Business system testing method, apparatus, device, medium, and product

Abstract

The application relates to a business system test method, device, equipment, medium and product. The method comprises the following steps: determining at least one target transaction information meeting a business screening condition from historical transaction information contained in a business system; determining key features of the target transaction information; constructing test sample data according to the key features; and performing a business operation based on the test sample data to obtain a target test result of the business system. The method can improve the accuracy of business system testing.

Description

Technical Field

[0001] This application relates to the field of system testing technology, and in particular to a business system testing method, apparatus, equipment, medium, and product. Background Technology

[0002] With the continuous development of business system technology, system testing has become an important means to ensure the accuracy of accounting data and the stability of business system operation. Traditional testing techniques usually involve manually constructing test data and building various test scenarios to complete functional testing.

[0003] However, the traditional method of manually constructing test data is prone to problems such as data errors and incomplete data samples, which leads to low test accuracy of business systems. Summary of the Invention

[0004] Therefore, it is necessary to provide a business system testing method, apparatus, equipment, medium, and product that can improve the accuracy of business system testing in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a business system testing method, including:

[0006] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0007] Identify the key characteristics that link the various target transaction information;

[0008] Based on key features, construct test sample data;

[0009] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0010] In one embodiment, key features that link the various target transaction information are determined, including:

[0011] Information is extracted from each target transaction to obtain the corresponding loan data for each target transaction.

[0012] By performing distribution statistics on the data from each loan receipt, key characteristics of the interrelationships among the target transaction information are obtained.

[0013] In one embodiment, the distribution statistics of each loan receipt are performed to obtain key features that correlate the target transaction information, including:

[0014] Retrieve pre-defined key feature fields;

[0015] Feature extraction is performed on key feature fields in each loan data to obtain key features that are related to each target transaction information.

[0016] In one embodiment, the business filtering criteria include a first filtering criterion based on the business operation type and a second filtering criterion based on the business status.

[0017] From the historical transaction information contained in the business system, identify at least one target transaction that meets the business screening criteria, including:

[0018] From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0019] From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria.

[0020] In one embodiment, based on test sample data, business operations are performed to obtain the target test results of the business system, including:

[0021] For the test sample data, collect all field information of the database table associated with the test sample data as initial test information;

[0022] Business operations are performed based on test sample data, and all field information of the database table associated with the test sample data after the business operations are performed is collected as target test information.

[0023] Based on the initial test information and the target test information, determine the target test result.

[0024] In one embodiment, determining the target test result based on initial test information and target test information includes:

[0025] Determine the test differences between the initial test information and the target test information;

[0026] Based on the test discrepancy information, determine the target test results for the business system.

[0027] Secondly, this application also provides a business system testing apparatus, comprising:

[0028] The determination module is used to determine at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system.

[0029] The determination module is also used to determine the key features that relate to the various target transaction information;

[0030] The building module is used to construct test sample data based on key features;

[0031] The testing module is used to perform business operations based on test sample data to obtain the target test results of the business system.

[0032] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0033] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0034] Identify the key characteristics that link the various target transaction information;

[0035] Based on key features, construct test sample data;

[0036] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0037] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0038] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0039] Identify the key characteristics that link the various target transaction information;

[0040] Based on key features, construct test sample data;

[0041] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0042] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0043] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0044] Identify the key characteristics that link the various target transaction information;

[0045] Based on key features, construct test sample data;

[0046] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0047] The aforementioned business system testing methods, devices, equipment, media, and products mitigate data errors caused by manual data creation by filtering target transaction information that meets business screening criteria from the historical transaction information of the business system. By identifying relevant key features based on the target transaction information and constructing test sample data, the accuracy of the test samples is ensured to be completely aligned with the business logic, thus compensating for the incomplete data samples caused by manual data creation. Finally, by executing business operations based on the test sample data and obtaining test results, the accuracy of business system testing is effectively improved. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is an application environment diagram of a business system testing method in one embodiment;

[0050] Figure 2 This is a flowchart illustrating a business system testing method in one embodiment;

[0051] Figure 3 This is a flowchart illustrating the business system testing method in yet another embodiment;

[0052] Figure 4 This is a schematic diagram of the forward business operation process of a business system testing method in one embodiment;

[0053] Figure 5 This is a schematic diagram illustrating the feature statistics of a business system testing method in one embodiment;

[0054] Figure 6 This is a schematic diagram of the business and data change chain of a business system testing method in one embodiment;

[0055] Figure 7 This is a schematic diagram of the business rule setting process for a business system testing method in one embodiment;

[0056] Figure 8 This is a structural block diagram of a business system testing device in one embodiment;

[0057] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0059] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0060] The business system testing method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Terminal 102 sends a business system test request to server 104. Server 104 receives the business system test request, executes the business system test method, and sends the target test results of the business system back to terminal 102. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0061] In one exemplary embodiment, such as Figure 2 As shown, a business system testing method is provided, which is applied to... Figure 1 Taking the server in the example of this, the explanation includes:

[0062] Step 202: Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system.

[0063] The business system can be a business processing system that carries out core financial operations such as loan disbursement, repayment, post-loan management, batch interest calculation, and loan status migration, such as a financial accounting system; historical transaction information can be historical transaction records stored in the operation log table of the business system, including data such as business operations, batch processing execution records, transaction numbers, unique loan identifiers, operation status, and operation type; business filtering conditions can be pre-set conditions for filtering transaction records, such as filtering transaction records of the same type as the business operation to be tested (such as repayment operation); target transaction information can be transaction records that match the business to be tested and filtered from historical transaction records.

[0064] Optionally, first determine the business filtering conditions corresponding to the business operation to be tested, then retrieve the full historical transaction records from the business system's operation record table, and filter the retrieved full historical transaction records according to the business filtering conditions to obtain the target transaction information.

[0065] Step 204: Determine the key characteristics that link the various target transaction information.

[0066] Among them, key features can be common business attributes of the loan receipts that are hit by business operations in the business system, including but not limited to the loan receipt status (such as normal / overdue / written off), amount range, repayment method, post-loan label and overdue days, etc.

[0067] Optionally, the unique identifier of the loan receipt is first extracted from each target transaction information. Then, the corresponding complete loan receipt information is obtained by reverse association through the unique identifier of the loan receipt. Finally, multi-dimensional statistical analysis of key fields is performed on this batch of associated loan receipt information to extract the common key features of all target transaction corresponding loan receipts, that is, the key features of the mutual association of each target transaction information.

[0068] Step 206: Construct test sample data based on key features.

[0069] The test sample data can be generated in the test environment based on key features.

[0070] Optionally, test data can be generated according to the statistical proportion of key features (such as 50% normal loan receipts and 50% overdue loan receipts); test data can also be generated specifically for a key feature (such as only overdue status and interest-only repayment method); multiple key features such as loan status, term range and business tags can be combined to generate test data for composite scenarios; in addition to the above methods, other methods can be used to construct test data, and this embodiment does not limit this.

[0071] Step 208: Based on the test sample data, perform business operations to obtain the target test results of the business system.

[0072] Among them, business operations can be the business operations to be tested in the business system, including real-time business operations and batch business operations; real-time business operations can include various online and offline interface calls, such as loan disbursement, repayment, and post-loan management, and real-time business operations can directly respond to real-time instructions from users or business personnel; batch business operations can be batch jobs automatically executed by the business system through scheduled tasks, such as interest accrual, loan status migration, and batch deduction, and batch business operations usually run at night or in specific time windows, affecting all outstanding loan documents; the target test result can be the final conclusion on whether the data changes after the execution of the business operation comply with the accounting rules, including results such as test passed and test failed.

[0073] Optionally, a snapshot of all database field information is generated before the test sample data collection operation, and then the business operation to be tested (or batch processing operation) is performed on the batch of data in the business system. After the operation is completed, a snapshot of the same batch of data is collected after the operation, and the differences between the snapshots before and after are compared. This verifies whether the data changes after the business operation are executed comply with the accounting rules, so as to obtain the target test results of the business system.

[0074] In the above-mentioned business system testing method, the problem of data errors caused by manual data creation is alleviated by screening target transaction information that meets the business screening conditions from the historical transaction information of the business system; the test sample data is constructed based on the target transaction information to determine the associated key features, which can ensure that the test sample is completely consistent with the business logic and make up for the defect of incomplete data sample caused by manual data creation; finally, the business operation is executed based on the test sample data and the test results are obtained, which effectively improves the accuracy of business system testing.

[0075] In one exemplary embodiment, such as Figure 3 As shown, the key features that determine the interrelationships among the various target transaction information include:

[0076] Step 302: Extract information from each target transaction to obtain the corresponding loan data for each target transaction.

[0077] Among them, the loan receipt data can be complete loan receipt information corresponding to the target transaction information in the business system, including business attribute data such as loan receipt status, repayment method, loan period, post-loan status, interest subsidy mark and guarantee method.

[0078] Optionally, a unique identifier for the loan receipt can be extracted from each target transaction. Using the unique identifier as the basis for association, a matching query can be performed in the loan receipt database of the business system to obtain the complete loan receipt information and business attribute data corresponding to the identifier, thus obtaining the loan receipt data corresponding to each target transaction.

[0079] Step 304: Perform distribution statistics on each loan data to obtain the key features of the interrelationship between the target transaction information.

[0080] Optionally, first, clarify the statistical dimensions of the loan data (such as loan status, repayment method, and installment interval). Then, for all loan data related to the target transaction information, conduct frequency statistics and proportion analysis according to each dimension to obtain the distribution of loan status (such as normal, overdue, off-balance sheet, etc.), repayment method composition (such as equal principal and interest, interest-only payment followed by principal, etc.), installment interval (such as the 1st installment, the 3rd to 6th installments, etc.), post-loan status (such as normal watch, substandard, doubtful, etc.) and other business tags (such as interest subsidy mark, guarantee method, etc.), which are the key features that are related to each target transaction information.

[0081] In this embodiment, by extracting information from the target transaction information to obtain the corresponding loan receipt data, the accurate association and matching of transaction information and loan receipt data is achieved. By conducting distribution statistics on the loan receipt data to extract key features, the common attributes of the target transaction-related loan receipts can be determined based on real business data, ensuring that the obtained key features conform to the real business screening logic and distribution rules.

[0082] In an exemplary embodiment, the distribution statistics of each loan receipt data are performed to obtain the key features that are related to each target transaction information, including: obtaining pre-set key feature fields; extracting features from the key feature fields in each loan receipt data to obtain the key features that are related to each target transaction information.

[0083] Among them, key feature fields can be business attribute fields used to determine whether the loan agreement is hit by the business operation, including fields such as loan agreement status, repayment method, loan period range, post-loan status, interest subsidy flag, and guarantee method.

[0084] Optionally, pre-set fields such as loan status, repayment method, loan period, post-loan status, interest subsidy mark, and guarantee method are obtained. Then, for each loan data, corresponding feature information is extracted only from the preset fields. Finally, the extraction results of all loan data are summarized to determine the common key features of the loan data associated with the target transaction information.

[0085] Optionally, the business operations or batch processing in this embodiment are performed on loan receipts or on customers. This embodiment uses loan receipt processing as an example to illustrate the forward business processing flow. Figure 4As shown, the relationship between customers and IOUs is either one-to-many or one-to-one. A business operation or batch processing will filter which IOUs to operate on based on their status, amount, tags, and other characteristics. After the operation is completed, the operation status will be recorded as "completed" and written to the operation record table. Based on this operation, the operation flow can be traced back to obtain the characteristics of the IOUs and customer information, thereby determining the features of the IOUs and customer information corresponding to the operation.

[0086] In complex financial accounting systems, every business operation (such as repayment or account adjustment) or batch operation (such as batch interest calculation) is not an "indiscriminate attack," but rather is strictly filtered based on certain characteristic dimensions of the loan agreement or customer. These characteristics may include: loan agreement status (normal / overdue / written off), amount range, repayment method, post-loan tags, overdue days, etc. Therefore, to verify the correctness of the logic, the test data must first be "aligned" with the characteristic distribution in real business scenarios.

[0087] Optionally, this embodiment starts with tracing online transaction records to form a closed loop of "reverse feature extraction + forward data construction." For example... Figure 5 As shown, taking a typical forward operation process as an example, this illustrates how to perform reverse feature extraction and forward data construction. Specifically, the business system filters out a batch of loan receipts that meet the conditions according to business rules, executes operations (such as batch deductions), records the operation status after completion, and writes it to the operation record table.

[0088] This embodiment can trace the operation flow to uncover common characteristics of the processed loan documents: Locating successful transactions: Filtering out transactions with a "successful" status in the current business operation or batch processing from the operation record table (i.e., target transaction information); Associating loan document information: Based on the unique identifier of the loan document in the transaction flow, reversibly linking it to the corresponding complete loan document information (i.e., loan document data); Feature statistical analysis: Performing multi-dimensional feature statistics on the key fields of these loan documents, such as: loan document status distribution (normal, overdue, off-balance sheet, etc.), repayment method composition (equal principal and interest, interest-only, etc.), loan period range (1st period, 3-6th periods, etc.), post-loan status (normal watch list, substandard, doubtful, etc.), and other business tags (interest subsidy mark, guarantee method, etc.). Through this reverse process, it is possible to accurately extract "what kind of loan documents will be hit in this operation." After obtaining these features (i.e., key features), data (i.e., test sample data) can be constructed as needed in the test environment, rather than blindly generating random data. This ensures that each batch of test data has a real business basis, thus making the test scenario more realistic.

[0089] In this embodiment, by using pre-defined key feature fields, the dimensions and scope of feature extraction can be standardized, the interference of invalid fields can be mitigated, and the efficiency and targeting of feature extraction can be improved. Based on the preset fields, targeted feature extraction of the loan data can accurately match the business screening logic of the business system, ensuring that the extracted key features are consistent with the real business attributes.

[0090] In an exemplary embodiment, determining at least one target transaction information that meets business screening criteria from historical transaction information contained in the business system includes: determining at least one first transaction information whose business operation type meets a first screening criterion from historical transaction information contained in the business system; and determining at least one target transaction information whose business status meets a second screening criterion from each first transaction information.

[0091] The business filtering criteria include a first filtering criterion based on the type of business operation and a second filtering criterion based on the business status.

[0092] The first screening criterion can be the business operation type of the business system to be tested, including real-time business operations (such as loan disbursement, repayment, post-loan management and post-loan adjustment) and batch processing (such as batch interest calculation, loan status migration, interest accrual and batch deduction). The first transaction information can be the transaction flow information that matches the business operation type initially screened from historical transaction information with the first screening criterion. The second screening criterion can be the execution result status of the transaction, such as the success status.

[0093] Optionally, based on the first filtering condition, the first transaction information matching the operation type is firstly filtered from the historical transaction information of the business system. For example, if the first filtering condition is to filter out transaction flow of repayment type, the transaction information of repayment type is filtered from the historical transaction information as the first transaction information. Then, the first transaction information is further filtered based on the second filtering condition. For example, the transaction information with the business status of success is filtered from the first transaction information as the target transaction information, so that at least one target transaction information can be obtained.

[0094] In this embodiment, by breaking down the filtering conditions into two layers of rules—operation type and execution status—for progressive filtering, invalid transaction data with mismatched operation types or execution failures can be accurately filtered, thereby improving the accuracy of target transaction information filtering.

[0095] It's worth noting that the technical complexity of business systems (such as accounting systems) primarily relies on two core dimensions: the dynamic evolution of business states and the temporal superposition of business operations. On one hand, the lifecycle of a loan agreement is highly dynamic; loan entities can correspond to various business states such as normal, overdue, and off-balance-sheet interest-bearing. Different states correspond to different interest calculation rules, penalty interest calculation logic, and reserve provision strategies. This requires the business system to be able to identify loan status in real time and accurately trigger matching business processing logic. On the other hand, business systems support arbitrary combinations and temporal superposition of multiple business operations. Typical scenarios include sequentially performing partial repayments, post-loan adjustments, and batch deductions on the same loan agreement. The order and interaction logic of multiple operations can easily trigger complex transitions in the system's state machine, leading to an exponential increase in code logic branches.

[0096] The business and data change link diagram provided in this embodiment is as follows: Figure 6 As shown, the upper-layer link represents the business change dimension, covering business attributes and constraints such as customer and loan agreement relationship, loan agreement lifecycle status, time node, and operation restrictions. The input is the loan agreement and customer data to be operated on, and the output is the loan agreement and customer data after the operation. The lower-layer link represents the data change dimension, corresponding to the changes in core data such as loan agreement information, customer information, and repayment information in the database caused by business operations.

[0097] Given these dual characteristics, testing the business system faces significant technical challenges. Testing must not only verify the basic correctness of individual business functions but also cover data consistency and final result accuracy under complex scenarios such as concurrent execution of multiple operations, interleaved operation sequences, and mixed batch processing and online transactions. To this end, test design needs to introduce a combined coverage strategy, performing orthogonal analysis on core elements such as loan status, business operation type, and time dimension to construct a scenario matrix that closely reflects the real-world business flow. Simultaneously, it is crucial to focus on concurrency conflicts between batch operations and online transactions. For example, when real-time repayment occurs during batch interest calculation, can the system use locking mechanisms or optimistic locking mechanisms to avoid interest calculation deviations? Furthermore, given that accounting data is directly linked to financial security, regression testing of core business scenarios must achieve full automated coverage to ensure that the existing business logic loop is not disrupted during code iteration.

[0098] The core essence of business system testing is to ensure the correctness of core financial business and the robustness of the system under various complex operating conditions by taking the massive set of business state machines and complex concurrent operation logic of the business system as the core, and through systematic and combined scenario coverage and full-dimensional logic verification. This also puts forward higher requirements for the accuracy of test data, the standardization of test process and the accuracy of test results.

[0099] In an exemplary embodiment, based on test sample data, business operations are performed to obtain the target test result of the business system, including: collecting all field information of the database table associated with the test sample data as initial test information; performing business operations based on the test sample data and collecting all field information of the database table associated with the test sample data after the business operations are performed as target test information; and determining the target test result based on the initial test information and the target test information.

[0100] The initial test information can be the full field information of the database table associated with the test sample data collected before the business operation is executed, i.e., a snapshot before the operation; the target test information can be the full field information of the database table associated with the same test sample data collected after the business operation is executed, i.e., a snapshot after the operation.

[0101] Optionally, for the test sample data, before executing the business operation, collect all field information of its associated database table as initial test information; then, based on the test sample data, execute the business operation to be tested in the business system, and after the operation is completed, collect all field information of the same associated database table as target test information; finally, compare the differences between the initial test information and the target test information across all fields to determine the target test result.

[0102] In this embodiment, by collecting all field information of the related database tables before and after the operation to form before-and-after comparison data, the entire state of data change can be completely preserved; the test result is determined based on the difference comparison of the before and after information, realizing the full automation of data verification and improving verification efficiency and accuracy.

[0103] In an exemplary embodiment, determining the target test result based on initial test information and target test information includes: determining test difference information between the initial test information and the target test information; and determining the target test result of the business system based on the test difference information.

[0104] The test difference information includes the set of fields whose values ​​have changed, the field values ​​before the change, and the field values ​​after the change.

[0105] Optionally, the initial test information and the target test information are compared field by field to extract the content where the field values ​​have changed, forming test difference information. Then, non-business verification fields such as modification time, serial number, and version number automatically generated by the system are filtered by a dynamic whitelist, retaining only the differences related to core business. Finally, the filtered test difference information is used to determine whether it meets the pre-set business rules, so as to determine the target test result of the business system.

[0106] Optionally, if there are no pre-defined business rules, such as Figure 7As shown, setting business rules involves the following four steps:

[0107] Data snapshot: For the constructed test data (i.e. a batch of IOUs with specific characteristics), before executing business operations, collect all field information of all relevant database tables as a "pre-operation snapshot", i.e., the initial test data.

[0108] Execute operation: Perform the business operation to be tested (such as post-loan processing) or batch job on this set of data.

[0109] Post-operation snapshot: After the operation is completed, the database table information of the same batch of IOUs is collected again as the "post-operation snapshot", that is, the target test data.

[0110] Difference Analysis: A full-field comparison is performed between the two snapshots to identify all fields that have changed (i.e., test difference information). At this point, a dynamic whitelist mechanism is introduced: fields that are naturally generated during system operation and do not belong to business logic verification points (such as creation time, last modification time, serial number, and version number) are pre-filtered out. The remaining changed fields are the "verification points" that business operations should truly affect. Having obtained these verification points and their values ​​before and after the changes, a verification assertion statement is automatically generated, for example: "The loan status changes from 'normal' to 'overdue,' the overdue days increase by 1, and the accrued penalty interest amount increases by 1 yuan." Assembling these assertions forms a fully automated verification script (i.e., business rule). Furthermore, if the data characteristics (i.e., key characteristics) remain unchanged, the script can be executed repeatedly, and each regression test can complete the work that originally required manual item-by-item verification at machine speed.

[0111] In this embodiment, by first extracting test difference information and then determining the test results, the redundancy of full data verification is reduced, the changes in key business data are accurately identified, the automation and accuracy of data verification are achieved, and the efficiency of business system testing is improved.

[0112] To more comprehensively demonstrate this solution, this embodiment presents a business system testing method, specifically including:

[0113] 1. From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0114] 2. From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria;

[0115] 3. Extract information from each target transaction to obtain the corresponding loan data for each target transaction;

[0116] 4. Obtain pre-defined key feature fields;

[0117] 5. Extract key features from the key feature fields of each loan receipt data to obtain the key features that are related to each target transaction information;

[0118] 6. Construct test sample data based on key features;

[0119] 7. For the test sample data, collect all field information from the database table associated with the test sample data as initial test information;

[0120] 8. Execute business operations based on test sample data, and collect all field information of the database table associated with the test sample data after the business operations are executed, as the target test information;

[0121] 9. Determine the test differences between the initial test information and the target test information;

[0122] 10. Based on the test difference information, determine the target test results for the business system.

[0123] The specific process of the above steps can be found in the description of the above method embodiments. The implementation principle and technical effect are similar, and will not be repeated here.

[0124] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0125] Based on the same inventive concept, this application also provides a business system testing apparatus for implementing the business system testing method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more business system testing apparatus embodiments provided below can be found in the limitations of the business system testing method described above, and will not be repeated here.

[0126] In one exemplary embodiment, such as Figure 8As shown, a business system testing apparatus is provided, comprising: a determination module 81, a construction module 82, and a testing module 83, wherein:

[0127] The determination module 81 is used to determine at least one target transaction information that meets the business screening criteria from the historical transaction information contained in the business system;

[0128] The determination module 81 is also used to determine the key features that are related to each target transaction information;

[0129] Module 82 is used to construct test sample data based on key features;

[0130] Test module 83 is used to perform business operations based on test sample data to obtain the target test results of the business system.

[0131] In one embodiment, the determining module 81 is further configured to:

[0132] Information is extracted from each target transaction to obtain the corresponding loan data for each target transaction.

[0133] By performing distribution statistics on the data from each loan receipt, key characteristics of the interrelationships among the target transaction information are obtained.

[0134] In one embodiment, the determining module 81 is further configured to:

[0135] Retrieve pre-defined key feature fields;

[0136] Feature extraction is performed on key feature fields in each loan data to obtain key features that are related to each target transaction information.

[0137] In one embodiment, the determining module 81 is further configured to:

[0138] From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0139] From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria.

[0140] In one embodiment, the test module 83 is further configured to:

[0141] For the test sample data, collect all field information of the database table associated with the test sample data as initial test information;

[0142] Business operations are performed based on test sample data, and all field information of the database table associated with the test sample data after the business operations are performed is collected as target test information.

[0143] Based on the initial test information and the target test information, determine the target test result.

[0144] In one embodiment, the test module 83 is further configured to:

[0145] Determine the test differences between the initial test information and the target test information;

[0146] Based on the test discrepancy information, determine the target test results for the business system.

[0147] Each module in the aforementioned business system testing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the operations corresponding to each module.

[0148] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores the target test results of the business system. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a business system testing method.

[0149] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0150] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0151] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0152] Identify the key characteristics that link the various target transaction information;

[0153] Based on key features, construct test sample data;

[0154] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0155] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0156] Information is extracted from each target transaction to obtain the corresponding loan data for each target transaction.

[0157] By performing distribution statistics on the data from each loan receipt, key characteristics of the interrelationships among the target transaction information are obtained.

[0158] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0159] Retrieve pre-defined key feature fields;

[0160] Feature extraction is performed on key feature fields in each loan data to obtain key features that are related to each target transaction information.

[0161] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0162] From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0163] From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria.

[0164] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0165] For the test sample data, collect all field information of the database table associated with the test sample data as initial test information;

[0166] Business operations are performed based on test sample data, and all field information of the database table associated with the test sample data after the business operations are performed is collected as target test information.

[0167] Based on the initial test information and the target test information, determine the target test result.

[0168] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0169] Determine the test differences between the initial test information and the target test information;

[0170] Based on the test discrepancy information, determine the target test results for the business system.

[0171] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0172] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0173] Identify the key characteristics that link the various target transaction information;

[0174] Based on key features, construct test sample data;

[0175] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0176] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0177] Information is extracted from each target transaction to obtain the corresponding loan data for each target transaction.

[0178] By performing distribution statistics on the data from each loan receipt, key characteristics of the interrelationships among the target transaction information are obtained.

[0179] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0180] Retrieve pre-defined key feature fields;

[0181] Feature extraction is performed on key feature fields in each loan data to obtain key features that are related to each target transaction information.

[0182] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0183] From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0184] From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria.

[0185] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0186] For the test sample data, collect all field information of the database table associated with the test sample data as initial test information;

[0187] Business operations are performed based on test sample data, and all field information of the database table associated with the test sample data after the business operations are performed is collected as target test information.

[0188] Based on the initial test information and the target test information, determine the target test result.

[0189] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0190] Determine the test differences between the initial test information and the target test information;

[0191] Based on the test discrepancy information, determine the target test results for the business system.

[0192] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0193] Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system;

[0194] Identify the key characteristics that link the various target transaction information;

[0195] Based on key features, construct test sample data;

[0196] Based on the test sample data, business operations are performed to obtain the target test results of the business system.

[0197] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0198] Information is extracted from each target transaction to obtain the corresponding loan data for each target transaction.

[0199] By performing distribution statistics on the data from each loan receipt, key characteristics of the interrelationships among the target transaction information are obtained.

[0200] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0201] Retrieve pre-defined key feature fields;

[0202] Feature extraction is performed on key feature fields in each loan data to obtain key features that are related to each target transaction information.

[0203] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0204] From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition;

[0205] From each of the first transaction information, identify at least one target transaction information whose business status meets the second screening criteria.

[0206] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0207] For the test sample data, collect all field information of the database table associated with the test sample data as initial test information;

[0208] Business operations are performed based on test sample data, and all field information of the database table associated with the test sample data after the business operations are performed is collected as target test information.

[0209] Based on the initial test information and the target test information, determine the target test result.

[0210] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0211] Determine the test differences between the initial test information and the target test information;

[0212] Based on the test discrepancy information, determine the target test results for the business system.

[0213] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0214] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0215] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0216] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A business system testing method, characterized in that, The method includes: Identify at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system; Identify the key characteristics that link the various target transaction information items together; Based on the aforementioned key features, test sample data is constructed; Based on the test sample data, business operations are performed to obtain the target test results of the business system.

2. The method according to claim 1, characterized in that, The key features used to determine the interrelationships among the target transaction information include: Information is extracted from each of the target transaction information to obtain the loan data corresponding to each of the target transaction information; By performing distribution statistics on the data of each loan agreement, the key features that are related to the target transaction information are obtained.

3. The method according to claim 2, characterized in that, The distribution statistics of each of the loan data are used to obtain key features that are interrelated to the target transaction information, including: Retrieve pre-defined key feature fields; Feature extraction is performed on the key feature fields in each of the loan data to obtain the key features that are related to each of the target transaction information.

4. The method according to claim 1, characterized in that, The business filtering criteria include a first filtering criterion based on the business operation type and a second filtering criterion based on the business status. The step of determining at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system includes: From the historical transaction information contained in the business system, determine at least one first transaction information whose business operation type meets the first screening condition; From each of the first transaction information, determine at least one target transaction information whose business status meets the second screening criteria.

5. The method according to any one of claims 1-4, characterized in that, The step of performing business operations based on the test sample data to obtain the target test results of the business system includes: For the test sample data, collect all field information of the database table associated with the test sample data as initial test information; The business operation is executed based on the test sample data, and the full field information of the database table associated with the test sample data after the business operation is executed is collected as the target test information. The target test result is determined based on the initial test information and the target test information.

6. The method according to claim 5, characterized in that, The step of determining the target test result based on the initial test information and the target test information includes: Determine the test difference information between the initial test information and the target test information; Based on the test difference information, the target test result of the business system is determined.

7. A business system testing device, characterized in that, The device includes: The determination module is used to determine at least one target transaction that meets the business screening criteria from the historical transaction information contained in the business system. The determining module is also used to determine the key features that are related to each of the target transaction information; A construction module is used to construct test sample data based on the key features; The testing module is used to perform business operations based on the test sample data to obtain the target test results of the business system.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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