CN116775358A - Data analysis method, device, electronic equipment and storage medium - Google Patents

Abstract

The disclosure relates to a data analysis method, a data analysis device, an electronic device and a storage medium. The method comprises the following steps: responding to the data analysis request, and acquiring configuration information carried by the data analysis request; the configuration information includes: lane information and interface information; acquiring an abnormal data index matched with the data analysis request; based on lane information, interface information and abnormal data index, acquiring corresponding target abnormal construction data from a pre-constructed abnormal construction database; the abnormal structure database contains abnormal structure data of various abnormal processing types; generating abnormal data based on the target abnormal construction data, inputting the abnormal data into a data interface characterized by interface information, and thus obtaining an abnormal test result corresponding to the abnormal data. Since the abnormal structure database contains the structure data of a plurality of abnormality types, compared with the case where abnormality is found by the detection tool, abnormality problems of a plurality of abnormality types can be detected, thereby improving the accuracy of abnormality analysis.

Description

Data analysis method, device, electronic equipment and storage medium

Technical Field

The disclosure relates to the field of computer technology, and in particular, to a data analysis method, a data analysis device, electronic equipment and a storage medium.

Background

With the development of computer technology, in order to reduce the occurrence of breakdown of a mobile terminal and ensure the operation stability of the mobile terminal, a technology for detecting an abnormality by performing data analysis on the mobile terminal has appeared. For example, by detecting tools, abnormal problems such as null pointer abnormality and code non-standardization which may exist in the mobile terminal can be identified, so that the running stability of the mobile terminal is improved.

However, the current technology of performing the anomaly analysis on the mobile terminal by using the detection tool can only be used for detecting the anomaly problems of a specific type, but the anomaly problems of other types except the specific type cannot be detected by using the detection tool, so that the conventional anomaly analysis method of the mobile terminal has low accuracy of anomaly analysis.

Disclosure of Invention

The disclosure provides a data analysis method, a data analysis device, electronic equipment and a storage medium, so as to at least solve the problem of low accuracy of mobile end anomaly analysis in the related art. The technical scheme of the present disclosure is as follows:

according to a first aspect of embodiments of the present disclosure, there is provided a data analysis method, including:

responding to a data analysis request, and acquiring configuration information carried by the data analysis request; the configuration information includes: lane information and interface information;

Acquiring an abnormal data index matched with the data analysis request;

acquiring corresponding target abnormal construction data from a pre-constructed abnormal construction database based on the lane information, interface information and the abnormal data index; the abnormal structure database comprises abnormal structure data of various abnormal processing types;

generating abnormal data based on the target abnormal construction data, and inputting the abnormal data into a data interface represented by the interface information, thereby obtaining an abnormal test result corresponding to the abnormal data.

In an exemplary embodiment, before the obtaining the corresponding target abnormal structure data from the pre-built abnormal structure database, the method further includes: displaying the front end interface of the abnormal structure platform; obtaining abnormal construction data to be constructed, which are input in the displayed front-end interface, aiming at a plurality of abnormal processing types; constructing the abnormal construction data according to an abnormal data construction rule preset by the abnormal construction platform and the abnormal data configuration information, and storing the abnormal construction data into the abnormal construction database.

In an exemplary embodiment, the abnormal data configuration information includes: raw data corresponding to the exception construction data and processing type information for representing exception processing types; the original data is non-abnormal data; the constructing the abnormal construction data according to the preset abnormal data construction rule and the abnormal data configuration information comprises the following steps: acquiring a target abnormal data construction rule matched with the processing type information from the abnormal data construction rule; and carrying out exception processing on the original data according to the target exception data construction rule to obtain the exception construction data corresponding to the original data.

In an exemplary embodiment, the raw data comprises a plurality of node data; the abnormal data configuration information further includes: node identification information; performing exception processing on the original data according to the target exception data construction rule to construct the exception construction data, including: acquiring target node data corresponding to the node identification information from a plurality of node data of the original data; and carrying out exception processing on the target node data according to the target exception data construction rule to construct the exception construction data.

In an exemplary embodiment, the processing type information includes mutation type information, discard type information, and cut-off type information; performing exception processing on the target node data according to the target exception data construction rule to construct the exception construction data, wherein the exception construction data comprises at least one of the following: performing mutation processing on the target node data according to the target abnormal data construction rule to construct the abnormal construction data; discarding the target node data according to the target abnormal data construction rule to construct the abnormal construction data; and according to the target abnormal data construction rule, cutting off the target node data to construct the abnormal construction data.

In an exemplary embodiment, the abnormal data configuration information further includes: interface information corresponding to the abnormal construction data; the storing the abnormal construction data into the abnormal construction database includes: obtaining lane information matched with a construction request corresponding to the abnormal construction data; binding the abnormal construction data with interface information corresponding to the abnormal construction data and lane information matched with the construction request, and storing the abnormal construction data into the abnormal construction database.

In an exemplary embodiment, after the storing the abnormal configuration data in the abnormal configuration database, the method further includes: and displaying the configuration information of the abnormal data corresponding to the abnormal construction data of each abnormal processing type through the front-end interface.

In an exemplary embodiment, the front-end interface includes a preset control for determining a data index; the obtaining the abnormal data index matched with the data analysis request comprises the following steps: acquiring user operation information based on the preset control, and determining a data index matched with the data analysis request according to the user operation information; after the data index matching the data analysis request is determined according to the user operation information, the method further comprises: and displaying the abnormal data based on the data index which is determined to be matched with the data analysis request according to the user operation information through the front-end interface.

In an exemplary embodiment, the obtaining the abnormal data index matched with the data analysis request includes: acquiring the input times of the current abnormal data of the data interface; and obtaining the abnormal data index according to the input times.

According to a second aspect of embodiments of the present disclosure, there is provided a data analysis apparatus comprising:

the test configuration acquisition unit is configured to respond to the data analysis request and acquire configuration information carried by the data analysis request; the configuration information includes: lane information and interface information;

a data index acquisition unit configured to perform acquisition of an abnormal data index matched with the data analysis request;

a construction data acquisition unit configured to perform acquisition of corresponding target abnormal construction data from an abnormal construction database constructed in advance based on the lane information, interface information, and the abnormal data index; the abnormal structure database comprises abnormal structure data of various abnormal processing types;

and the abnormal data testing unit is configured to execute the generation of abnormal data based on the target abnormal construction data, input the abnormal data into the data interface characterized by the interface information, and obtain an abnormal test result corresponding to the abnormal data.

In an exemplary embodiment, the data analysis device further includes: an abnormal data construction unit configured to execute a front end interface showing an abnormal construction platform; obtaining abnormal construction data to be constructed, which are input in the displayed front-end interface, aiming at a plurality of abnormal processing types; constructing the abnormal construction data according to an abnormal data construction rule preset by the abnormal construction platform and the abnormal data configuration information, and storing the abnormal construction data into the abnormal construction database.

In an exemplary embodiment, the abnormal data configuration information includes: raw data corresponding to the exception construction data and processing type information for representing exception processing types; the original data is non-abnormal data; an abnormal data construction unit further configured to execute, from the abnormal data construction rules, a target abnormal data construction rule that matches the processing type information; and carrying out exception processing on the original data according to the target exception data construction rule to obtain the exception construction data corresponding to the original data.

In an exemplary embodiment, the raw data comprises a plurality of node data; the abnormal data configuration information further includes: node identification information; the abnormal data construction unit is further configured to acquire target node data corresponding to the node identification information from the plurality of node data of the original data; and carrying out exception processing on the target node data according to the target exception data construction rule to construct the exception construction data.

In an exemplary embodiment, the processing type information includes mutation type information, discard type information, and cut-off type information; an abnormal data construction unit configured to perform mutation processing on the target node data according to the target abnormal data construction rule, and construct the abnormal construction data; discarding the target node data according to the target abnormal data construction rule to construct the abnormal construction data; and according to the target abnormal data construction rule, cutting off the target node data to construct the abnormal construction data.

In an exemplary embodiment, the abnormal data configuration information further includes: interface information corresponding to the abnormal construction data; an abnormal data construction unit further configured to perform acquisition of lane information matching a construction request corresponding to the abnormal construction data; binding the abnormal construction data with interface information corresponding to the abnormal construction data and lane information matched with the construction request, and storing the abnormal construction data into the abnormal construction database.

In an exemplary embodiment, the exception data construction unit is further configured to execute exception data configuration information respectively corresponding to the exception construction data showing each exception processing type through the front end interface.

In an exemplary embodiment, the front-end interface includes a preset control for determining a data index; the data index acquisition unit is further configured to acquire user operation information based on the preset control, and determine an abnormal data index matched with the data analysis request according to the user operation information; the data analysis device further includes: and the abnormal data display unit is configured to display the abnormal data through the front-end interface based on the abnormal data index which is determined to be matched with the data analysis request according to the user operation information.

In an exemplary embodiment, the data index obtaining unit is further configured to perform obtaining the number of inputs of the current input abnormal data of the data interface; and obtaining the abnormal data index according to the input times.

According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, comprising: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the data analysis method according to any one of the embodiments of the first aspect.

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the data analysis method according to any one of the embodiments of the first aspect.

According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising instructions therein, which when executed by a processor of an electronic device, enable the electronic device to perform the data analysis method according to any one of the embodiments of the first aspect.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

the method comprises the steps of responding to a data analysis request to obtain configuration information carried by the data analysis request; the configuration information includes: lane information and interface information; acquiring an abnormal data index matched with the data analysis request; based on lane information, interface information and abnormal data index, acquiring corresponding target abnormal construction data from a pre-constructed abnormal construction database; the abnormal structure database contains abnormal structure data of various abnormal processing types; generating abnormal data based on the target abnormal construction data, inputting the abnormal data into a data interface characterized by interface information, and thus obtaining an abnormal test result corresponding to the abnormal data. According to the method and the device, when the abnormal test is executed, corresponding lane information and interface information can be configured, after the abnormal data index is obtained, target abnormal construction data can be obtained from an abnormal construction database which is built in advance and contains abnormal construction data of various abnormal processing types, after the target abnormal construction data is utilized to generate the abnormal data, the abnormal data are input into a data interface represented by the interface information, and accordingly, a corresponding abnormal test result is obtained.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.

FIG. 1 is a flow chart illustrating a method of data analysis according to an exemplary embodiment.

FIG. 2 is a flowchart illustrating the construction of an exception construction database, according to an example embodiment.

FIG. 3 is a flow chart illustrating constructing exception configuration data according to an exemplary embodiment.

Fig. 4 is a technical architecture diagram illustrating an anomaly analysis method according to an exemplary embodiment.

FIG. 5 is a flow chart illustrating constructing exception configuration data according to an exemplary embodiment.

FIG. 6 is a flowchart illustrating anomaly testing of a mobile terminal according to an example embodiment.

Fig. 7 is a block diagram illustrating a data analysis device according to an exemplary embodiment.

Fig. 8 is a block diagram of an electronic device, according to an example embodiment.

Detailed Description

In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.

It should be further noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for presentation, analyzed data, etc.) related to the present disclosure are information and data authorized by the user or sufficiently authorized by each party.

Fig. 1 is a flowchart illustrating a data analysis method according to an exemplary embodiment, which is used in a terminal as shown in fig. 1, and includes the following steps.

In step S101, in response to a data analysis request, configuration information carried by the data analysis request is obtained; the configuration information includes: lane information and interface information.

The data analysis request refers to a request for testing the abnormal operation condition of the terminal to perform abnormal analysis, the data analysis request can be triggered by a test user executing the abnormal test of the terminal, and the configuration information is configuration information related to the data analysis request, which is configured by the test user in the process of triggering the data analysis request, wherein the configuration information can comprise lane information for executing the abnormal test and interface information related to an interface for inputting abnormal data.

Specifically, when the test user performs an anomaly test for the terminal, a data analysis request may be triggered at the terminal, and lane information and interface information related to the data analysis request may be input as configuration information, and then the terminal may respond to the request to obtain the configuration information input by the test user.

In step S102, an abnormal data index matching the data analysis request is obtained;

in step S103, based on the lane information, the interface information, and the abnormal data index, corresponding target abnormal structure data is acquired from the abnormal structure database constructed in advance; the exception configuration database contains exception configuration data of a plurality of exception handling types.

The exception structure database is a database for storing exception structure data, which may be constructed in advance, and in which exception structure data of various exception handling types are stored in advance, for example, exception structure data of a structure in which a data variable is mutated to a null value or a null array, or exception structure data of a structure in which a data variable is lost. The abnormal data index is an index for searching for abnormal structure data contained in the abnormal structure database. In general, for configuration information carried by the same data analysis request, that is, the same lane information and interface information, the corresponding exception configuration data stored in the exception configuration database may also be multiple, and then the exception data index is an index for identifying each exception configuration data matching the lane information and the interface information, where the index may be updated during the process of executing the exception test, and the exception data index matched with the data analysis request refers to the data index corresponding to the current data analysis request. The target abnormal structure data refers to the abnormal structure data which is matched with the lane information, the interface information and the abnormal data index.

Specifically, after obtaining the lane information and the interface information, the terminal may obtain an abnormal data index matching the data analysis request based on the simulation service, so as to screen out, from an abnormal structure database including abnormal structure data of a plurality of types of abnormal processing, which is constructed in advance, the abnormal structure data matching the lane information, the interface information and the abnormal data index as target abnormal structure data, using the lane information, the interface information and the abnormal data index.

For example, for the lane information and the interface information, 3 pieces of abnormal structure data may be included in the abnormal structure database, namely, abnormal structure data 1, abnormal structure data 2 and abnormal structure data 3, and after the terminal obtains the lane information and the interface information, it may be determined that the data analysis request is currently matched with the abnormal data index, if the abnormal data index is index 1, the terminal may use the abnormal structure data 1 as the target abnormal structure data, and if the abnormal data index is updated to index 2 during the abnormal test corresponding to the data analysis request, the terminal may use the abnormal structure data 2 as the target abnormal structure data again.

In step S104, abnormal data is generated based on the target abnormal configuration data, and the abnormal data is input to the data interface characterized by the interface information, thereby obtaining an abnormal test result corresponding to the abnormal data.

The abnormal data is the data used for simulating the abnormal environment finally, after the target abnormal structure data is obtained, the terminal can also generate corresponding abnormal data by calling the simulation test service, and input the abnormal data into a data interface represented by interface information configured by an abnormal test user, so that the abnormal test of the abnormal data is realized, and a corresponding abnormal test result is obtained.

In the data analysis method, configuration information carried by a data analysis request is obtained by responding to the data analysis request; the configuration information includes: lane information and interface information; acquiring an abnormal data index matched with the data analysis request; based on lane information, interface information and abnormal data index, acquiring corresponding target abnormal construction data from a pre-constructed abnormal construction database; the abnormal structure database contains abnormal structure data of various abnormal processing types; generating abnormal data based on the target abnormal construction data, inputting the abnormal data into a data interface characterized by interface information, and thus obtaining an abnormal test result corresponding to the abnormal data. According to the method and the device, when the abnormal test is executed, corresponding lane information and interface information can be configured, after the abnormal data index is obtained, target abnormal construction data can be obtained from an abnormal construction database which is built in advance and contains abnormal construction data of various abnormal processing types, after the target abnormal construction data is utilized to generate the abnormal data, the abnormal data are input into a data interface represented by the interface information, and accordingly, a corresponding abnormal test result is obtained.

In an exemplary embodiment, as shown in fig. 2, before step S103, the method may further include:

in step S201, a front end interface of an abnormal configuration platform is displayed.

The abnormal configuration platform may refer to a network platform for constructing abnormal configuration data contained in an abnormal configuration database, in this embodiment, a network platform may be pre-built for constructing abnormal configuration data, and the front end interface is an interface displayed on the terminal by the network platform, and may be a network interface displayed by the terminal. Specifically, when the user needs to build abnormal construction data, for example, a certain abnormal construction data is newly added, the user can log in the abnormal construction platform, so that a corresponding front-end interface is displayed on the terminal.

In step S202, for the to-be-constructed abnormal configuration data of the plurality of types of abnormal processing, the abnormal data configuration information of the to-be-constructed abnormal configuration data input in the presented front-end interface is acquired.

The abnormal construction data to be constructed refers to abnormal construction data that a user needs to form through the abnormal construction platform, and the abnormal data configuration information refers to configuration information required for forming the abnormal construction data to be constructed. Specifically, the user may input configuration information for constructing the abnormal configuration data on the front end interface of the abnormal configuration platform, for example, a plurality of configuration templates for configuring the abnormal configuration data may be displayed in advance on the front end interface, and after the user selects a corresponding configuration template, the abnormal configuration data corresponding to the configuration template may be generated and used as the abnormal configuration data corresponding to the abnormal configuration data, so as to implement the input of the abnormal configuration data.

In step S203, the abnormal construction data is constructed according to the abnormal data construction rule and the abnormal data arrangement information set in advance by the abnormal construction platform, and the abnormal construction data is stored in the abnormal construction database.

The rule for generating the abnormal data may be a rule set in the abnormal configuration platform in advance, specifically, after the terminal obtains the configuration information of the abnormal data input by the user in step S202, the abnormal configuration data matched with the configuration information of the abnormal data input by the user may be generated by using the rule for generating the abnormal data set in advance in the abnormal configuration platform, and the configured abnormal configuration data may be stored in the abnormal configuration database, so that when the terminal performs the abnormal test, the configured abnormal configuration data may be obtained from the abnormal configuration database through the simulation test service, so as to simulate and generate the abnormal data, and further realize the simulation test of the abnormal data.

In this embodiment, an abnormal structure platform for constructing abnormal structure data may be pre-built, and when a user needs to construct the abnormal structure data, only the front end interface of the abnormal structure platform is required to input corresponding abnormal data configuration information, and then the abnormal structure data may be generated by an abnormal data construction rule preset by the abnormal structure platform, so that various types of abnormal structure data may be quickly generated, and the generation efficiency of the abnormal structure data may be improved.

Further, the abnormal data configuration information includes: raw data corresponding to the exception construction data and processing type information for characterizing exception processing types; the original data is non-abnormal data; as shown in fig. 3, step S203 may further include:

in step S301, a target abnormal data construction rule matching the processing type information is acquired from the abnormal data construction rules.

The configuration information of the abnormal data may include original data and processing type information for representing an abnormal processing type, where the original data refers to data that can normally run, i.e. non-abnormal data, and the processing type information is processing type information representing abnormal processing of the original data. In this embodiment, the exception configuration data may be obtained after performing exception processing of the type represented by the above processing type information on the original data. Meanwhile, since the number of the exception handling types is multiple, and the construction modes of the exception construction data of different exception handling types are also different, the exception construction data of different exception handling types respectively correspond to different exception data construction rules, and the target exception data construction rules refer to the exception data construction rules corresponding to the handling type information contained in the exception data configuration information.

For example, the types of the abnormal processing may include a plurality of types, and may be an abnormal processing type 1 including a mutation processing of the original data, an abnormal processing type 2 including a discard processing of the original data, and an abnormal processing type 3 including a truncate processing of the original data, and the respective abnormal processing types are respectively provided with corresponding abnormal data construction rules, respectively an abnormal data construction rule 1, an abnormal data construction rule 2, and an abnormal data construction rule 3. If the user configures to perform mutation processing on a certain piece of original data in the abnormal data configuration information, the corresponding processing type information may be mutation type information, and at this time, the terminal may determine an abnormal data rule corresponding to the abnormal processing type 1 as a target abnormal data construction rule. If the user configures to discard a certain original data in the abnormal data configuration information, the corresponding processing type information can be discarding type information, and at this time, the terminal can determine an abnormal data rule corresponding to the abnormal processing type 2 as a target abnormal data construction rule.

In step S302, according to the target abnormal data construction rule, the original data is subjected to abnormal processing, so as to obtain abnormal construction data corresponding to the original data.

After determining the target abnormal data construction rule, the original data may be subjected to abnormal processing by using the target abnormal data construction rule, so as to generate abnormal construction data corresponding to the original data.

In this embodiment, the configuration information of the exception data for generating the exception configuration data may include the original data and the processing type information, so that the exception processing may be performed on the original data by using a target exception data configuration rule preset by the exception configuration platform and matched with the processing type information, thereby generating the exception configuration data of the exception type corresponding to the original data, and further improving the efficiency of configuration of the exception configuration data.

Further, the original data includes a plurality of node data; abnormal data configuration information, further comprising: node identification information; step S302 may further include: acquiring target node data corresponding to the node identification information from a plurality of node data of the original data; and carrying out exception processing on the target node data according to the target exception data construction rule to construct exception construction data.

In this embodiment, the original data may be composed of a plurality of node data, for example, the original data may be data composed of four variables, in which case each variable may be one node data, and the node identification information is identification information for representing each node data. In this embodiment, the user may also configure that only a part of the node data in the original data is subjected to exception processing to construct exception configuration data, and the node identification information is node information identifying that exception processing is required. The target node data refers to node data corresponding to the node identification information among the plurality of node data contained in the original data.

Specifically, the user may further configure node identification information of the node data to be subjected to exception processing in the exception data configuration information, and after obtaining the exception data configuration information, the terminal may determine node data corresponding to the node identification information from a plurality of node data corresponding to the original data, as target node data, so as to perform exception processing on the target node data based on a target exception data construction rule, thereby constructing corresponding exception construction data.

For example, the original data may be data composed of four variables, and if the user only needs to perform mutation processing on the third variable data in the original data, node identification information for identifying the third variable data may be added to the abnormal data configuration information, so that when the abnormal construction data is constructed, the third variable data of the original data may be taken as target node data, so that the abnormal processing is performed only on the third variable data, instead of performing the abnormal processing on all of the four variables of the original data, to generate the corresponding abnormal construction data.

In this embodiment, the user may further configure the exception configuration data by setting the node identification information in the exception data configuration information, and the terminal may perform exception processing on only the target node data in the original data corresponding to the node identification information, without performing exception processing on all the node data of the original data, thereby further improving the accuracy of generating the exception configuration data.

In an exemplary embodiment, the processing type information includes variation type information, discard type information, and cut-off type information; performing exception processing on target node data according to a target exception data construction rule to construct exception construction data, wherein the exception construction data comprises at least one of the following: performing mutation processing on the target node data according to the target abnormal data construction rule to construct abnormal construction data; discarding the target node data according to the target abnormal data construction rule to construct abnormal construction data; and according to the target abnormal data construction rule, carrying out truncation processing on the target node data to construct abnormal construction data.

In this embodiment, the exception handling type information may include three types of mutation type information for mutating the target node data in the original data, for example, mutation type information mutated to a null value or a null array, discard type information for discarding the target node data in the original data, and cut-off type information for cutting off the target node data in the original data, and so on. Accordingly, if the abnormality processing type information is mutation type information, the terminal may perform mutation processing on the target node data to construct abnormality structural data corresponding to the original data, if the abnormality processing type information is discard type information, the terminal may perform discard processing on the target node data to construct abnormality structural data corresponding to the original data, and if the abnormality processing type information is cut-off type information, the terminal may perform cut-off processing on the target node data to construct abnormality structural data corresponding to the original data.

In this embodiment, the processing type information includes mutation type information, discard type information, and cut-off type information, so that the abnormal configuration data of the terminal structure may be one of performing mutation processing on the target node data in the original data, discarding processing on the target node data in the original data, and cutting-off processing on the target node data in the original data, so that the variety of the abnormal configuration data types may be further improved.

In an exemplary embodiment, the abnormal data configuration information further includes: interface information corresponding to the abnormal construction data; step S203 may further include: obtaining lane information matched with a construction request corresponding to the abnormal construction data; binding the abnormal construction data with interface information corresponding to the abnormal construction data and lane information matched with the construction request, and storing the abnormal construction data into an abnormal construction database.

In the configuration information of the user configuration anomaly data, interface information corresponding to the anomaly construction data may also be configured, and the interface information may be used to characterize an input interface of anomaly data generated according to the anomaly construction data. The lane information matched with the abnormal construction data can be determined according to a construction request, triggered by a user, for the abnormal construction data, for example, the lane information can be generated based on a user account carried in the construction request. Then, the generated abnormal structure data can be respectively bound with the lane information and the interface information and stored in an abnormal structure database, so that the generated abnormal structure data can be queried by utilizing the lane information and the interface information carried in the data analysis request when the abnormal test is performed.

In this embodiment, the user may further configure interface information corresponding to the abnormal configuration data in the abnormal data configuration information, and when the abnormal configuration data is stored, may further determine, according to a configuration request for configuring the abnormal configuration data, lane information matched with the abnormal configuration data, so that after the abnormal configuration data is bound with the lane information and the interface information, the lane information is stored in the abnormal configuration database, thereby further improving efficiency of storing the abnormal configuration data.

In addition, after step S203, it may further include: and displaying the configuration information of the abnormal data corresponding to the abnormal construction data of each abnormal processing type through the front-end interface.

After the terminal completes the construction of the abnormal construction data through the abnormal construction platform, the abnormal construction platform can also display the abnormal configuration information corresponding to the constructed abnormal construction data of each abnormal processing type on the front end interface of the abnormal construction platform, such as the original data forming the abnormal construction data, the lane information and the interface information bound by the abnormal construction data, the target node data for carrying out the abnormal processing on the original data and the like.

In this embodiment, after the construction of the abnormal construction data is completed, the terminal may further display the abnormal data configuration information corresponding to the abnormal construction data on the front end interface of the abnormal construction platform, so as to inform the user of the related information of the abnormal construction data generated, thereby further improving the intelligence of the construction of the abnormal construction data.

In an exemplary embodiment, the front-end interface includes a preset control for determining the data index; step S102 may further include: acquiring user operation information based on a preset control, and determining an abnormal data index matched with the data analysis request according to the user operation information; after determining the abnormal data index matched with the data analysis request according to the user operation information, the method further comprises the following steps: and obtaining the abnormal data based on the abnormal data index which is determined to be matched with the data analysis request according to the user operation information through the front-end interface display.

In this embodiment, the abnormal data index may be specified by a user, for example, the user may specify a corresponding data index through a control for determining the data index included on the front end interface of the abnormal configuration platform, so that the terminal may use the data index specified by the user as the abnormal data index matched with the data analysis request based on the user operation information, or may use a control for clicking a preset data index on the front end interface of the abnormal configuration platform, for example, a control is used to use the last data index before updating, and again use the control as the abnormal data index after updating, to execute the abnormal test of the abnormal data generated by the abnormal data index again, and may display the abnormal data generated according to the abnormal data index set by the user on the front end interface.

For example, for a certain data analysis request, the terminal has obtained target abnormal configuration data corresponding to 4 data indexes from the target abnormal configuration data, namely abnormal configuration data a, abnormal configuration data B, abnormal configuration data C and abnormal configuration data D, respectively, and generates corresponding abnormal data, namely abnormal data a, abnormal data B, abnormal data C and abnormal data D, respectively, to implement an abnormal test, if the user wants to view the abnormal test result for a certain abnormal data again, if the user needs to view the abnormal test result for abnormal data B, the user can click a control for setting a data index displayed on the front end interface, and input the data index 2, at this time, the terminal uses the data index 2 as the abnormal data index currently matched by the data analysis request, thereby obtaining the abnormal data B corresponding to the abnormal configuration data B again, to implement the abnormal test, and also can display the abnormal data B on the front end interface displayed by the terminal. Similarly, the preset control may be configured to set the previous data index as an abnormal data index that is currently matched with the data analysis request, and after the user clicks the preset control, the terminal uses the previous data index, that is, the data index 4, as the abnormal data index that is currently matched with the data analysis request, so as to obtain the abnormal data D corresponding to the abnormal configuration data D again, to implement an abnormal test, and may also display the abnormal data D on the front end interface displayed by the terminal.

In this embodiment, the user may further implement the specification of the abnormal data index through a preset control for determining the data index provided by the front end interface of the abnormal configuration platform, and may further display the abnormal data generated by using the abnormal data index on the front end interface, thereby further improving the intelligence of obtaining the abnormal data index.

In an exemplary embodiment, step S102 may further include: acquiring the input times of the current abnormal data of the data interface; and obtaining an abnormal data index according to the input times.

If the user does not specify the abnormal data index, the obtaining of the abnormal data index may be determined based on the number of times the terminal currently inputs the abnormal data to the data interface, for example, the number of times the terminal currently inputs the abnormal data to the data interface is 0, which indicates that the obtained target abnormal configuration data is the data interface which is used for generating the abnormal data for the first time and is characterized by inputting the interface information, at this time, the terminal may determine that the abnormal data index matched with the current data analysis request is the data index 1, and if the number of times the terminal currently inputs the abnormal data to the data interface is 1, which indicates that the obtained target abnormal configuration data is used for the second time and is used for generating the abnormal data for the second time and is characterized by inputting the interface information, which indicates that the obtained target abnormal configuration data is the data index matched with the current data analysis request is the data index 2.

In this embodiment, the terminal may further obtain the abnormal data index based on the number of times of inputting the current abnormal data of the data interface, so as to automatically determine the abnormal data index matched with the current data analysis request by the terminal, without actively setting the abnormal data index by the user each time, and further improve the efficiency of the abnormal test.

In an exemplary embodiment, an exception analysis method is further provided, by constructing an exception structure platform, the scene data of issuing exceptions, truncation, discarding and the like are conveniently and quickly constructed, so that various issuing field exceptions of a server can be directly simulated from an interface layer, the technical architecture of the exception analysis method can be shown in fig. 4, and the method specifically comprises the following steps:

1. and (3) realizing new and edit (interface, replacement node, discarding or not, lane and the like) related configuration information of the abnormal construction data through an abnormal construction platform, and displaying a key information list.

2. The abnormal construction platform is provided with an abnormal construction rule, such as a mutation rule, a discarding rule, a cutting rule and the like in advance, so that the abnormal construction rule and the configuration information of the abnormal construction data are utilized to generate the abnormal construction data, and the abnormal construction data, the lane information and the interface information are bound and stored in the database.

3. When testing, the user can configure the lane information and the interface information for the mobile terminal executing the test, call the simulation test service, obtain the related index information after the simulation test service obtains the lane information and the interface information, query the database by utilizing the lane information, the interface information and the index information to obtain the abnormal construction data, generate the abnormal data corresponding to the abnormal construction data by utilizing the simulation test service, input the abnormal data into the interface matched with the interface information of the mobile terminal to realize the abnormal test, and input the data through the on-line interface for the other interfaces.

Specifically, the process of creating the abnormal structure data may be as shown in fig. 5:

(1) The user triggers the construction request through the front end interface of the abnormal construction platform, and inputs interface information, original data, an abnormal processing mode, configuration data such as an abnormal processing node and the like.

(2) The abnormal construction platform checks the configuration data of the construction request, so that the configuration information is utilized to generate abnormal construction data, and the abnormal construction data is stored in a database.

(3) And returning the configuration data to the front end of the exception construction platform for presentation, such as presentation interface information, original data, exception processing nodes, lane information and the like.

The flow of the anomaly test performed by the mobile terminal may be as shown in fig. 6:

(1) The user configures the lane information and interface information for the anomaly test through the mobile terminal.

(2) The mobile terminal calls the simulation test service, wherein the interface configured by the user acquires the abnormal construction data matched with the lane information and the interface information from the abnormal construction database to generate an interface corresponding to the abnormal data input interface information, and the other interfaces acquire data from the on-line interface to input so as to realize the abnormal operation test of the mobile terminal.

Through the above embodiment, through the abnormal structure platform, abnormal structure data can be rapidly generated, the method is suitable for a full-volume service interface, the mobile terminal can also simulate abnormal operation through rapid access and use, abnormal problems in use are solved, and the functional capabilities of positioning, reproduction, log tracking and the like are supported, so that the stability risk of the mobile terminal can be found in advance, and the stable operation capability of the mobile terminal is improved.

It should be understood that, although the steps in the flowcharts of this disclosure are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps in the figures may include steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages in other steps.

It should be understood that the same/similar parts of the embodiments of the method described above in this specification may be referred to each other, and each embodiment focuses on differences from other embodiments, and references to descriptions of other method embodiments are only needed.

Fig. 7 is a block diagram illustrating a data analysis device according to an exemplary embodiment. Referring to fig. 7, the apparatus includes a test configuration acquisition unit 701, a data index acquisition unit 702, a configuration data acquisition unit 703, and an abnormal data test unit 704.

A test configuration obtaining unit 701 configured to obtain configuration information carried by a data analysis request in response to the data analysis request; the configuration information includes: lane information and interface information;

a data index acquisition unit 702 configured to perform acquisition of an abnormal data index matched with the data analysis request;

a construction data acquisition unit 703 configured to perform acquisition of corresponding target abnormal construction data from an abnormal construction database constructed in advance based on the lane information, the interface information, and the abnormal data index; the abnormal structure database contains abnormal structure data of various abnormal processing types;

And an abnormal data testing unit 704 configured to perform generation of abnormal data based on the target abnormal configuration data, input the abnormal data to the data interface characterized by the interface information, and thereby obtain an abnormal test result corresponding to the abnormal data.

In an exemplary embodiment, the data analysis device further includes: an abnormal data construction unit configured to execute a front end interface showing an abnormal construction platform; obtaining abnormal data configuration information of the to-be-constructed abnormal construction data input in a displayed front-end interface aiming at the to-be-constructed abnormal construction data of a plurality of abnormal processing types; constructing abnormal construction data according to an abnormal data construction rule and abnormal data configuration information which are preset by an abnormal construction platform, and storing the abnormal construction data into an abnormal construction database.

In an exemplary embodiment, the anomalous data configuration information includes: raw data corresponding to the exception construction data and processing type information for characterizing exception processing types; the original data is non-abnormal data; an abnormal data construction unit further configured to execute a target abnormal data construction rule that is matched with the processing type information from among the abnormal data construction rules; and carrying out exception processing on the original data according to the target exception data construction rule to obtain exception construction data corresponding to the original data.

In an exemplary embodiment, the raw data comprises a plurality of node data; abnormal data configuration information, further comprising: node identification information; the abnormal data construction unit is further configured to acquire target node data corresponding to the node identification information from a plurality of node data of the original data; and carrying out exception processing on the target node data according to the target exception data construction rule to construct exception construction data.

In an exemplary embodiment, the processing type information includes variation type information, discard type information, and cut-off type information; the abnormal data construction unit is further configured to execute mutation processing on the target node data according to the target abnormal data construction rule to construct abnormal construction data; discarding the target node data according to the target abnormal data construction rule to construct abnormal construction data; and according to the target abnormal data construction rule, carrying out truncation processing on the target node data to construct abnormal construction data.

In an exemplary embodiment, the abnormal data configuration information further includes: interface information corresponding to the abnormal construction data; an abnormal data construction unit further configured to perform acquisition of lane information matching a construction request corresponding to the abnormal construction data; binding the abnormal construction data with interface information corresponding to the abnormal construction data and lane information matched with the construction request, and storing the abnormal construction data into an abnormal construction database.

In an exemplary embodiment, the exception data construction unit is further configured to execute exception data configuration information respectively corresponding to the exception construction data showing each exception processing type through the front-end interface.

In an exemplary embodiment, the front-end interface includes a preset control for determining the data index; the data index obtaining unit 702 is further configured to obtain user operation information based on a preset control, and determine an abnormal data index matched with the data analysis request according to the user operation information; the data analysis device further includes: and the abnormal data display unit is configured to display, through the front-end interface, abnormal data obtained based on the abnormal data index which is determined to be matched with the data analysis request according to the user operation information.

In an exemplary embodiment, the data index obtaining unit 702 is further configured to perform obtaining the number of inputs of the current input abnormal data of the data interface; and obtaining an abnormal data index according to the input times.

The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

Fig. 8 is a block diagram illustrating an electronic device 800 for anomaly testing, according to an example embodiment. For example, the electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.

Referring to fig. 8, an electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.

The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interactions between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, video, and so forth. The memory 804 may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, optical disk, or graphene memory.

The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 800.

The multimedia component 808 includes a screen between the electronic device 800 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operational mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.

The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the electronic device 800. For example, the sensor assembly 814 may detect an on/off state of the electronic device 800, a relative positioning of the components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of a user's contact with the electronic device 800, an orientation or acceleration/deceleration of the device 800, and a change in temperature of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices, either wired or wireless. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, an operator network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.

In an exemplary embodiment, a computer-readable storage medium is also provided, such as memory 804 including instructions executable by processor 820 of electronic device 800 to perform the above-described method. For example, the computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

In an exemplary embodiment, a computer program product is also provided, comprising instructions executable by the processor 820 of the electronic device 800 to perform the above-described method.

It should be noted that the descriptions of the foregoing apparatus, the electronic device, the computer readable storage medium, the computer program product, and the like according to the method embodiments may further include other implementations, and the specific implementation may refer to the descriptions of the related method embodiments and are not described herein in detail.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (12)

1. A method of data analysis, comprising:

responding to a data analysis request, and acquiring configuration information carried by the data analysis request; the configuration information includes: lane information and interface information;

acquiring an abnormal data index matched with the data analysis request;

acquiring corresponding target abnormal construction data from a pre-constructed abnormal construction database based on the lane information, interface information and the abnormal data index; the abnormal structure database comprises abnormal structure data of various abnormal processing types;

generating abnormal data based on the target abnormal construction data, and inputting the abnormal data into a data interface represented by the interface information, thereby obtaining an abnormal test result corresponding to the abnormal data.

2. The method of claim 1, wherein before obtaining the corresponding target abnormal structure data from the pre-constructed abnormal structure database, further comprises:

displaying the front end interface of the abnormal structure platform;

obtaining abnormal construction data to be constructed, which are input in the displayed front-end interface, aiming at a plurality of abnormal processing types;

Constructing the abnormal construction data according to an abnormal data construction rule preset by the abnormal construction platform and the abnormal data configuration information, and storing the abnormal construction data into the abnormal construction database.

3. The method of claim 2, wherein the anomalous data configuration information comprises: raw data corresponding to the exception construction data and processing type information for representing exception processing types; the original data is non-abnormal data;

the constructing the abnormal construction data according to the preset abnormal data construction rule and the abnormal data configuration information comprises the following steps:

acquiring a target abnormal data construction rule matched with the processing type information from the abnormal data construction rule;

and carrying out exception processing on the original data according to the target exception data construction rule to obtain the exception construction data corresponding to the original data.

4. A method according to claim 3, wherein the raw data comprises a plurality of node data; the abnormal data configuration information further includes: node identification information;

performing exception processing on the original data according to the target exception data construction rule to construct the exception construction data, including:

Acquiring target node data corresponding to the node identification information from a plurality of node data of the original data;

and carrying out exception processing on the target node data according to the target exception data construction rule to construct the exception construction data.

5. The method of claim 4, wherein the processing type information includes variant type information, discard type information, and cut-off type information;

performing exception processing on the target node data according to the target exception data construction rule to construct the exception construction data, wherein the exception construction data comprises at least one of the following:

performing mutation processing on the target node data according to the target abnormal data construction rule to construct the abnormal construction data;

discarding the target node data according to the target abnormal data construction rule to construct the abnormal construction data;

and according to the target abnormal data construction rule, cutting off the target node data to construct the abnormal construction data.

6. The method of claim 3, wherein the anomalous data configuration information further comprises: interface information corresponding to the abnormal construction data;

The storing the abnormal construction data into the abnormal construction database includes:

obtaining lane information matched with a construction request corresponding to the abnormal construction data;

binding the abnormal construction data with interface information corresponding to the abnormal construction data and lane information matched with the construction request, and storing the abnormal construction data into the abnormal construction database.

7. The method of claim 2, wherein after storing the anomaly construction data in the anomaly construction database, further comprising:

and displaying the configuration information of the abnormal data corresponding to the abnormal construction data of each abnormal processing type through the front-end interface.

8. The method of claim 2, wherein the front-end interface includes a preset control for determining a data index;

the obtaining the abnormal data index matched with the data analysis request comprises the following steps:

acquiring user operation information based on the preset control, and determining an abnormal data index matched with the data analysis request according to the user operation information;

after determining the abnormal data index matched with the data analysis request according to the user operation information, the method further comprises the following steps:

And displaying, by the front-end interface, the abnormal data based on the abnormal data index which is determined to be matched with the data analysis request according to the user operation information.

9. The method of claim 1, wherein the obtaining the exception data index matching the data analysis request comprises:

acquiring the input times of the current abnormal data of the data interface;

and obtaining the abnormal data index according to the input times.

10. A data analysis device, comprising:

the test configuration acquisition unit is configured to respond to the data analysis request and acquire configuration information carried by the data analysis request; the configuration information includes: lane information and interface information;

a data index acquisition unit configured to perform acquisition of an abnormal data index matched with the data analysis request;

a construction data acquisition unit configured to perform acquisition of corresponding target abnormal construction data from an abnormal construction database constructed in advance based on the lane information, interface information, and the abnormal data index; the abnormal structure database comprises abnormal structure data of various abnormal processing types;

And the abnormal data testing unit is configured to execute the generation of abnormal data based on the target abnormal construction data, input the abnormal data into the data interface characterized by the interface information, and obtain an abnormal test result corresponding to the abnormal data.

11. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the data analysis method of any one of claims 1 to 9.

12. A computer readable storage medium, characterized in that instructions in the computer readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the data analysis method of any one of claims 1 to 9.