially performs the anomaly analysis on the query object information according to the detection priorities corresponding to the plurality of detection rule information, and stops performing the anomaly analysis on the query object information when the analysis results are all normal results, determines the error reason information according to the analysis results corresponding to the plurality of detection rule information, and outputs and displays the error reason information, where the error reason information may be a specific error reason corresponding to the abnormal results, or the error identification corresponding to the abnormal result, and then the specific error reason is obtained according to the error identification.
It should be noted that, in this embodiment, the process of sequentially performing the anomaly analysis on the query object information according to the detection priorities respectively corresponding to the plurality of detection rule information to obtain the analysis result is only enumerated as the case of performing the anomaly analysis on the query object information according to one detection rule information, and in an actual case, the case of performing the anomaly analysis on the query object information according to the plurality of detection rule information is the same as the method in the above embodiment, and is not described here again.
Steps S201 and S205 in the embodiment of the present invention refer to specific descriptions of steps S101 and S103 in the embodiment shown in fig. 1, and are not described herein again.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when the analysis result corresponding to the target detection rule information is an abnormal result, the abnormal analysis of the query object information is stopped, the error reason information is determined according to the analysis result corresponding to the target detection rule information, the error reason information is output and displayed, the multiple detection rule information is adopted, the abnormal analysis of the query object information can be carried out according to the priority sequence of the detection rule information in the multiple detection rule information, the problem that the push message cannot be received by the mobile terminal is accurately positioned, the problem that the abnormal problem cannot be timely detected when developers are busy is solved, the manual detection of developers which the abnormal problems easy to analyze are indiscriminately avoided, the labor cost is reduced, and the time consumed for positioning the abnormal problems is reduced.
A data detection method provided by an embodiment of the present invention will be specifically described below.
The specific implementation scenario is that the mobile terminal cannot receive the pushed information for problem location, as shown in fig. 3, query object information and an application program identifier are obtained from the program script file, the query object information is a mobile phone number of a user, the application program identifier corresponds to an application program that cannot receive the pushed information in the mobile terminal, a plurality of detection rule information are obtained from a query database corresponding to the application program identifier, and according to detection priorities corresponding to the plurality of detection rule information, the query object information is subjected to anomaly analysis in sequence to obtain an analysis result, the plurality of detection rule information are binding object sets, test information, information storage lists and template information, wherein the detection priorities corresponding to the plurality of detection rule information are from high to low in sequence, the binding object sets, the test information, the information storage lists, And (4) template information.
The data detection equipment inquires whether a binding object set associated with the inquired object information exists in a binding database according to the inquired object information and generates a first inquiry result, if the first inquiry result is that the binding object set does not exist in a binding relation database, the data detection equipment outputs an analysis result as an abnormal result, stops performing abnormal analysis on the inquired object information, determines error reason information according to the analysis result and outputs and displays the error reason information;
if the first query result is that the binding object set exists in the binding relation database, outputting an analysis result as a normal result, sending test information to address information corresponding to the user information in the binding object set by the data detection equipment through a message pushing platform, and receiving receipt information corresponding to the test information; if the receipt information is the sending failure information, outputting an analysis result as an abnormal result, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result, and outputting and displaying the error reason information;
if the receipt information is successful sending information, outputting an analysis result as a normal result, detecting whether test information sent to address information through a message pushing platform exists in an information storage list by data detection equipment, and outputting a second query result, if the second query result is that the test information does not exist in the information storage list, outputting the analysis result as an abnormal result, stopping performing abnormal analysis on query object information, determining error reason information according to the analysis result, and outputting and displaying the error reason information;
if the second query result is that the test information exists in the information storage list, outputting an analysis result as a normal result, acquiring template information corresponding to the test information by using data detection equipment, detecting whether a message sending strategy exists in the template information, if the message sending strategy exists in the template information, outputting the analysis result as an abnormal result, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result, and outputting and displaying the error reason information;
and if the message sending strategy does not exist in the template information, outputting an analysis result as a normal result, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result, and outputting and displaying the error reason information.
Fig. 4 is a schematic structural diagram of a data detection apparatus according to an embodiment of the present invention. As shown in fig. 4, the data detection apparatus 1 according to an embodiment of the present invention may include: the system comprises an information identification acquisition module 11, an abnormality analysis module 12 and a first abnormality reason display module 13.
An information identifier obtaining module 11, configured to obtain query object information and an application identifier from the program script file;
the anomaly analysis module 12 is configured to obtain multiple pieces of detection rule information from the query database corresponding to the application program identifier, and perform anomaly analysis on query object information in sequence according to detection priorities respectively corresponding to the multiple pieces of detection rule information to obtain an analysis result;
and a first abnormal cause display module 13, configured to, when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stop performing abnormal analysis on the query object information, determine error cause information according to the analysis result corresponding to the target detection rule information, and output and display the error cause information.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stopping abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, outputting and displaying the error reason information, adopting the plurality of detection rule information, sequentially performing abnormal analysis on the query object information, and accurately positioning the problem that the mobile terminal cannot receive the push message.
Fig. 5 is a schematic structural diagram of a data detection apparatus according to an embodiment of the present invention. As shown in fig. 5, the data detection apparatus 1 according to an embodiment of the present invention may include: the system comprises an information identification acquisition module 11, an abnormality analysis module 12, a first abnormality reason display module 13 and a second abnormality reason display module 14.
An information identifier obtaining module 11, configured to obtain query object information and an application identifier from the program script file;
the anomaly analysis module 12 is configured to obtain multiple pieces of detection rule information from the query database corresponding to the application program identifier, and perform anomaly analysis on query object information in sequence according to detection priorities respectively corresponding to the multiple pieces of detection rule information to obtain an analysis result;
referring to fig. 6, a schematic structural diagram of the anomaly analysis module 12 is provided in the embodiment of the present invention. As shown in fig. 6, the abnormality analysis module 12 according to the embodiment of the present invention may include: a rule information acquisition unit 121, an abnormality analysis unit 122, and a rule setting unit 123.
A rule information obtaining unit 121 configured to obtain initial detection rule information from the plurality of detection rule information; the initial detection rule information is the detection rule information with the highest rule priority in the detection rule information which is not used for carrying out the anomaly analysis;
an anomaly analysis unit 122 configured to generate an analysis result for the query object information based on the initial detection rule information;
referring to fig. 7, a schematic structural diagram of an abnormality analysis unit 122 is provided for an embodiment of the present invention. As shown in fig. 7, the abnormality analysis unit 122 according to an embodiment of the present invention may include: a first anomaly analysis subunit 1221, a first output subunit 1222.
When the initial detection rule information is a binding object set, a first anomaly analysis subunit 1221, configured to query, according to the query object information, from a binding database, whether a binding object set associated with the query object information exists, and generate a first query result;
a first output subunit 1222, configured to output, if the first query result is that the set of binding objects does not exist in the binding relationship database, an analysis result as an abnormal result; and if the first query result is that the binding object set exists in the binding relation database, outputting an analysis result as a normal result.
Referring to fig. 8, a schematic structural diagram of an abnormality analysis unit 122 is provided in the embodiment of the present invention. As shown in fig. 8, the abnormality analyzing unit 122 according to the embodiment of the present invention may include: a second abnormality analysis subunit 1223, a second output subunit 1224.
When the initial detection rule information is test information, the second anomaly analysis subunit 1223 is configured to send the test information to address information corresponding to user information in a bound object set through a message pushing platform, obtain a task identifier corresponding to the test information generated by the message pushing platform, and receive response piece information corresponding to the test information;
a second output subunit 1224, configured to output, if the receipt information is transmission failure information, an analysis result as an abnormal result; and if the receipt information is the information of successful transmission, outputting an analysis result as a normal result.
Referring to fig. 9, a schematic structural diagram of an abnormality analysis unit 122 is provided for an embodiment of the present invention. As shown in fig. 9, the abnormality analysis unit 122 according to an embodiment of the present invention may include: a third anomaly analysis subunit 1225, and a third output subunit 1226.
When the initial detection rule information is an information storage list, a third anomaly analysis subunit 1225 is configured to detect whether there is test information sent to address information by a message push platform in the information storage list, and output a second query result, where the information storage list is used to store history information of push-to-send;
a third output subunit 1226, configured to output, if the second query result is that the test information does not exist in the information storage list, an analysis result as an abnormal result; and if the second query result is that the test information exists in the information storage list, outputting an analysis result as a normal result.
Referring to fig. 10, a schematic structural diagram of an abnormality analysis unit 122 is provided for an embodiment of the present invention. As shown in fig. 10, the abnormality analysis unit 122 according to an embodiment of the present invention may include: a fourth anomaly analysis subunit 1227, and a fourth output subunit 1228.
A fourth anomaly analysis subunit 1227, configured to, when the initial detection rule information is template information, obtain, by the data detection device, template information corresponding to the test information, and detect whether a message sending policy exists in the template information;
a fourth output subunit 1228, configured to output, if a message sending policy exists in the template information, an analysis result as an abnormal result; and if the message sending strategy does not exist in the template information, outputting the analysis result as a normal result.
A rule setting unit 123, configured to, if an analysis result corresponding to the initial detection rule information is a normal result, take the next detection rule information as the initial detection rule information according to a rule priority order until there is an abnormal result or all analysis results corresponding to the target detection rule information are normal results;
a first abnormal cause display module 13, configured to, when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stop performing abnormal analysis on the query object information, determine error cause information according to the analysis result corresponding to the target detection rule information, and output and display the error cause information;
and a second abnormal cause display module 14, configured to stop performing abnormal analysis on the query object information when the analysis results corresponding to all the detection rule information in the multiple pieces of detection rule information are normal results, determine error cause information according to the analysis results corresponding to the multiple pieces of detection rule information, and output and display the error cause information.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when the analysis result corresponding to the target detection rule information is an abnormal result, the abnormal analysis of the query object information is stopped, the error reason information is determined according to the analysis result corresponding to the target detection rule information, the error reason information is output and displayed, the multiple detection rule information is adopted, the abnormal analysis of the query object information can be carried out according to the priority sequence of the detection rule information in the multiple detection rule information, the problem that the push message cannot be received by the mobile terminal is accurately positioned, the problem that the abnormal problem cannot be timely detected when developers are busy is solved, the manual detection of developers which the abnormal problems easy to analyze are indiscriminately avoided, the labor cost is reduced, and the time consumed for positioning the abnormal problems is reduced.
An embodiment of the present invention further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, where the instructions are suitable for being loaded by a processor and executing the method steps in the embodiments shown in fig. 1 to fig. 3, and a specific execution process may refer to specific descriptions of the embodiments shown in fig. 1 to fig. 3, which are not described herein again.
Fig. 11 is a schematic structural diagram of data detection according to an embodiment of the present invention. As shown in fig. 11, the data detection 1000 may include: at least one processor 1001, such as a CPU, at least one network interface 1004, a user interface 1003, memory 1005, at least one communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), and the optional user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 1005 may alternatively be at least one memory device located remotely from the processor 1001. As shown in fig. 11, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a data detection application program.
In the terminal 1000 shown in fig. 11, the user interface 1003 is mainly used as an interface for providing input for a user, and acquiring data input by the user; and the processor 1001 may be configured to invoke the data detection application stored in the memory 1005 and specifically perform the following operations:
acquiring query object information and an application program identifier from the program script file;
acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result;
and when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of pieces of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
In the embodiment of the invention, query object information and an application program identifier are obtained from the program script file; acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information to obtain an analysis result; when an analysis result corresponding to target detection rule information is an abnormal result in the plurality of detection rule information, stopping abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, outputting and displaying the error reason information, adopting the plurality of detection rule information, sequentially performing abnormal analysis on the query object information, and accurately positioning the problem that the mobile terminal cannot receive the push message.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (9)
1. A method of data detection, comprising:
acquiring query object information and an application program identifier from a program script file;
acquiring a plurality of detection rule information from a query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the detection rule information respectively to obtain an analysis result, wherein the analysis result comprises the following steps: inquiring whether a binding object set associated with the query object information exists in a binding database according to the query object information, if so, sending test information to address information corresponding to user information in the binding object set through a message pushing platform, acquiring a task identifier corresponding to the test information generated by the message pushing platform, and receiving receipt information corresponding to the test information; if the receipt information is the information which is successfully sent, detecting whether test information sent to the address information through the message pushing platform exists in the information storage list or not; if the test information exists in the information storage list, acquiring template information corresponding to the test information, and detecting whether a message sending strategy exists in the template information, wherein the message sending strategy is a sending condition limit carried by the template information, and the sending condition limit comprises delayed sending; if the message sending strategy exists in the template information, outputting an analysis result as an abnormal result;
and when the analysis result corresponding to the target detection rule information is an abnormal result in the plurality of pieces of detection rule information, stopping performing abnormal analysis on the query object information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
2. The method according to claim 1, wherein the obtaining a plurality of detection rule information from the query database corresponding to the application identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the plurality of detection rule information, to obtain an analysis result, further comprises:
inquiring whether a binding object set associated with the inquiry object information exists in a binding database according to the inquiry object information, and generating a first inquiry result;
and if the first query result is that the binding object set does not exist in the binding relation database, outputting an analysis result as an abnormal result.
3. The method of claim 2, wherein querying a binding database for the presence of a set of binding objects associated with the query object information based on the query object information and generating a first query result comprises:
acquiring user information corresponding to the query object information from a first database corresponding to the application program identifier;
and inquiring whether a binding object set corresponding to the user information exists from a binding database, and generating a first inquiry result.
4. The method according to claim 1, wherein the obtaining a plurality of detection rule information from the query database corresponding to the application identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the plurality of detection rule information, respectively, to obtain an analysis result, further comprises:
and if the receipt information is the sending failure information, outputting an analysis result as an abnormal result.
5. The method according to claim 1 or 4, wherein the sending, by the message push platform, test information to address information corresponding to the user information in the bound object set, obtaining a task identifier corresponding to the test information generated by the message push platform, and receiving receipt information corresponding to the test information, comprises:
acquiring a binding object set associated with the user information, and acquiring address information and an application program identifier corresponding to the user information from the binding object set;
acquiring test information corresponding to the application program identifier from the message pushing platform, and acquiring a task identifier corresponding to the test information generated by the message pushing platform;
and sending the test information to address information corresponding to the user information, and receiving receipt information corresponding to the test information.
6. The method according to claim 1, wherein the obtaining a plurality of detection rule information from the query database corresponding to the application identifier, and sequentially performing anomaly analysis on query object information according to detection priorities corresponding to the plurality of detection rule information, to obtain an analysis result, further comprises:
detecting whether test information sent to address information through a message pushing platform exists in an information storage list or not, and outputting a second query result, wherein the information storage list is used for storing historical pushed and sent information;
and if the second query result is that the test information does not exist in the information storage list, outputting an analysis result as an abnormal result.
7. A data detection apparatus, comprising:
the information identifier acquisition module is used for acquiring query object information and an application program identifier from the program script file;
the anomaly analysis module is used for acquiring a plurality of detection rule information from the query database corresponding to the application program identifier, and sequentially performing anomaly analysis on query object information according to detection priorities respectively corresponding to the detection rule information to obtain an analysis result, and comprises: inquiring whether a binding object set associated with the query object information exists in a binding database according to the query object information, if the binding object set exists in the binding relation database, sending test information to address information corresponding to user information in the binding object set through a message pushing platform, acquiring a task identifier corresponding to the test information generated by the message pushing platform, and receiving receipt information corresponding to the test information; if the receipt information is the information which is successfully sent, detecting whether test information sent to the address information through the message pushing platform exists in the information storage list or not; if the test information exists in the information storage list, acquiring template information corresponding to the test information, and detecting whether a message sending strategy exists in the template information, wherein the message sending strategy is a sending condition limit carried by the template information, and the sending condition limit comprises delayed sending; if the message sending strategy exists in the template information, outputting an analysis result as an abnormal result;
and the first abnormal reason display module is used for stopping performing abnormal analysis on the query object information when an analysis result corresponding to the target detection rule information is an abnormal result in the plurality of detection rule information, determining error reason information according to the analysis result corresponding to the target detection rule information, and outputting and displaying the error reason information.
8. A computer-readable storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to carry out the method steps according to any one of claims 1 to 6.
9. A data detection apparatus, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1-6.
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