CN114186873B - Processing variable verification method and device and related equipment - Google Patents
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Abstract
The application provides a processing variable verification method, a device, computer equipment and a computer readable storage medium, which belong to the technical field of data analysis, and aim to solve the technical problem of low processing variable verification efficiency.
Description
Technical Field
The present application relates to the field of data analysis technologies, and in particular, to a method and apparatus for verifying a processing variable, a computer device, and a computer readable storage medium.
Background
The verification of the risk variable is a verification work which is important in the field of financial risk control. Whether the risk variable is correct or not directly determines the accuracy of the risk model, and the accuracy of the risk model directly determines the effectiveness of risk control of the financial transaction, so the risk variable is the basis of the financial risk control.
The risk variables are generally from data of several ways such as request uploading, offline data files or real-time acquisition, and most of the risk variables are usually from processing the offline data files, and the risk variables are based on processing the values of each field in the offline data files of different data structures, that is, the risk variables are processing variables. The control risk in financial wind control ensures the accuracy of risk variable processing, and the accuracy of risk variable processing is controlled through risk variable verification.
Aiming at the risk variable, the traditional verification mode is to firstly construct a file, cover different data forms of each field in the file, arrange and combine the different data forms of each field into a plurality of pieces of data, carry out logic processing by using the constructed file, output the risk variable, then carry out logic calculation based on the value of the corresponding field of the risk variable, compare with the actually output variable value to verify the correctness of the risk variable.
Disclosure of Invention
The application provides a processing variable verification method, a processing variable verification device, computer equipment and a computer readable storage medium, which can solve the technical problem of low verification efficiency of processing variables in the prior art.
In a first aspect, the present application provides a process variable verification method, including: acquiring a preset file constructed based on a formatted file structure definition, wherein the preset file comprises preset input variables, the preset input variables are described by adopting input variable names, and all the preset input variables cover all input data of preset business; performing variable processing on the preset input variable by adopting a preset business variable processing mode to obtain a processing variable, and obtaining a first mapping relation between the input variable and the processing variable, wherein the processing variable is described by adopting a processing variable name; acquiring a name relationship between the input variable name and the processing variable name, classifying a first mapping relationship of a preset input variable and a processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set; identifying a logic processing relation between specific business input data and clustering processing variables in the preset business data, and determining a second mapping relation between the clustering processing variables and the specific business input data according to the logic processing relation; from the cluster mapping relation set, associating a target input variable, wherein the target input variable is a variable with the second mapping relation with the cluster processing variable; and inputting preset historical service input data corresponding to the target input variable into the clustering processing variable to obtain an output result, and comparing the output result with a historical service actual result corresponding to the preset historical service input data to obtain a comparison result so as to verify the clustering processing variable.
In a second aspect, the present application also provides a process variable verification apparatus, including: the first acquisition unit is used for acquiring a preset file constructed based on the formatted file structure definition, wherein the preset file comprises preset input variables, the preset input variables are described by adopting input variable names, and all the preset input variables cover all input data of preset business; the variable processing unit is used for performing variable processing on the preset input variable by adopting a preset business variable processing mode to obtain a processing variable and a first mapping relation between the input variable and the processing variable, wherein the processing variable is described by adopting a processing variable name; the classifying unit is used for acquiring the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship of the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set; the identification unit is used for identifying a logic processing relation between specific business input data and clustering processing variables in the preset business data and determining a second mapping relation between the clustering processing variables and the specific business input data according to the logic processing relation; the association unit is used for associating a target input variable from the clustering mapping relation set, wherein the target input variable is a variable which has the second mapping relation with the clustering processing variable; and the verification unit is used for inputting the preset historical service input data corresponding to the target input variable into the clustering processing variable to obtain an output result, and comparing the output result with the actual historical service result corresponding to the preset historical service input data to obtain a comparison result so as to verify the clustering processing variable.
In a third aspect, the present application also provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the process variable verification method when executing the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the process variable verification method.
The application provides a processing variable verification method, a device, computer equipment and a computer readable storage medium, which are used for constructing preset files of various data forms and boundary values of input data in a preset service by constructing a total amount, constructing processing variables based on the preset files, primarily clustering the processing variables according to the input variable names of the preset input variables and the processing variable names of the processing variables to obtain clustered processing variables, simultaneously identifying a second mapping relation corresponding to the clustered processing variables based on preset service data, associating all preset input variables which are stored in the second mapping relation with the clustered processing variables from a clustering mapping relation set to serve as target input variables, realizing intelligent association of mapping relations between different data forms of the same processing variables and the input variables of boundary values, inputting the preset historical service input data corresponding to the target input variables to the clustered processing variables to obtain output results, accurately comparing the output results with the actual results of the historical service, verifying the clustered processing variables on the basis of covering different data forms and the boundary values of the input variables, rapidly verifying the mapping relations between different data forms and the boundary values of the different data and the boundary values of the different processing variables based on the conventional processing variables, rapidly verifying the mapping relations between the different data forms and the boundary values and the different values of the input variables are rapidly verified relative to the same processing forms of the input variables, the variable verification efficiency can be improved, after the processing variable passes the automatic verification, if the processing variable is required to be automatically verified, for example, when the APP is upgraded, the variable can be repeatedly used and continuously regressed, the follow-up variable verification process is saved, and the follow-up processing variable verification efficiency is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a process variable verification method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a first sub-process of a process variable verification method according to an embodiment of the present application;
FIG. 3 is a schematic block diagram of a process variable verification apparatus provided in an embodiment of the present application;
Fig. 4 is a schematic block diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application. It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Referring to fig. 1, fig. 1 is a schematic flow chart of a process variable verification method according to an embodiment of the application. As shown in FIG. 1, embodiments of the present application may acquire and process related data based on artificial intelligence techniques, wherein artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) is a theory, method, technique and application system that simulates, extends and expands human intelligence using a digital computer or a machine controlled by a digital computer, perceives the environment, acquires knowledge and uses the knowledge to obtain optimal results, the method comprising the steps of S11-S16:
S11, acquiring a preset file constructed based on formatted file structure definition, wherein the preset file comprises preset input variables, the preset input variables are described by adopting input variable names, and all the preset input variables cover all input data of preset business.
Specifically, each field value in different data structure files included in the preset offline data file can be carded and processed based on the preset offline data file, so as to obtain various data forms and boundary values of data included in the preset offline data file, and a preset input variable is constructed based on the data forms and the boundary values, wherein the preset input variable is described by adopting an input variable name, the preset input variable is a preset basic field, and all the preset input variables cover the data forms and the boundary values related to all the input data of a preset service.
And then constructing a preset file based on a formatted file structure definition, wherein the preset file comprises preset input variables corresponding to input data of preset business, the preset input variables relate to different data forms and boundary values of the input data, the formatted file structure definition adopts a preset format definition file structure, the file structure definition of specific file contents is stored through the preset file structure definition, the data forms comprise Chinese, english and other words, numbers or combination of the words and the numbers and other data forms, the boundary values are data ranges corresponding to preset basic fields, and for example, the boundary values can be positive numbers, negative numbers or data ranges of letters and the like larger than the preset number. For example, if the preset service includes 1000 preset input variables such as A, B, C, D and E, each preset input variable corresponds to a different data form of the input data, each preset input variable sets a corresponding boundary value, and the preset file may be constructed by describing 1000 preset input variables such as A, B, C, D and E, and the data form and the boundary value of each preset input variable based on a file structure definition formatted by EXCEL format and the like.
When the processing variable verification is carried out, a preset file is obtained, wherein the preset file comprises preset input variables, all the preset input variables cover all input data of preset services, namely the preset file realizes the full coverage of the input data of the preset specific services and is a combined file of the full input data of the preset services.
S12, carrying out variable processing on the preset input variable by adopting a preset business variable processing mode to obtain a processing variable, and obtaining a first mapping relation between the input variable and the processing variable, wherein the processing variable is described by adopting a processing variable name.
Specifically, based on the preset input variable, a preset business variable processing mode is constructed according to the actual requirement of processing preset business, wherein the preset business variable processing mode is the processing logic of the preset input variable. And performing variable processing on the preset input variable in the preset service variable processing mode, namely performing logic processing on the preset input variable, so as to construct different processing variables, wherein the processing variables are output variables, the processing variables are described by adopting processing variable names, a first mapping relation between the preset input variable and the processing variable is obtained at the same time, the processing variable is a variable required to be used in the processing process of the preset service, and the processing variable can be an intermediate variable for processing the preset service. The preset business variable processing mode is processing logic for processing a preset input variable, namely a mapping relation between the preset input variable and an output variable, and comprises processing logic such as direct assignment, data type conversion, various mathematical conversions of single word segments, multi-field mathematical conversions and the like. For directly assigned processing variables, the preset business variable processing mode is direct assignment, for processing variables which are not directly assigned, if the processing variables are data type conversion, the preset business variable processing mode is a general method for converting data types, for single fields, various mathematical conversions are carried out, the preset business variable processing mode is a general method for converting various mathematics corresponding to development codes one by one, and for other variable processing logics, the preset business variable processing mode is a designated processing conversion method corresponding to other variable processing logics.
Because variable processing is performed on the basis of all preset input variables contained in a preset file, processing variables are obtained, and therefore processing variables which are not required by the preset service exist in a plurality of obtained processing variables.
S13, acquiring a name relationship between the input variable name and the processing variable name, classifying the first mapping relationship of the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set.
Specifically, based on all preset input variables contained in a preset file, a preset business variable processing mode is adopted to generate an output processing variable, then the input variable name of the preset input variable and the processing variable name of the processing variable are obtained, and the name relation between the input variable name and the processing variable name is identified, wherein the name relation can be that the input variable name is a subset of the processing variable name, namely, the input variable name is consistent with the processing variable name, or the input variable name is a substring of the processing variable name.
According to the name relationship, classifying preset input variables and processing variables with the same name relationship and first mapping relationships between the preset input variables and the processing variables into the same category mapping relationship to obtain a clustered first mapping relationship set, wherein the clustered first mapping relationship set comprises clustered processing variables, clustered input variables and clustered mapping relationships between the clustered processing variables and the clustered input variables, and the first mapping relationships with the same default name relationship are equal (basically the first mapping relationships may be different), so that preliminary clustering of the processing variables, the preset input variables corresponding to the processing variables and the first mapping relationships between the processing variables is realized, and preliminary intelligent association of the processing variables, the preset input variables and the first mapping relationships is realized.
S14, identifying a logic processing relation between specific business input data and clustering processing variables in the preset business data, and determining a second mapping relation between the clustering processing variables and the specific business input data according to the logic processing relation.
Specifically, based on preset service data, for example, based on preset offline service data, identifying a logic processing relationship between specific service input data and corresponding clustering processing variables in the preset service data, and determining a second mapping relationship between the clustering processing variables and the specific service input data according to the logic processing relationship, so as to obtain what the corresponding second mapping relationship of the clustering processing variables in the preset service is, wherein the second mapping relationship is used for describing processing logic between the specific service input data and the clustering processing variables, namely, the second mapping relationship between the specific service input data A and the clustering processing variables B, and the second mapping relationship can be direct assignment, type conversion, various mathematical conversion of single word segments or multi-field mathematical conversion, and the like.
S15, associating a target input variable from the clustering mapping relation set, wherein the target input variable is a variable which has the second mapping relation with the clustering processing variable.
Specifically, after the second mapping relation is obtained, according to the second mapping relation, in combination with the construction process of the processing variables, all clustering input variables with the second mapping relation with the clustering processing variables are determined and used as target input variables, and all relevant preset input variables associated with the clustering processing variables are obtained.
S16, inputting preset historical service input data corresponding to the target input variable into the clustering processing variable to obtain an output result, and comparing the output result with a historical service actual result corresponding to the preset historical service input data to obtain a comparison result so as to verify the clustering processing variable.
Specifically, all relevant preset input variables related to the clustering processing variables are used as target input variables, the target input variables comprise data forms and boundary values of all input data related to the clustering processing variables, so that intelligent association of mapping relations is realized for the same processing variable, preset historical service input data corresponding to the target input variables are input to the clustering processing variables based on the clustering mapping relations between the clustering processing variables and the clustering input variables to obtain output results, and the output results are compared with historical service actual results corresponding to the preset historical service input data to obtain comparison results, so that the clustering processing variables are verified by adopting initialization data corresponding to the target input variables, if the comparison results are consistent, the clustering processing variables have no problem, if the comparison results are inconsistent, the clustering processing variables have problems, and manual intervention is needed to be processed.
According to the embodiment of the application, through constructing preset files of various data forms and boundary values of input data in a preset service, constructing processing variables based on the preset files, and carrying out preliminary clustering on the processing variables according to the names of the input variables of the preset input variables and the processing variable names of the processing variables to obtain clustered processing variables, and simultaneously, based on preset service data, identifying a second mapping relation corresponding to the clustered processing variables, according to the second mapping relation, associating all preset input variables with the clustered processing variables in the second mapping relation from a cluster mapping relation set, taking the preset input variables as target input variables, realizing intelligent association of mapping relations of different data forms of the same processing variables with the input variables of the boundary values, then inputting the preset historical service input data corresponding to the target input variables into the clustered processing variables, obtaining output results, and comparing the output results with actual results of the historical service, so as to verify the clustered processing variables, thereby being capable of rapidly and accurately determining all the input variables with different data forms and the boundary values of the clustered processing variables on the basis of the full-quantity covering of the preset service data, realizing rapid verification of the processing variables, being capable of achieving rapid verification of the processing state and the processing variables with respect to the input variables by the prior art after the fact that the input variables are matched with the different data forms of the same data form and the boundary values of the clustering processing variables are verified, if the follow-up processing variable is required to be automatically verified, for example, when the APP is in an upgrade version, the variable can be repeatedly used and continuously regressed, so that the follow-up variable verification process is saved, and the follow-up processing variable verification efficiency is improved.
In an embodiment, the obtaining the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship between the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining the cluster mapping relationship set includes:
identifying whether the process variable name contains the input variable name;
If the processing variable name contains the input variable name, classifying a first mapping relation between a preset input variable with a containing relation and the processing variable into the same category mapping relation to obtain a clustering mapping relation set;
And if the processing variable name does not contain the input variable name, the first mapping relation between the preset input variable and the processing variable is not classified into the same type mapping relation.
Specifically, whether the processing variable name contains the input variable name is identified, if the processing variable name contains the input variable name, a preset input variable with a containing relation, a processing variable, a first mapping relation between the preset input variable and the processing variable are classified into the same type mapping relation, and a clustering mapping relation set is obtained, so that the processing variable, the mapping relation and the input variable are initially and intelligently associated, and if the processing variable name does not contain the input variable name, the preset input variable, the processing variable and the first mapping relation between the preset input variable and the processing variable are not classified into the same type mapping relation.
In an embodiment, the identifying whether the process variable name includes the input variable name includes:
Identifying whether the input variable name is consistent with the processing variable name;
if the input variable name is consistent with the processing variable name, determining that the processing variable name contains the input variable name;
and if the input variable name is inconsistent with the processing variable name, determining that the processing variable name does not contain the input variable name.
Specifically, if the input variable name is consistent with the processing variable name, determining that the processing variable name contains the input variable name, classifying a preset input variable corresponding to the input variable name, a processing variable corresponding to the processing variable name and a mapping relation between the preset input variable and the processing variable into the same type mapping relation, and obtaining a first clustering mapping relation set, so that intelligent association is performed on the processing variable, the corresponding mapping relation and the input variable, if the input variable name is inconsistent with the processing variable name, determining that the processing variable name does not contain the input variable name, and not classifying the first mapping relation between the preset input variable and the processing variable into the same type mapping relation.
In an embodiment, if the input variable name is inconsistent with the process variable name, the method further includes:
identifying whether the input variable name is a substring of the process variable name;
If the input variable name is a substring of the processing variable name, determining that the processing variable name contains the input variable name;
And if the input variable name is not the substring of the processing variable name, determining that the processing variable name does not contain the input variable name.
Specifically, if the input variable name is a substring of the processing variable name, determining that the processing variable name contains the input variable name, classifying a preset input variable corresponding to the input variable name, a processing variable corresponding to the processing variable name, and a mapping relationship between the preset input variable and the processing variable into the same type mapping relationship, so as to further relate the processing variable to the mapping relationship and the input variable, and if the input variable name is not the substring of the processing variable name, determining that the processing variable name does not contain the input variable name, and not classifying a first mapping relationship between the preset input variable and the processing variable into the same type mapping relationship.
Further, referring to fig. 2, fig. 2 is a schematic diagram of a first sub-flow of the process variable verification method provided by the embodiment of the present application, as shown in fig. 2, in this embodiment, after determining that the process variable name includes the input variable name, if the input variable name is a sub-string of the process variable name, the method further includes:
s21, judging whether the input variable name is a substring of other processing variable names;
S22, if the input variable name is not a substring of other processing variable names, executing the step of classifying the first mapping relation between the preset input variable with the containing relation and the processing variable into the same category mapping relation to obtain a clustering mapping relation set;
s23, if the input variable name is a substring of other processing variable names, prompting the mapping relation between the preset input variable and the processing variable.
Specifically, if the input variable name is a substring of the processing variable name, judging whether the input variable name is a substring of other processing variable names, if the input variable name is not a substring of other processing variable names, namely, the processing variable corresponding to the input variable name and the mapping relation between the processing variable corresponding to the input variable name and the processing variable are single, classifying the mapping relation among the preset input variable corresponding to the input variable name, the processing variable corresponding to the processing variable name and the mapping relation among the preset input variable and the processing variable into the same type of mapping relation to obtain a second type mapping relation set, classifying the input variable name, the corresponding processing variable and the mapping relation directly, and if the input variable name is a substring of other processing variable names, namely, the input variable name is a substring of a plurality of processing variable names, prompting the mapping relation among the preset input variable corresponding to the input variable name, the processing variable corresponding to the processing variable name and the preset input variable and the processing variable, mapping relation among the preset input variable corresponding to the processing variable is manually processed, and the mapping relation among the preset input variable and the processing variable is displayed.
In an embodiment, if the input variable name is a substring of the process variable name, determining that the process variable name includes the input variable name includes:
if the input variable name is a substring of the processing variable name, identifying a substring position corresponding to the position of the input variable name in the processing variable name;
Or identifying the substring sequence corresponding to the sequence of the input variable names in the processing variable names, and classifying the first mapping relations between the preset input variables with the same substring position or the same substring sequence and the processing variables into the same category mapping relation to obtain a clustering mapping relation set.
Specifically, for the same preset service variable processing mode, for example, direct assignment, data type conversion, performing various mathematical conversions on a single field, performing multiple field mathematical conversions, and other mapping relations, due to the fact that the same variable processing logic is provided, whether the input variable belongs to the processing variable with the same mapping relation can be determined by identifying whether the substring positions or the substring sequences of the input variable names in the processing variable names are the same. If the input variable name is a substring of the processing variable name, further identifying the substring position or the substring sequence of the input variable name in the processing variable name, classifying preset input variables corresponding to the input variable names with the same substring position or the input variable names with the same substring sequence, processing variables corresponding to the processing variable names and mapping relations between the preset input variables and the processing variables into the same category mapping relation, and obtaining a second category mapping relation set, so that processing variables possibly belonging to the same mapping relation are further and intelligently associated as accurately as possible, and input variables with different data forms and boundary values of the same processing variable are obtained.
In an embodiment, the obtaining the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship between the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining the cluster mapping relationship set includes:
based on a preset neural network model, acquiring a name relationship between the input variable name and the processing variable name, classifying the first mapping relationship of the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set.
Specifically, a neural network model can be pre-built, a training sample is adopted to train a preset neural network model, so that the preset neural network model can accurately identify the name relationship between an input variable name and a processing variable name, then the input variable name and the processing variable name are acquired based on the preset neural network model, the name relationship between the input variable name and the processing variable name is identified, and the preset input variable with the same name relationship, the first mapping relationship between the input variable and the preset input variable and the processing variable are classified as the same category mapping relationship, so that a clustering mapping relationship set is obtained. Based on a preset neural network model, intelligent association of the mapping relation is performed, and accuracy and association efficiency of the intelligent association of the mapping relation can be improved.
It should be noted that, the processing variable verification method described in each of the foregoing embodiments may be used to re-combine the technical features included in the different embodiments according to the need, so as to obtain a combined embodiment, which is within the scope of protection claimed by the present application.
Referring to fig. 3, fig. 3 is a schematic block diagram of a process variable verification apparatus according to an embodiment of the present application. Corresponding to the processing variable verification method, the embodiment of the application also provides a processing variable verification device. As shown in fig. 3, the process variable verification apparatus includes a unit for performing the above-described process variable verification method, and the process variable verification apparatus may be configured in a computer device. Specifically, referring to fig. 3, the processing variable verification device 30 includes a first obtaining unit 31, a variable processing unit 32, a classifying unit 33, an identifying unit 34, an associating unit 35, and a verification unit 36.
The first obtaining unit 31 is configured to obtain a preset file constructed based on a formatted file structure definition, where the preset file includes preset input variables, the preset input variables are described by using input variable names, and all the preset input variables cover all input data of a preset service;
The variable processing unit 32 is configured to perform variable processing on the preset input variable by using a preset service variable processing manner, obtain a processing variable, and obtain a first mapping relationship between the input variable and the processing variable, where the processing variable is described by using a processing variable name;
The classifying unit 33 is configured to obtain a name relationship between the input variable name and the processing variable name, and classify a first mapping relationship between a preset input variable having the same name relationship and a processing variable into the same category mapping relationship, so as to obtain a cluster mapping relationship set;
The identifying unit 34 is configured to identify a logical processing relationship between specific service input data and a clustering processing variable in the preset service data, and determine a second mapping relationship between the clustering processing variable and the specific service input data according to the logical processing relationship;
An association unit 35, configured to associate a target input variable from the cluster mapping relation set, where the target input variable is a variable having the second mapping relation with the cluster processing variable;
And the verification unit 36 is configured to input preset historical service input data corresponding to the target input variable to the clustering processing variable to obtain an output result, and compare the output result with an actual historical service result corresponding to the preset historical service input data to obtain a comparison result, so as to verify the clustering processing variable.
In an embodiment, the classifying unit 33 includes:
a first identifying subunit, configured to identify whether the processing variable name includes the input variable name;
And the first classifying subunit is used for classifying the first mapping relation between the preset input variable with the containing relation and the processing variable into the same type mapping relation if the processing variable name contains the input variable name, so as to obtain a clustering mapping relation set.
In an embodiment, the first identification subunit comprises:
the second identification subunit is used for identifying whether the input variable name is consistent with the processing variable name;
And the first determination subunit is used for determining that the processing variable name comprises the input variable name if the input variable name is consistent with the processing variable name.
In an embodiment, the first identification subunit further comprises:
a third identifying subunit, configured to identify whether the input variable name is a substring of the processing variable name;
and the second determining subunit is used for determining that the processing variable name comprises the input variable name if the input variable name is a substring of the processing variable name.
In an embodiment, the first identification subunit further comprises:
A judging subunit, configured to judge whether the input variable name is a substring of another processing variable name;
and the execution subunit is used for executing the first mapping relation between the preset input variable with the inclusion relation and the processing variable into the same category mapping relation if the input variable name is not a substring of other processing variable names, and obtaining a clustering mapping relation set.
In an embodiment, the second determining subunit comprises:
a fourth identifying subunit, configured to identify, if the input variable name is a substring of the processing variable name, a substring position corresponding to a position of the input variable name in the processing variable name;
Or identifying the substring sequence corresponding to the sequence of the input variable names in the processing variable names, and classifying the first mapping relations between the preset input variables with the same substring position or the same substring sequence and the processing variables into the same category mapping relation to obtain a clustering mapping relation set.
In an embodiment, the classifying unit 33 is specifically configured to obtain a name relationship between the input variable name and the processing variable name based on a preset neural network model, and classify the first mapping relationship between the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, so as to obtain a cluster mapping relationship set.
It should be noted that, as those skilled in the art can clearly understand, the specific implementation process of the processing variable verification device and each unit may refer to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, the description is omitted herein.
Meanwhile, the dividing and connecting modes of the units in the processing variable verification device are only used for illustration, in other embodiments, the processing variable verification device can be divided into different units according to the needs, and different connecting sequences and modes can be adopted for the units in the processing variable verification device so as to complete all or part of functions of the processing variable verification device.
The process variable verification device described above may be implemented in the form of a computer program which is executable on a computer device as shown in fig. 4.
Referring to fig. 4, fig. 4 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a computer device such as a desktop computer or a server, or may be a component or part of another device.
With reference to fig. 4, the computer device 500 includes a processor 502, a memory, and a network interface 505, which are connected by a system bus 501, wherein the memory may include a non-volatile storage medium 503 and an internal memory 504, which may also be a volatile storage medium.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, causes the processor 502 to perform a process variable verification method as described above. The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500. The internal memory 504 provides an environment for the execution of a computer program 5032 in the non-volatile storage medium 503, which computer program 5032, when executed by the processor 502, causes the processor 502 to perform a process variable verification method as described above.
The network interface 505 is used for network communication with other devices. It will be appreciated by those skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device 500 to which the present inventive arrangements may be implemented, and that a particular computer device 500 may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components. For example, in some embodiments, the computer device may include only a memory and a processor, and in such embodiments, the structure and function of the memory and the processor are consistent with the embodiment shown in fig. 4, and will not be described again.
Wherein the processor 502 is configured to execute a computer program 5032 stored in a memory to implement the process variable verification method described in the above embodiments.
It should be appreciated that in embodiments of the present application, the Processor 502 may be a Central processing unit (Central ProcessingUnit, CPU), the Processor 502 may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processors, DSPs), application SPECIFIC INTEGRATED Circuits (ASICs), off-the-shelf Programmable gate arrays (Field-Programmable GATEARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be appreciated by those skilled in the art that all or part of the flow of the method of the above embodiments may be implemented by a computer program, which may be stored on a computer readable storage medium. The computer program is executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present application also provides a computer-readable storage medium. The computer readable storage medium may be a nonvolatile computer readable storage medium or a volatile computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the process variable verification method described in the above embodiments.
The computer readable storage medium may be an internal storage unit of the aforementioned device, such as a hard disk or a memory of the device. The computer readable storage medium may also be an external storage device of the device, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), etc. that are provided on the device. Further, the computer readable storage medium may also include both internal storage units and external storage devices of the device.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and unit described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The storage medium is a physical, non-transitory storage medium, and may be, for example, a U-disk, a removable hard disk, a Read-only memory (ROM), a magnetic disk, or an optical disk.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed.
The steps in the method of the embodiment of the application can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the application can be combined, divided and deleted according to actual needs. In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (10)
1. A process variable verification method, the method comprising:
acquiring a preset file constructed based on a formatted file structure definition, wherein the preset file comprises preset input variables, the preset input variables are described by adopting input variable names, and all the preset input variables cover all input data of preset business;
Performing variable processing on the preset input variable by adopting a preset business variable processing mode to obtain a processing variable, and obtaining a first mapping relation between the input variable and the processing variable, wherein the processing variable is described by adopting a processing variable name;
Acquiring a name relationship between the input variable name and the processing variable name, classifying a first mapping relationship of a preset input variable and a processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set;
Identifying a logic processing relation between specific business input data and clustering processing variables in the preset business data, and determining a second mapping relation between the clustering processing variables and the specific business input data according to the logic processing relation;
From the cluster mapping relation set, associating a target input variable, wherein the target input variable is a variable with the second mapping relation with the cluster processing variable;
and inputting preset historical service input data corresponding to the target input variable into the clustering processing variable to obtain an output result, and comparing the output result with a historical service actual result corresponding to the preset historical service input data to obtain a comparison result so as to verify the clustering processing variable.
2. The method for verifying a processing variable according to claim 1, wherein the obtaining the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship between the preset input variable and the processing variable having the same name relationship into the same category mapping relationship, and obtaining the cluster mapping relationship set includes:
identifying whether the process variable name contains the input variable name;
And if the processing variable name comprises the input variable name, classifying a first mapping relation between a preset input variable with a containing relation and the processing variable into the same category mapping relation to obtain a clustering mapping relation set.
3. The process variable verification method of claim 2, wherein said identifying whether said process variable name contains said input variable name comprises:
Identifying whether the input variable name is consistent with the processing variable name;
and if the input variable name is consistent with the processing variable name, determining that the processing variable name comprises the input variable name.
4. The process variable verification method according to claim 3, further comprising, if the input variable name is inconsistent with the process variable name:
identifying whether the input variable name is a substring of the process variable name;
And if the input variable name is the substring of the processing variable name, determining that the processing variable name contains the input variable name.
5. The process variable verification method according to claim 4, wherein if the input variable name is a substring of the process variable name, determining that the process variable name includes the input variable name further comprises:
judging whether the input variable names are substrings of other processing variable names or not;
and if the input variable name is not a substring of other processing variable names, executing the step of classifying the first mapping relation between the preset input variable with the containing relation and the processing variable into the same type mapping relation to obtain a clustering mapping relation set.
6. The process variable verification method of claim 4, wherein if the input variable name is a substring of the process variable name, determining that the process variable name contains the input variable name comprises:
if the input variable name is a substring of the processing variable name, identifying a substring position corresponding to the position of the input variable name in the processing variable name;
Or identifying the substring sequence corresponding to the sequence of the input variable names in the processing variable names, and classifying the first mapping relations between the preset input variables with the same substring position or the same substring sequence and the processing variables into the same category mapping relation to obtain a clustering mapping relation set.
7. The method for verifying a processing variable according to claim 1, wherein the obtaining the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship between the preset input variable and the processing variable having the same name relationship into the same category mapping relationship, and obtaining the cluster mapping relationship set includes:
based on a preset neural network model, acquiring a name relationship between the input variable name and the processing variable name, classifying the first mapping relationship of the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set.
8. A process variable verification apparatus, said apparatus comprising:
The first acquisition unit is used for acquiring a preset file constructed based on the formatted file structure definition, wherein the preset file comprises preset input variables, the preset input variables are described by adopting input variable names, and all the preset input variables cover all input data of preset business;
The variable processing unit is used for performing variable processing on the preset input variable by adopting a preset business variable processing mode to obtain a processing variable and a first mapping relation between the input variable and the processing variable, wherein the processing variable is described by adopting a processing variable name;
The classifying unit is used for acquiring the name relationship between the input variable name and the processing variable name, classifying the first mapping relationship of the preset input variable and the processing variable with the same name relationship into the same category mapping relationship, and obtaining a clustering mapping relationship set;
The identification unit is used for identifying a logic processing relation between specific business input data and clustering processing variables in the preset business data and determining a second mapping relation between the clustering processing variables and the specific business input data according to the logic processing relation;
The association unit is used for associating a target input variable from the clustering mapping relation set, wherein the target input variable is a variable which has the second mapping relation with the clustering processing variable;
And the verification unit is used for inputting the preset historical service input data corresponding to the target input variable into the clustering processing variable to obtain an output result, and comparing the output result with the actual historical service result corresponding to the preset historical service input data to obtain a comparison result so as to verify the clustering processing variable.
9. A computer device comprising a memory and a processor coupled to the memory; the memory is used for storing a computer program; the processor being adapted to run the computer program to perform the steps of the method according to any of claims 1-7.
10. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1-7.
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