Platform product test data analysis modeling method and device, equipment, storage medium and product

Abstract

The invention discloses a platform product test data analysis modeling method and device, equipment, a storage medium and a product, and relates to the technical field of product testing, and the platform product test data analysis modeling method comprises the steps: determining various function objects corresponding to a plurality of function items of a platform product based on system architecture information of the platform product; determining the position of each functional object in a system link according to the system link information of the platform product, and analyzing to obtain various test data; dividing the test data into public data, basic data and transaction data according to the positions of the function entries and the test data in the system link; and respectively combining the attributes corresponding to the public data, the basic data and the transaction data and the composition factors corresponding to the attributes to obtain respectively corresponding data modeling results. According to the technical scheme, test data of complete platform products can be quickly and efficiently sorted, and the efficiency of automatic number generation, automatic testing and manual number testing is improved.

Description

Technical Field

[0001] The present application relates to the field of product testing technology, and in particular to a platform product testing data analysis modeling method, device, electronic device, computer-readable storage medium and computer program product. Background Art

[0002] For platform products (such as financial platform products) in the actual project testing process, a certain amount of test data that meets the test purpose and test requirements needs to be called. At present, in the process of platform product testing, the acquisition and standardization of test data are mainly affected by the subjective factors of the testers involved in research and development, and the source, sorting, and analysis of test data are not standardized. Therefore, the existing platform product test data acquisition and sorting schemes are poorly standardized, and temporary manual plans need to be formulated when acquiring test data. The quality of the test data sets formed varies, affecting the acquisition efficiency and application efficiency of test data.

[0003] The above information disclosed in this Background section is only for understanding the background of the present application concept and therefore it may contain information that does not constitute prior art. Summary of the invention

[0004] The main purpose of this application is to provide a platform product test data analysis modeling method, device, electronic device, computer-readable storage medium and computer program product, aiming to solve the technical problems of poor acquisition efficiency and application efficiency of existing platform product test data.

[0005] To achieve the above objectives, the present application provides a platform product test data analysis modeling method, the platform product test data analysis modeling method comprising:

[0006] Based on the system architecture information of the platform product, determine various types of functional objects corresponding to the multiple functional items of the platform product;

[0007] According to the system link information of the platform product, determine the position of each functional object in the system link, and analyze and obtain various test data;

[0008] According to the positions of the function items and the test data in the system link, the test data are divided into common data, basic data and transaction data;

[0009] The attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes are respectively combined to obtain data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

[0010] In one embodiment, the step of determining, based on the system architecture information of the platform product, various types of functional objects corresponding to the multiple functional items of the platform product, respectively, includes:

[0011] Generate multi-level function items corresponding to the platform product according to the functions of the platform product represented by the system architecture information of the platform product, wherein the multi-level function items are respectively summarized according to basic functions and transaction functions;

[0012] By extracting the commonality of the functional objects associated with each last-level functional item in the multi-level functional items, the corresponding multi-category functional objects are obtained.

[0013] In one embodiment, the system link information includes at least the types of test data corresponding to the input data and the output data respectively;

[0014] The step of determining the positions of the functional objects in the system link according to the system link information of the platform product and analyzing and obtaining various test data comprises:

[0015] According to the types of input data and output data in the system link information and the data types of upstream and downstream platform products, each of the functional objects is analyzed to obtain the position of each type of functional object in the system link;

[0016] Classifying each of the functional objects based on the position of each of the functional objects to obtain various types of test data;

[0017] The location includes at least one of the upstream, downstream, basic support, input data, and output data of the platform product.

[0018] In one embodiment, the step of dividing each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link includes:

[0019] Determine the association between the test data and the platform product, the business product on the platform, and the source of the test data according to the function item corresponding to each test data and the position in the system link;

[0020] If the test data is associated with both the platform product and the business product on the platform, and the source is not provided by or accessed from the platform and the business product, the test data is classified as public data;

[0021] If the test data is associated with the platform product and the source is provided by the platform product or accessed externally, the test data is classified as basic data;

[0022] If the test data is associated with a transaction of the platform product, the test data is classified as transaction data.

[0023] In one embodiment, the step of combining the attributes corresponding to the public data, the basic data, and the transaction data and the constituent factors corresponding to the attributes to obtain the data modeling results corresponding to the public data, the basic data, and the transaction data, respectively, includes:

[0024] Extracting attributes corresponding to various types of test data in the public data, and determining a plurality of constituent factors corresponding to each attribute;

[0025] According to the actual information in each test data in the public data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the public data;

[0026] Extracting attributes corresponding to various types of test data in the basic data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0027] According to the actual information in each test data in the basic data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the basic data;

[0028] Extracting attributes corresponding to various types of test data in the transaction data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0029] According to the actual information in each test data in the transaction data, each attribute of each test data and a constituent factor corresponding to each attribute are determined and combined to obtain a data modeling result of the transaction data.

[0030] In one embodiment, the public data includes at least household registration data;

[0031] The step of extracting attributes corresponding to various types of test data in the public data and determining a plurality of optional constituent factors corresponding to each attribute includes:

[0032] Extracting various attributes from the account data, each of the attributes including at least one of account type, account code, account bitmap and transaction restriction, account agreement, account type, foreign exchange account nature, currency, banknote and remittance mark, and counter withdrawal method;

[0033] According to the preset household registration data attribute rules, the constituent factors of each attribute are analyzed.

[0034] In one embodiment, the basic data includes at least parameter data;

[0035] The step of extracting attributes corresponding to various types of test data in the basic data and determining a plurality of optional constituent factors corresponding to each attribute comprises:

[0036] Extracting each attribute in the parameter data, each attribute at least including a foreign exchange settlement and sale attribute, a foreign exchange settlement and sale attribute description, a transaction code, and a transaction code description;

[0037] According to the preset parameter data attribute rules, the constituent factors of each attribute are analyzed and obtained.

[0038] In one embodiment, the transaction data includes at least public transaction data and personalized transaction data, wherein the public transaction data includes at least transaction currency data;

[0039] The step of extracting attributes corresponding to various types of test data in the transaction data and determining a plurality of optional constituent factors corresponding to each attribute comprises:

[0040] Extracting various attributes in the transaction currency data, each of the attributes at least including the transaction currency of foreign exchange settlement and sale, the currency code of foreign exchange settlement and sale, and the banknote and exchange mark;

[0041] According to the preset transaction currency attribute rules, the constituent factors of each attribute are analyzed.

[0042] The present application also provides a platform product test data analysis and modeling device, the platform product test data analysis and modeling device comprising:

[0043] A function object determination module, used to determine various types of function objects corresponding to multiple function items of the platform product based on the system architecture information of the platform product;

[0044] A test data determination module, used to determine the position of each functional object in the system link according to the system link information of the platform product, and analyze and obtain various test data;

[0045] A type classification module, used for classifying each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link;

[0046] The data modeling module is used to respectively combine the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes to obtain data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

[0047] The present application also provides an electronic device, which is a physical device, and includes: a memory, a processor, and a program of the platform product test data analysis and modeling method stored in the memory and executable on the processor. When the program of the platform product test data analysis and modeling method is executed by the processor, the steps of the platform product test data analysis and modeling method as described above can be implemented.

[0048] The present application also provides a computer-readable storage medium, on which is stored a program for implementing a platform product test data analysis and modeling method. When the program of the platform product test data analysis and modeling method is executed by a processor, the steps of the platform product test data analysis and modeling method as described above are implemented.

[0049] The present application also provides a computer program product, including a computer program, which implements the steps of the platform product test data analysis and modeling method as described above when executed by a processor.

[0050] The present application provides a platform product test data analysis modeling method, in which the various functional objects corresponding to the multiple functional items of the platform product are first determined based on the system architecture information of the platform product, and then the positions of the functional objects in the system link are determined according to the system link information of the platform product, and various test data are obtained by analysis, and then the test data are divided into public data, basic data and transaction data according to the positions of the functional items and the test data in the system link, and then the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes are respectively combined to obtain the data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include the multiple attributes corresponding to each data and the constituent factors of each attribute. The technical solution of the present application proposes a method for combing and analyzing the test data of the platform product based on the system architecture and full-link perspective of the platform product, generates the corresponding functional items, and classifies the test data by analyzing the positions of the test data, and divides them into three types: public data, basic data and transaction data, so as to realize the fast and efficient combing of the product test data. In this application, data modeling is performed separately for these three types of data based on the attributes and composition factors of the test data, which facilitates efficient and automated data generation, automated testing, and manual testing as needed when testing products on different platforms in the future, thereby improving the efficiency of acquiring and applying test data. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0053] Figure 1 This is a flow chart of the first embodiment of the product test data analysis and modeling method of the application platform;

[0054] Figure 2 This is a schematic diagram of the architecture of a product for public foreign exchange settlement and sale in the data analysis and modeling method for the product test of this application platform;

[0055] Figure 3 A hierarchical diagram of the public data, platform product basic data, and product multi-channel transaction data in the platform product test data analysis modeling method of this application;

[0056] Figure 4 A schematic diagram of the commonality of test data of the terminal functions of the common basic module and the transaction initiation module extracted by the test data analysis modeling method of the platform product of this application;

[0057] Figure 5 A schematic diagram of the commonality of test data for the terminal functions of the common basic module, transaction initiation module and post-transaction processing module extracted by the test data analysis modeling method of the platform product of this application;

[0058] Figure 6 This is a schematic diagram of the system link for the public foreign exchange settlement and sales product in the data analysis and modeling method for the product test of this application platform;

[0059] Figure 7 This is a schematic diagram of the structure of the product test data analysis and modeling device of the application platform;

[0060] Figure 8 This is a schematic diagram of the device structure of the hardware operating environment involved in the platform product test data analysis modeling method in the embodiment of the present application.

[0061] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0062] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0063] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0064] The execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, a server, etc., or an electronic device, a control device, etc. capable of realizing the above functions. The following takes a computer as an execution subject as an example to illustrate this embodiment and the following embodiments.

[0065] The present application embodiment provides a platform product test data analysis modeling method. In the first embodiment of the platform product test data analysis modeling method of the present application, refer to Figure 1 , the platform product test data analysis and modeling method includes:

[0066] Step S10, based on the system architecture information of the platform product, determining various types of functional objects corresponding to the multiple functional items of the platform product;

[0067] The platform product in the embodiment of the present application may be a multi-channel financial platform product. In order to sort out the data of the platform product, it is first necessary to use the system architecture information of the platform product to comprehensively examine the functional modules of the platform product. Among them, the system architecture information may be a system architecture diagram of the platform product, so as to analyze the functional scenarios involved in the platform product from the architecture diagram.

[0068] For example, a product architecture of a public foreign exchange settlement and sales platform is as follows: Figure 2As shown, customers and operators can initiate transactions or inquiries to the public foreign exchange sales platform through channels, which may include: counter, corporate online banking, corporate APP (application), OneNet, docking channel A, docking channel B, docking channel C, docking channel D, docking channel E, docking channel F, docking channel G, and also include docking channel H, docking channel I, docking channel J, and docking channel K of external platforms; the channel is connected to the bank's basic system through the exchange switching gateway; the bank's basic system connection includes the front end corresponding to the counter, the counter transaction application of the counter channel transaction, corporate online banking, corporate APP, OneNet, etc. Channel trading applications; platform products also include a variety of basic applications, including: exchange rate management, exchange rate platform, external exchange rate query, public module and basic module. The in-house basic system is also associated with the accounting middle office, public accounting, receipts, accounts, permissions, etc.; testers can configure the parameters of platform products through the configuration middle office and parameter management; obtain market information such as market mid-price through external market system A, external market system B, external market system C, etc.; platform products exchange data with external regulatory agencies through the exchange platform, including regulatory reporting reports, CBRC system (corresponding to Tables 1-3, Organizations 1-3 respectively) and foreign exchange declaration system (corresponding to foreign exchange systems 1-3).

[0069] Relying on the system architecture of the above-mentioned platform products, we sort out the functional items involved in the platform products, and then classify the functional objects of each of the above-mentioned functional items involved in the platform products (the functional objects are equivalent to the original data corresponding to each functional item), so as to complete the summary of the data based on the business function level.

[0070] Step S20, according to the system link information of the platform product, determine the position of each functional object in the system link, and analyze and obtain various test data;

[0071] Among them, the system link information of the platform product includes the full link data of the platform product at the system level, specifically including the input data, output data, data processing, etc. of each part in the architecture diagram. In the embodiment of the present application, by analyzing the position of the functional object in the full link, it is possible to determine what role the functional object plays in the platform product, its status and scope, so as to facilitate further classification and induction of the functional objects and obtain test data that can be used for product testing.

[0072] Step S30, dividing each test data into common data, basic data and transaction data according to each function item and the position of each test data in the system link;

[0073] After determining the various types of test data corresponding to each functional item and the position of each type of test data in the system link, the various types of test data can be further classified into three types: public data, basic data, and transaction data. Among them, the functional item reflects the specific role of the test data in the platform product, and the position in the system link reflects the relationship between the test data and the platform product. After determining the above information, the test data can be further summarized according to the relationship between the test data and the platform product.

[0074] Among them, public data refers to test data that is shared by other business products on the platform in addition to platform products. It is a universal type. Public data is related to each platform and business product, but it is not data provided by the platform and business products. For the platform, it belongs to the data of the lower-level product support. Basic data refers to the basic data of platform products. Various business products on the platform may also use it. Although it also belongs to the underlying support data, it has a stronger correlation with platform products than public data. It is data generated by the functions provided by platform products or data for external access to platform products. Transaction data refers to the transaction data of platform products. Compared with basic data, it pays more attention to the transaction itself and is the data generated during the transaction process in platform products.

[0075] When testing platform products, the above three types of data corresponding to the platform products are usually needed. When testing other business products on the same platform, the public data and basic data obtained above can also be reused to a certain extent without rebuilding the corresponding test data. When testers are testing platform products, they can use the above various types of data as needed, which can effectively improve the application efficiency of test data. Figure 3 As shown, the levels of public data, platform product basic data and product multi-channel transaction data are rising. The application scope of the data at the lower level is wider and more universal, while the application scope of the data at the upper level is narrower and more specific.

[0076] Step S40, respectively combining the attributes corresponding to the public data, basic data and transaction data and the constituent factors corresponding to the attributes to obtain data modeling results corresponding to the public data, basic data and transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

[0077] In the process of data modeling for types of data such as public data, basic data, and transaction data, it is necessary to analyze the corresponding attributes. Usually, one type of data includes multiple attributes, and there is only one constituent factor corresponding to each attribute of each data, but each attribute itself has multiple constituent factors to be selected. For the same type of data, the multiple attributes included are the same, and the constituent factors corresponding to each attribute can be different. Through the above-mentioned data modeling method, the test data of the platform product in the embodiment of the present application is composed of data major categories (one of public data, basic data, and transaction data), data minor categories (specific types), multiple attributes, and constituent factors corresponding to multiple attributes to form data modeling results. After the modeling is completed, the test data of the platform product can be stored in a relatively clear hierarchical structure, which is also convenient for efficiently obtaining test data according to the type hierarchy when the corresponding type of test data needs to be called.

[0078] Through the technical solution of this application, a test data analysis and combing strategy for multi-channel platform products can be determined, and a unified test data analysis modeling solution can be provided. These solutions can form clear and unified guidance specifications, facilitate promotion and implementation in various platform products, and improve the application efficiency of platform product test data. In addition, unified solutions and strategies are more scientific and reasonable, avoiding the influence of testers' subjective factors.

[0079] Furthermore, in a feasible embodiment, the step of determining various types of functional objects corresponding to the multiple functional items of the platform product respectively based on the system architecture information of the platform product includes:

[0080] Step S11, generating multi-level function items corresponding to the platform product according to the functions of the platform product represented by the system architecture information of the platform product, wherein the multi-level function items are respectively summarized according to basic functions and transaction functions;

[0081] First, it is necessary to sort out the functions involved in the platform product in the system architecture information, and generate corresponding multi-level function items based on the preset function item formulation principles. The function item formulation principle means that the platform's function items need to be summarized according to basic functions and transaction functions. For new platform products, the corresponding function items can be generated directly based on the function item formulation principles; for existing products, it is necessary to first evaluate whether the original function items meet the function item formulation principles. If not, they need to be re-formulated.

[0082] Multi-level function entries mean that the functions of platform products are graded according to actual needs. The functions of a module may also include multiple sub-functions. When sorting out the functions of platform products, it is necessary to analyze the functions of each level of the module step by step.

[0083] For example, a certain platform product includes two modules: basic functions and transaction functions, and each module includes multiple sub-modules. Each sub-module has different functions, and some functions have multiple sub-functions.

[0084] Step S12, obtaining corresponding multiple categories of functional objects by extracting the commonality of functional objects associated with each last-level functional item in the multi-level functional items.

[0085] Among the function items of the platform product, the final function items all have function objects associated with them, wherein the final function item refers to a function item that does not have a next-level function. For example, the function of a submodule is A, and function A has two subfunctions, subfunction a and subfunction b. Then subfunction a and subfunction b are both final function items, but function A is not a final function item. If function B of a submodule does not have a next-level subfunction, then function B is a final function item.

[0086] Although the final functional items are different, the data involved in each functional item has commonalities. Figure 4 As shown in the figure, for the platform product "Spot Foreign Exchange Settlement and Sale System", the three functional items in the public basic module, namely "Exchange Rate Management", "Discount Management" and "Spread Management", will all involve functional objects such as external market conditions, spreads (a type of configuration), exchange rates and discounts; the functional items such as "Foreign Exchange Settlement" and "Foreign Exchange Sale" in the transaction initiation module will all involve functional objects such as customers, accounts, work calendars (a type of configuration), parameters, currencies, exchange rates and discounts. Figure 5 As shown, the functional items such as "foreign exchange settlement and sale qualification management", "discount management", "spread management" in the public basic module all involve internal system data, and "exchange rate management" will involve functional objects such as external market data; "counter channels" and "corporate online banking" in the transaction initiation module involve functional objects such as channel data; the "clearing" function in the post-transaction processing module involves core system data, and the "declaration" function involves external declaration data.

[0087] After listing each terminal function item, removing duplicates and summarizing them, the commonalities of the functional objects involved in each terminal function item are extracted to obtain all types of functional objects involved in this platform product.

[0088] In a feasible embodiment, the system link information at least includes the types of test data corresponding to the input data and the output data respectively;

[0089] The step of determining the positions of the functional objects in the system link according to the system link information of the platform product and analyzing and obtaining various test data comprises:

[0090] Step S21, analyzing each functional object according to the types of input data and output data in the system link information and the data types of the upstream and downstream platform products, and obtaining the position of each type of functional object in the system link;

[0091] Step S22, classifying each functional object based on the position of each functional object to obtain various types of test data;

[0092] The location includes at least one of the upstream, downstream, basic support, input data, and output data of the platform product.

[0093] System link information (such as system architecture diagram) can be used to analyze the entire link data of platform products at the system level. Figure 6 The application at the bottom of the figure is the basic supporting application of the platform product, which contains both input data, such as household data and permission data, and output data, such as account data and receipt data after a successful transaction; data processing is performed within the bank's basic system; the applications on the left and above the figure belong to the upstream of the platform product, and the data contained are input data, such as parameter data, configuration data, exchange rate data, channel information data, etc.; the applications on the right side of the figure are the downstream of the platform product, and the data contained are output data, such as report submission data and notification information data.

[0094] After obtaining the position of each type of functional object in the system link, the test data corresponding to these functional objects can be further determined, and it can be determined whether each type of test data belongs to public data, basic data or transaction data.

[0095] Furthermore, the step of dividing each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link includes:

[0096] Step S31, determining the association between the test data and the platform product, the business product on the platform, and the source of the test data according to the function item corresponding to each test data and the position in the system link;

[0097] Because the functional items corresponding to the test data and their position in the system link can reflect the role and status of the test data in the platform product, they can be used to analyze the relationship between the test data and the platform products, business products on the platform, and the source of the test data, thereby providing a data basis for further classification into public data, basic data, and transaction data.

[0098] Exemplarily, based on a functional entry of test data, the role of such test data in the platform product can be determined, and the corresponding association relationship (associated or unassociated) with the platform product or business product can be determined. The position in the system link can also determine the source of the test data. For example, if the test data is output data, it means that it is generated and provided by the platform product. If it is input data, the source is other platforms or manual input.

[0099] Step S32: if the test data is associated with both the platform product and the business product on the platform, and the source is not provided or accessed by the platform and the business product, the test data is classified as public data;

[0100] Test data is associated with both platform products and business products on the platform. This means that in addition to platform products, this type of test data is also shared by other business products on the platform. It is universal and related to each platform and business product, but it is not data provided by the platform and business product. It is data supported by products at the lower level of the platform. Therefore, this type of test data can be classified as public data.

[0101] Step S33, if the test data is associated with the platform product and the source is provided by the platform product or accessed externally, the test data is classified as basic data;

[0102] The association of test data with platform products means that this type of test data is the basic data of platform products. Although other business products on the platform may also use it and it is also underlying support data, it has a stronger correlation with platform products than public data. This type of test data is data generated by the functions provided by platform products or data for external access to platform products. Therefore, this type of test data can be classified as basic data.

[0103] Step S34: if the test data is associated with a transaction of a platform product, the test data is classified as transaction data.

[0104] The transaction association between test data and platform products means that this type of test data is the transaction data of platform products. Compared with basic data, this type of test data is more closely related to the transaction itself, is exclusive to this platform product, and is generally less used by other business products. Therefore, this type of test data can be classified as transaction data.

[0105] It should be noted that the transaction data divided in the embodiment of the present application can also be called product multi-channel transaction data, and the basic data can be called platform product basic data. The application scope of the three types of test data, product multi-channel transaction data, platform product basic data, and public product, increases in sequence.

[0106] In a feasible embodiment, the step of combining the attributes corresponding to the public data, the basic data, and the transaction data and the constituent factors corresponding to the attributes to obtain the data modeling results corresponding to the public data, the basic data, and the transaction data, respectively, includes:

[0107] Step S41, extracting attributes corresponding to various types of test data in the public data, and determining a plurality of constituent factors corresponding to each attribute;

[0108] Step S42, according to the actual information in each test data in the public data, determine and combine each attribute of each test data and a component factor corresponding to each attribute, to obtain a data modeling result of the public data;

[0109] Step S43, extracting attributes corresponding to various types of test data in the basic data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0110] Step S44, according to the actual information in each test data in the basic data, determine and combine each attribute of each test data and a component factor corresponding to each attribute, to obtain a data modeling result of the basic data;

[0111] Step S45, extracting attributes corresponding to various types of test data in the transaction data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0112] Step S46, according to the actual information in each test data in the transaction data, determine and combine each attribute of each test data and a component factor corresponding to each attribute, so as to obtain a data modeling result of the transaction data.

[0113] It should be noted that, in the embodiment of the present application, steps S41 to S42, steps S43 to S44, and steps S45 to S46 are respectively used to perform data modeling on public data, basic data, and transaction data, and there is a parallel relationship between the three. That is to say, steps S41 to S42, steps S43 to S44, and steps S45 to S46 are independent of each other, and there is no fixed order relationship between the three. They can be executed in a random order or simultaneously.

[0114] In the process of data modeling, the main method is to extract the attributes of the test data and the constituent factors corresponding to the attributes. The data modeling result is composed of multiple data, each of which corresponds to multiple attributes contained in this type of data, and each attribute corresponds to an optional constituent factor used to characterize the specific value or type of this attribute, forming a three-layer structure modeling result of data-attribute-factor.

[0115] For example, common public data includes customer data, household registration data, work calendar, etc. The actual information in the test data includes the attributes of customer data and the corresponding components of each attribute. The attributes of customer data can include customer number, form, label type, effective date, expiration date, etc. For each customer data, each attribute can correspond to a component factor. For example, the label type can correspond to one of the following: rural enterprises, offshore customer acceptance categories, free trade customer identification, dormant customers, or strategic customer identification.

[0116] In the embodiment of the present application, the attributes and constituent factors of each piece of data in types of data such as public data, basic data, and transaction data are extracted and combined to complete the data modeling. The obtained data modeling results can clearly display the key information of various types of test data, so that testers can quickly obtain the corresponding test data according to their own needs during the subsequent platform product testing process. For the three types of test data for which the model has been established, efficient and automated number generation, automated testing, and manual testing are achieved based on the formulated test data number generation scheme and test scheme.

[0117] Further, in a feasible embodiment, the public data at least includes household registration data;

[0118] The step of extracting attributes corresponding to various types of test data in the public data and determining a plurality of optional constituent factors corresponding to each attribute includes:

[0119] Step S411, extracting various attributes in the account data, wherein the attributes include at least one of the account type, account code, account bitmap and transaction restriction, account agreement, account type, foreign exchange account nature, currency, banknote and remittance mark, and counter withdrawal method;

[0120] Step S412: Analyze and obtain the constituent factors of each attribute according to the preset household registration data attribute rules.

[0121] Common public data include customer data, household registration data, work calendar, etc. When analyzing public data, first extract the attributes attached to the data one by one, and then sort out the corresponding constituent factors for each extracted attribute. Since the test data is applied to platform products, the preset household registration data attribute rules can be analyzed from the business scenarios of platform products to determine the various constituent factors that may be involved in each attribute.

[0122] Taking household registration data as an example, based on the household registration data attribute rules corresponding to the platform products, the attributes of household registration data involved in the platform products can be sorted out, including household registration type, household registration code, household registration bitmap and transaction restrictions, household registration agreement, account type, nature of foreign exchange account, currency, banknote mark, counter withdrawal method, etc. Further, for each attribute, sort out its corresponding constituent factors. Exemplarily, for account type, its corresponding constituent factors may include: basic account, general account, special deposit account for budget unit, temporary deposit account, temporary deposit (capital verification account), and other special deposit accounts. By analogy, sort out all the constituent factors of each attribute of household registration data.

[0123] After the attributes and constituent factors of each type of data are sorted out, the actual values ​​of the corresponding attributes and constituent factors can be determined according to the actual information of each test data in the subsequent process, and finally the data modeling results of each test data in the public data can be constructed.

[0124] Further, in a feasible embodiment, the basic data at least includes parameter data;

[0125] The step of extracting attributes corresponding to various types of test data in the basic data and determining a plurality of optional constituent factors corresponding to each attribute comprises:

[0126] Step S431, extracting various attributes in the parameter data, wherein each attribute at least includes a foreign exchange settlement and sale attribute, a foreign exchange settlement and sale attribute description, a transaction code, and a transaction code description;

[0127] Step S432: Analyze and obtain the constituent factors of each attribute according to the preset parameter data attribute rules.

[0128] It should be noted that common platform basic data include parameter data, configuration data, etc.

[0129] Taking parameter data as an example, data modeling can be performed in the same way as public data. First, the attributes attached to the parameter data are sorted out, and then the various constituent factors of the attributes are sorted out.

[0130] Exemplarily, based on the parameter data attribute rules corresponding to the platform products, the attributes of the parameter attributes may include foreign exchange settlement and sale attributes (major categories), foreign exchange settlement and sale attributes (major categories) description, foreign exchange settlement and sale attributes (subdivisions), foreign exchange settlement and sale attributes (subdivisions) description, transaction codes, transaction code descriptions, etc. Further, the constituent factor corresponding to the foreign exchange settlement and sale attributes (major categories) may be a code, and the constituent factor of the foreign exchange settlement and sale attributes (major categories) description corresponding to the code in the foreign exchange settlement and sale attributes (major categories) description may be "current account settlement", and the constituent factors of the foreign exchange settlement and sale attributes (subdivisions) may include multiple codes, and the constituent factors of the foreign exchange settlement and sale attributes (subdivisions) description corresponding to each code may include "trade in goods", "transportation", "tourism", and "financial and insurance services".

[0131] In a feasible embodiment, the transaction data includes at least public transaction data and personalized transaction data, wherein the public transaction data includes at least transaction currency data;

[0132] The step of extracting attributes corresponding to various types of test data in the transaction data and determining a plurality of optional constituent factors corresponding to each attribute comprises:

[0133] Step S451, extracting various attributes in the transaction currency data, each attribute at least including the transaction currency of foreign exchange settlement and sale, the currency code of foreign exchange settlement and sale, and the banknote and exchange mark;

[0134] Step S452: Analyze and obtain the constituent factors of each attribute according to the preset transaction currency attribute rules.

[0135] It should be noted that in platform products, common transaction data include transaction currency, transaction exchange rate, transaction discount, etc.

[0136] Furthermore, product multi-channel transaction data can also be subdivided into product public transaction data and product personalized transaction data. For example, for foreign exchange settlement and sales platform products, transaction currency data belongs to the product's public transaction data, and all transactions are subject to the same transaction currency control regardless of the transaction type; while the transaction exchange rate is the product's personalized transaction data, and the transaction exchange rates of spot products and forward products are different.

[0137] Taking transaction currency data as an example, based on the transaction currency attribute rules of platform products, the modeling ideas of the above-mentioned public data and basic data are used to perform data modeling: first sort out the attributes attached to the transaction currency, and then sort out the constituent factors of the attributes. Exemplarily, the attributes of transaction currency data at least include the transaction currency of foreign exchange settlement and sale, the currency code of foreign exchange settlement and sale, and the banknote and exchange mark, wherein the constituent factors corresponding to the transaction currency of foreign exchange settlement and sale may include RMB, Hong Kong dollar, New Zealand dollar, Australian dollar, US dollar, Euro, Canadian dollar, British pound, Japanese yen, Singapore dollar, Swiss franc and other currencies, and the currency code of foreign exchange settlement and sale is in accordance with the international general coding rules. The constituent factors corresponding to the above various types of transaction currencies of foreign exchange settlement and sale are CNY, HKD, NZD, AUD, USD, EUR, CAD, GBP, JPY, SGD, CHF, and the constituent factors corresponding to the banknote and exchange representation may include: no banknote and exchange, cash and cash exchange.

[0138] By analogy, in the embodiment of the present application, after obtaining the attributes and constituent factors corresponding to the public data, basic data, and transaction data, respectively, the corresponding attributes and the unique constituent factors corresponding to each attribute are determined according to the actual information in each test data and combined to complete data modeling, so as to facilitate subsequent automated number generation, automated testing, and manual testing.

[0139] The present application also provides a platform product test data analysis modeling device, referring to Figure 7 , the platform product test data analysis and modeling device comprises:

[0140] A function object determination module 10 is used to determine various types of function objects corresponding to multiple function items of the platform product based on the system architecture information of the platform product;

[0141] The test data determination module 20 is used to determine the position of each functional object in the system link according to the system link information of the platform product, and analyze and obtain various test data;

[0142] A type classification module 30, for classifying each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link;

[0143] The data modeling module 40 is used to respectively combine the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes to obtain data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

[0144] In one embodiment, the functional object determination module 10 is further used for:

[0145] Generate multi-level function items corresponding to the platform product according to the functions of the platform product represented by the system architecture information of the platform product, wherein the multi-level function items are respectively summarized according to basic functions and transaction functions;

[0146] By extracting the commonality of the functional objects associated with each last-level functional item in the multi-level functional items, the corresponding multi-category functional objects are obtained.

[0147] In one embodiment, the test data determination module 20 is further configured to:

[0148] According to the types of input data and output data in the system link information and the data types of upstream and downstream platform products, each of the functional objects is analyzed to obtain the position of each type of functional object in the system link;

[0149] Classifying each of the functional objects based on the position of each of the functional objects to obtain various types of test data;

[0150] The location includes at least one of the upstream, downstream, basic support, input data, and output data of the platform product.

[0151] In one embodiment, the type classification module 30 is further used for:

[0152] Determine the association between the test data and the platform product, the business product on the platform, and the source of the test data according to the function item corresponding to each test data and the position in the system link;

[0153] If the test data is associated with both the platform product and the business product on the platform, and the source is not provided by or accessed from the platform and the business product, the test data is classified as public data;

[0154] If the test data is associated with the platform product and the source is provided by the platform product or accessed externally, the test data is classified as basic data;

[0155] If the test data is associated with a transaction of the platform product, the test data is classified as transaction data.

[0156] In one embodiment, the data modeling module 40 is further configured to:

[0157] Extracting attributes corresponding to various types of test data in the public data, and determining a plurality of constituent factors corresponding to each attribute;

[0158] According to the actual information in each test data in the public data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the public data;

[0159] Extracting attributes corresponding to various types of test data in the basic data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0160] According to the actual information in each test data in the basic data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the basic data;

[0161] Extracting attributes corresponding to various types of test data in the transaction data, and determining a plurality of optional constituent factors corresponding to each attribute;

[0162] According to the actual information in each test data in the transaction data, each attribute of each test data and a constituent factor corresponding to each attribute are determined and combined to obtain a data modeling result of the transaction data.

[0163] In one embodiment, the public data at least includes household registration data, and the data modeling module 40 is further used to:

[0164] Extracting various attributes from the account data, each of the attributes including at least one of account type, account code, account bitmap and transaction restriction, account agreement, account type, foreign exchange account nature, currency, banknote and remittance mark, and counter withdrawal method;

[0165] According to the preset household registration data attribute rules, the constituent factors of each attribute are analyzed.

[0166] In one embodiment, the basic data at least includes parameter data, and the data modeling module 40 is further used to:

[0167] Extracting each attribute in the parameter data, each attribute at least including a foreign exchange settlement and sale attribute, a foreign exchange settlement and sale attribute description, a transaction code, and a transaction code description;

[0168] According to the preset parameter data attribute rules, the constituent factors of each attribute are analyzed and obtained.

[0169] In one embodiment, the transaction data includes at least public transaction data and personalized transaction data, wherein the public transaction data includes at least transaction currency data, and the data modeling module 40 is further used to:

[0170] Extracting various attributes in the transaction currency data, each of the attributes at least including the transaction currency of foreign exchange settlement and sale, the currency code of foreign exchange settlement and sale, and the banknote and exchange mark;

[0171] According to the preset transaction currency attribute rules, the constituent factors of each attribute are analyzed.

[0172] The platform product test data analysis and modeling device provided by the present application adopts the platform product test data analysis and modeling method in the above-mentioned embodiment, which solves the technical problem of the poor acquisition efficiency and application efficiency of the existing platform product test data. Compared with the prior art, the beneficial effects of the platform product test data analysis and modeling device provided in the embodiment of the present application are the same as the beneficial effects of the platform product test data analysis and modeling method provided in the above-mentioned embodiment 1, and the other technical features in the platform product test data analysis and modeling device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0173] An embodiment of the present application also provides an electronic device, which includes: at least one processor; and a memory communicatively linked to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the platform product test data analysis modeling method in the above-mentioned embodiment one.

[0174] Reference below Figure 8 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable media players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0175] like Figure 8 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 (ROM) or a program loaded from a storage device 1003 to a random access memory 1004 (RAM). Various programs and data required for the operation of the electronic device are also stored in RAM 1004. The processing device 1004, ROM 1002, and RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also linked to the bus 1005.

[0176] Typically, the following systems can be linked to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an electronic device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0177] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0178] The electronic device provided by the present application adopts the platform product test data analysis modeling method in the above embodiment, which solves the technical problem of the poor acquisition efficiency and application efficiency of the existing platform product test data. Compared with the prior art, the beneficial effects of the electronic device provided by the embodiment of the present application are the same as the beneficial effects of the platform product test data analysis modeling method provided by the above embodiment 1, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0179] It should be understood that the various parts of the present disclosure can be implemented with hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0180] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0181] This embodiment also provides a computer-readable storage medium having computer-readable program instructions stored thereon, and the computer-readable program instructions are used to execute the method for platform product test data analysis and modeling in the above-mentioned embodiment one.

[0182] The computer-readable storage medium provided in the embodiment of the present application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical link with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, ErasableProgrammableRead-OnlyMemoryorFlash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a system or a device or used in combination with it. The program code contained on the computer-readable storage medium can be transmitted with any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0183] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0184] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by an electronic device, the electronic device: determines the various types of functional objects corresponding to the multiple functional items of the platform product based on the system architecture information of the platform product; determines the positions of each of the functional objects in the system link according to the system link information of the platform product, and obtains various types of test data through analysis; divides each of the test data into public data, basic data and transaction data according to the positions of each of the functional items and each of the test data in the system link; and respectively combines the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes to obtain the data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each piece of data and the constituent factors of each attribute.

[0185] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be linked to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be linked to an external computer (e.g., via the Internet using an Internet service provider).

[0186] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0187] The modules involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0188] The computer-readable storage medium provided by the present application stores computer-readable program instructions for executing the above-mentioned platform product test data analysis and modeling method, which solves the technical problem of poor acquisition efficiency and application efficiency of existing platform product test data. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the embodiment of the present application are the same as the beneficial effects of the platform product test data analysis and modeling method provided in the above-mentioned embodiment, and will not be repeated here.

[0189] The present application also provides a computer program product, including a computer program, which implements the steps of the platform product test data analysis and modeling method as described above when executed by a processor.

[0190] The computer program product provided by the present application solves the technical problem of the poor acquisition efficiency and application efficiency of the existing platform product test data. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the platform product test data analysis modeling method provided by the above embodiment, which will not be repeated here.

[0191] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A platform product test data analysis modeling method, characterized in that: The platform product test data analysis and modeling method comprises: Based on the system architecture information of the platform product, determine various types of functional objects corresponding to the multiple functional items of the platform product; According to the system link information of the platform product, determine the position of each functional object in the system link, and analyze and obtain various test data; According to the positions of the function items and the test data in the system link, the test data are divided into common data, basic data and transaction data; The attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes are respectively combined to obtain data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

2. The platform product test data analysis and modeling method according to claim 1, characterized in that: The step of determining various types of functional objects corresponding to the multiple functional items of the platform product respectively based on the system architecture information of the platform product includes: Generate multi-level function items corresponding to the platform product according to the functions of the platform product represented by the system architecture information of the platform product, wherein the multi-level function items are respectively summarized according to basic functions and transaction functions; By extracting the commonality of the functional objects associated with each last-level functional item in the multi-level functional items, the corresponding multi-category functional objects are obtained.

3. The platform product test data analysis and modeling method according to claim 1, characterized in that: The system link information at least includes the types of test data corresponding to the input data and the output data respectively; The step of determining the positions of the functional objects in the system link according to the system link information of the platform product and analyzing and obtaining various test data comprises: According to the types of input data and output data in the system link information and the data types of upstream and downstream platform products, each of the functional objects is analyzed to obtain the position of each type of functional object in the system link; Classifying each of the functional objects based on the position of each of the functional objects to obtain various types of test data; The location includes at least one of the upstream, downstream, basic support, input data, and output data of the platform product.

4. The platform product test data analysis and modeling method according to claim 1, characterized in that: The step of dividing each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link comprises: Determine the association between the test data and the platform product, the business product on the platform, and the source of the test data according to the function item corresponding to each test data and the position in the system link; If the test data is associated with both the platform product and the business product on the platform, and the source is not provided by or accessed from the platform and the business product, the test data is classified as public data; If the test data is associated with the platform product and the source is provided by the platform product or accessed externally, the test data is classified as basic data; If the test data is associated with a transaction of the platform product, the test data is classified as transaction data.

5. The platform product test data analysis and modeling method according to claim 1, characterized in that: The step of combining the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes to obtain the data modeling results corresponding to the public data, the basic data and the transaction data respectively includes: Extracting attributes corresponding to various types of test data in the public data, and determining a plurality of constituent factors corresponding to each attribute; According to the actual information in each test data in the public data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the public data; Extracting attributes corresponding to various types of test data in the basic data, and determining a plurality of optional constituent factors corresponding to each attribute; According to the actual information in each test data in the basic data, determine and combine each attribute of each test data and a constituent factor corresponding to each attribute, so as to obtain a data modeling result of the basic data; Extracting attributes corresponding to various types of test data in the transaction data, and determining a plurality of optional constituent factors corresponding to each attribute; According to the actual information in each test data in the transaction data, each attribute of each test data and a constituent factor corresponding to each attribute are determined and combined to obtain a data modeling result of the transaction data.

6. The platform product test data analysis and modeling method according to claim 5, characterized in that: The public data at least includes household registration data; The step of extracting attributes corresponding to various types of test data in the public data and determining a plurality of optional constituent factors corresponding to each attribute includes: Extracting various attributes from the account data, each of the attributes including at least one of account type, account code, account bitmap and transaction restriction, account agreement, account type, foreign exchange account nature, currency, banknote and remittance mark, and counter withdrawal method; According to the preset household registration data attribute rules, the constituent factors of each attribute are analyzed.

7. The platform product test data analysis and modeling method according to claim 5, characterized in that: The basic data at least includes parameter data; The step of extracting attributes corresponding to various types of test data in the basic data and determining a plurality of optional constituent factors corresponding to each attribute comprises: Extracting each attribute in the parameter data, each attribute at least including a foreign exchange settlement and sale attribute, a foreign exchange settlement and sale attribute description, a transaction code, and a transaction code description; According to the preset parameter data attribute rules, the constituent factors of each attribute are analyzed and obtained.

8. The platform product test data analysis and modeling method according to claim 5, characterized in that: The transaction data at least includes public transaction data and personalized transaction data, wherein the public transaction data at least includes transaction currency data; The step of extracting attributes corresponding to various types of test data in the transaction data and determining a plurality of optional constituent factors corresponding to each attribute comprises: Extracting various attributes in the transaction currency data, each of the attributes at least including the transaction currency of foreign exchange settlement and sale, the currency code of foreign exchange settlement and sale, and the banknote and exchange mark; According to the preset transaction currency attribute rules, the constituent factors of each attribute are analyzed.

9. A platform product test data analysis modeling device, characterized in that: The platform product test data analysis and modeling device comprises: A function object determination module, used to determine various types of function objects corresponding to multiple function items of the platform product based on the system architecture information of the platform product; A test data determination module, used to determine the position of each functional object in the system link according to the system link information of the platform product, and analyze and obtain various test data; A type classification module, used for classifying each of the test data into common data, basic data and transaction data according to each of the function items and the position of each of the test data in the system link; The data modeling module is used to respectively combine the attributes corresponding to the public data, the basic data and the transaction data and the constituent factors corresponding to the attributes to obtain data modeling results corresponding to the public data, the basic data and the transaction data, wherein the data modeling results at least include multiple attributes corresponding to each data and the constituent factors of each attribute.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively linked to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the platform product test data analysis and modeling method described in any one of claims 1 to 8.

11. A readable storage medium, characterized in that: The readable storage medium is a computer-readable storage medium, on which is stored a program for implementing the platform product test data analysis and modeling method. The program for implementing the platform product test data analysis and modeling method is executed by a processor to implement the steps of the platform product test data analysis and modeling method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the platform product test data analysis and modeling method according to any one of claims 1 to 8 are implemented.

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