A method and device for repairing business anomalies based on automated testing of banking systems

Abstract

The embodiment of the present application provides a method and device for repairing business anomalies based on automated testing of banking systems, which can be used in the field of testing security technology. The method includes: determining a set of repair behavior chains according to the business anomaly information in the automated testing process and the corresponding relationship between the business anomaly information and the set of repair behavior chains; the repair behavior chain information includes at least one repair behavior information; selecting one of the repair behavior chains from the set of repair behavior chains; executing the repair behavior chain to repair the business anomaly information. The present application realizes the autonomous adaptation of the test system by autonomously learning the user's historical behavior data, avoiding the intervention of human programming on the data, and also solving the problem of failed calls between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, the simpler, more commonly used and more reasonable repair behavior chains are used preferentially, so that the test practice is closer to and simulates the actual application situation.

Description

Technical Field

[0001] The present application relates to the field of testing security technology, and in particular to a method and device for repairing business anomalies based on automated testing of a banking system. Background Art

[0002] Large commercial bank transaction systems are usually divided into multiple subsystems, which are developed and maintained by different development and testing teams. In addition, there are often dependent calling relationships between subsystems. A development team usually calls another subsystem through the API documentation provided by another team. In essence, they are not familiar with the internal implementation logic of the other party. Therefore, the automated testing system developed by them is often difficult to properly and thoroughly solve the business logic errors that occur when calling another subsystem program, thereby affecting the success rate of the test. For example, a large amount of funds needs to be transferred between accounts of a certain enterprise. In the IT system of a commercial bank, the functions of the following two subsystems are often involved: the public account transaction subsystem and the anti-money laundering subsystem. When a customer makes a large transfer, the system usually needs to identify whether the transaction may involve money laundering. When the two subsystems are maintained by different development teams, the above problems are prone to occur (such as abnormal settings of the funds, switches and other parameters of the anti-money laundering system). Such problems are difficult to properly solve for the public development team as the upstream system. At this time, a method to properly solve such problems is needed. Summary of the invention

[0003] In response to the problems in the prior art, the present application provides a business anomaly repair method and device based on automated testing of a banking system, which realizes autonomous adaptation of the test system by autonomously learning historical user behavior data, avoids intervention in the data by human programming, and solves the problem of call failures between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used, and more reasonable repair behavior chains are given priority, making the test practice closer to and simulating actual application situations.

[0004] In order to solve the above technical problems, this application provides the following technical solutions:

[0005] One aspect of the present invention provides a method for repairing business anomalies based on automated testing of a banking system, comprising:

[0006] Determine a repair behavior chain set according to the service exception information in the automated test process and the corresponding relationship between the service exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0007] Selecting one of the repair behavior chains from the set of repair behavior chains;

[0008] Execute the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0009] In a preferred embodiment, the step of selecting one of the repair behavior chains from the set of repair behavior chains includes:

[0010] The repair behavior chain information is filtered out from the repair behavior chain set according to a preset evaluation model.

[0011] In a preferred embodiment, it also includes:

[0012] According to each historical business exception information, searching for all corresponding historical repair behavior chains from the historical repair data;

[0013] All historical repair behavior chains found are collected to form a repair behavior chain set corresponding to the business exception information.

[0014] In a preferred embodiment, searching for all corresponding historical repair behavior chains from the historical repair data according to each historical service exception information includes:

[0015] Extract corresponding characteristic information from historical service abnormality information, wherein the characteristic information includes: service name, service number, service running time, and abnormal information code;

[0016] According to the characteristic information, searching the historical repair data for all historical normal business information corresponding to the characteristic information;

[0017] According to each behavior chain in the historical normal business information, a corresponding repair behavior chain of the historical business abnormality is generated.

[0018] In a preferred embodiment, the method further includes: updating the repair behavior chain set.

[0019] In a preferred embodiment, the historical repair data is taken from a set time window, and the updating of the repair behavior chain set includes:

[0020] Taking the time point when the anomaly occurs as the starting point of the set time window and the time point when the anomaly is resolved as the end point of the set time window, reselecting historical repair data of multiple users;

[0021] An updated repair behavior chain set is generated based on the re-selected historical repair data, and the updated repair behavior chain set is used to replace the original repair behavior chain set to update the repair behavior chain set.

[0022] In a preferred embodiment, each repair behavior chain information corresponds to an evaluation score; the step of selecting the optimal repair behavior chain from a preset set of repair behavior chains includes:

[0023] Sorting each repair behavior chain in the repair behavior chain set in descending order of evaluation scores to obtain a repair behavior chain sequence;

[0024] A repair behavior chain at a set position in the repair behavior chain sequence is selected as the filtered repair behavior chain information.

[0025] In a preferred embodiment, the set position is the first position in the repair behavior chain sequence, and the selecting the repair behavior chain at the set position in the repair behavior chain sequence as the filtered repair behavior chain information includes:

[0026] The repair behavior chain at the first position in the repair behavior chain sequence is selected as the filtered repair behavior chain information.

[0027] In a preferred embodiment, each repair behavior chain information corresponds to an evaluation score; the method further includes:

[0028] Generate a score for all repair behavior chains based on their complexity and historical frequency of use.

[0029] In a preferred embodiment, the complexity of the repair behavior chain includes: the length of the repair behavior chain, the cyclomatic complexity of the repair behavior chain, and the generation of scores for all repair behavior chains based on the complexity of the repair behavior chain and the historical usage frequency includes:

[0030] A score is generated for all repair action chains based on the length, cyclomatic complexity and historical usage frequency of the repair action chain.

[0031] Another aspect of the present invention provides a business anomaly repair device based on automated testing of a banking system, comprising:

[0032] A repair behavior chain set determination module determines a repair behavior chain set according to the business exception information in the automated test process and the corresponding relationship between the business exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0033] A repair behavior chain screening module is used to screen out one of the repair behavior chains from the repair behavior chain set;

[0034] An execution repair module executes the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0035] In another aspect of the present invention, the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for repairing business anomalies based on automated testing of a banking system is implemented.

[0036] In another aspect of the present invention, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the business anomaly repair method based on automated testing of a banking system.

[0037] It can be seen from the above technical scheme that the present application provides a method for repairing business anomalies based on automated testing of banking systems, the method comprising: determining a set of repair behavior chains according to the business anomaly information in the automated testing process and the correspondence between the business anomaly information and the set of repair behavior chains; the repair behavior chain information includes at least one repair behavior information; selecting one of the repair behavior chains from the set of repair behavior chains; executing the repair behavior chain to repair the business anomaly information. The present invention realizes the autonomous adaptation of the test system by autonomously learning the user's historical behavior data, avoids the intervention of human programming on the data, and solves the problem of failed calls between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used, and more reasonable repair behavior chains are given priority, so that the test practice is closer to and simulates the actual application situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] 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, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 This is a flowchart of a business anomaly repair method based on automated testing of banking systems.

[0040] Figure 2 It is a flowchart of the repair behavior chain set generation process.

[0041] Figure 3 It is a flowchart of obtaining the historical restoration behavior chain.

[0042] Figure 4 It is a flowchart of the repair behavior chain set update process.

[0043] Figure 5 It is a flowchart of the screening and repair behavior chain.

[0044] Figure 6 It is a schematic diagram of the structure of a business anomaly repair device based on automated testing of a banking system.

[0045] Figure 7 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] It should be noted that the business anomaly repair method and device based on automated testing of banking systems disclosed in the present application can be used in the field of testing security technology, and can also be used in any field except the field of computer technology. The application field of the business anomaly repair method and device based on automated testing of banking systems disclosed in the present application is not limited.

[0048] In a specific embodiment, the present application provides a method for repairing business anomalies based on automated testing of a banking system, such as Figure 1 ,include:

[0049] S1: determining a repair behavior chain set according to the service exception information in the automated test process and the corresponding relationship between the service exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0050] Specifically, automated testing is a process of converting human-driven test behavior into machine execution. Usually, after the test case is designed and reviewed, the tester performs the test step by step according to the procedures described in the test case to obtain a comparison between the actual result and the expected result. In this process, in order to save manpower, time or hardware resources and improve test efficiency. In the process of automated testing, the business logic in the test case cannot be executed normally due to some reasons, and the business exception occurs. These business exception information will be recorded in the test log. For example, a test case is used to test the account withdrawal business. Because the withdrawal amount input into the test case is greater than the total amount of the account, the test case is executed abnormally, and the exception code in the recorded exception information is insufficient balance. According to the business exception information, the corresponding repair behavior chain set is determined, and the repair behavior chain set includes at least one repair behavior chain for the business exception, such as insufficient balance. In a specific embodiment, the repair behavior chain is a behavior chain composed of at least one repair behavior. For example, the repair behavior chain set for insufficient balance includes two repair behavior chains. Among them, the first repair behavior chain is: 1. Reduce the withdrawal amount to below the total amount, 2. Execute the withdrawal business operation, and the repair behavior chain includes two repair behaviors; the second repair behavior chain is: 1. Supplement the total amount of the account to above the withdrawal amount, 2. Execute the withdrawal business operation, and the repair behavior chain also includes two repair behaviors. The basic logic of the generation of the repair behavior chain is the timeliness requirement for problem solving and the invariance of the processing object. Business errors usually require resolution on the same day or even immediately, and there will be delays in rare cases. When there are abnormalities in the counter transactions represented by the teller, the same teller is usually responsible for resolving and handling them. For users, it is limited to handling their own business. And in the end, it must be through a transaction that is the same business as the failed transaction but is successfully handled to achieve the final repair closed loop. It is only necessary to find a series of transactions from the user's transaction error to the successful transaction, and this series of transactions can be regarded as a repair behavior chain that modifies the error. In a specific embodiment, the generation steps of the repair behavior chain set are as follows: Figure 2 ,include:

[0051] S11: searching for all corresponding historical repair behavior chains from the historical repair data according to each historical business exception information;

[0052] Specifically, the set of repair behavior chains for each business anomaly is generated based on the summary of the historical repair behavior chains for the business anomaly, and the historical repair data includes the historical repair behavior chains for the business anomaly. In a specific embodiment, the historical repair data is all the repair data included in a historical time window, and these repair data are the repair behavior data made by users for business anomalies in actual business operations. For example, the end point of the historical time window is set to the current time point, and the starting point of the window is set to the time point corresponding to the current time point minus 24 hours, that is, the duration of the historical time window is 24 hours.

[0053] In a specific embodiment, the above method searches for all corresponding historical repair behavior chains from the historical repair data according to each historical service exception information, such as Figure 3 ,include:

[0054] S111: extracting corresponding characteristic information from historical service exception information, wherein the characteristic information includes: service name, service number, service running time, and exception information code;

[0055] S112: searching the historical repair data for all historical normal service information corresponding to the characteristic information according to the characteristic information;

[0056] S113: Generate a corresponding repair behavior chain for the historical business abnormality according to the behavior chain in each of the historical business normal information.

[0057] Specifically, historical repair data within a set time window is obtained, and all corresponding historical repair behavior chains are found according to features such as the business name, business code, and exception information code in the business exception information. For example, in a business exception information, the business name is a deposit business, the business code is 001, and the exception information code is 01. The corresponding exception information is a password error. For this business exception information, 20 historical repair behavior chains corresponding to password errors in deposit businesses are found in all historical repair data within a time window of 24 hours.

[0058] S12: All historical repair behavior chains found are collected to form a repair behavior chain set corresponding to the business exception information.

[0059] Specifically, all historical repair behavior chains corresponding to a certain business anomaly found are collected together to form a repair behavior chain collection. It can be understood that there are many ways to collect all the repair behavior chains for a certain business anomaly together, such as marking all the repair behavior chains for deposit password errors as 1, or storing them in a folder, or storing them in a database table to form a repair behavior chain collection for subsequent query.

[0060] In a specific embodiment, the repair behavior chain set is updateable, and the specific steps of updating are as follows: Figure 4 ,include:

[0061] S121: taking the time point when the exception occurs as the starting point of the set time window and the time point when the exception is resolved as the end point of the set time window, and reselecting historical repair data of multiple users;

[0062] Specifically, when an execution exception occurs when executing a test case, you can directly select the best one from the repair behavior chain. After the exception is repaired and executed, in order to ensure that all repair behavior chains for the exception can be included in the repair behavior chain set for the exception, the time point when the exception occurs will be used as the starting point of the set time window, and the time point when it is resolved will be used as the end point. Multiple user historical repair data will be reselected. The users are the users who actually execute the business. For example, users of deposit business include bank counter operators, ATM users, mobile banking users, etc.

[0063] S122: Generate an updated repair behavior chain set based on the re-selected historical repair data, and replace the original repair behavior chain set with the updated repair behavior chain set to update the repair behavior chain set.

[0064] Specifically, after the historical repair data is reselected, all the repair behavior chains in the new historical repair data are searched again according to the characteristic information in the business exception information, and the collection is an updated repair behavior chain collection, which replaces the original repair behavior chain collection.

[0065] S2: selecting one of the repair behavior chains from the set of repair behavior chains;

[0066] Specifically, when a business execution exception occurs during the testing process, after determining the corresponding set of repair behavior chains based on the business exception information, it is necessary to select a repair behavior chain from the set of repair behavior chains to repair the exception. In a specific embodiment, in order to obtain the optimal repair behavior chain, an evaluation criterion for the repair behavior chain is introduced. According to the complexity and historical usage frequency of the repair behavior chain, scores for all repair behavior chains are generated, where the complexity of the repair behavior chain includes the length of the repair behavior chain and the cyclomatic complexity of the repair behavior chain. For example, if a repair behavior chain consists of 2 repair behaviors and has no loops or recursions, its complexity score can be regarded as 80. Another repair behavior chain consists of 8 repair behaviors and also has no loops and recursions, so its complexity can be regarded as 20. There is also a repair behavior chain consisting of 6 repair behaviors with one loop behavior, so its complexity can be regarded as 35. The smaller the complexity of the repair behavior chain, the simpler the repair steps, so its score increases sequentially from large to small according to the repair complexity. The historical usage frequency indicates that it is more general or more reasonable, so its score increases sequentially from few to many according to the number of times it appears.

[0067] The overall scoring formula is as follows:

[0068] S = S1 * W1 + S2 * W2

[0069] S: overall score, S1: single-item score for the complexity of the repair behavior chain (the single-item scoring rule is self-defined, 0 <= S1 <= 100), S2: single-item score for the historical usage frequency (the single-item scoring rule is self-defined, 0 <= S2 <= 100), W1: single-item weight value for the complexity of the repair behavior chain (the weight value is self-defined, 0 < W1 < 1), single-item weight value for the historical usage frequency (the weight value is self-defined, 0 < W2 < 1), W1 + W2 = 100%. For example, in the exception repair behavior chain for insufficient withdrawal balance, there are 4 repair behavior chains, and their single-item scores and weights are: 80, 0.2, 50, 0.4; 70, 0.6, 90, 0.8; 40, 0.9, 90, 0.4; 45, 0.6, 30, 0.8. Using the scoring formula, the scores of the 4 repair behavior chains are calculated as: 36, 114, 72, 51. Generally, in order to repair the business exceptions that occur during testing as quickly and best as possible, the repair behavior chain with the highest score will be adopted. The selection of the repair behavior chain from a preset set of repair behavior chains, such as Figure 5 , includes:

[0070] S21: Sort each repair behavior chain in the set of repair behavior chains in descending order according to the evaluation score to obtain a sequence of repair behavior chains;

[0071] In a specific embodiment, for example, the evaluation scores of four repair behavior chains are: the first is 36, the second is 114, the third is 72, and the fourth is 51. The repair behavior chains are sorted in descending order of the evaluation scores to obtain a repair behavior chain sequence, i.e., the second, the third, the fourth, and the first.

[0072] S22: Selecting a repair behavior chain at a set position in the repair behavior chain sequence as the filtered repair behavior chain information.

[0073] Specifically, the setting position is generally at the head of the sequence, such as the first position of the sequence. In a specific embodiment, if the sequence of the repair behavior chains is 1, 2, 3, 4, 5, the repair behavior chain 1 is selected first. If the repair behavior chain 1 cannot obtain an effective repair effect, the repair behavior chain 2 is selected, and so on.

[0074] S3: Execute the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0075] The present invention is further described in conjunction with a specific scenario.

[0076] The program scanned a current account withdrawal transaction at an ATM and found a business error. The error message was insufficient account balance. The customer who handled the transaction was A, and the time of occurrence was 2000-01-01 10:00:01.994766. Therefore, the program continues to search the anonymized log pool with customer A as the condition, and extracts all transaction records about A between 2000-01-01 10:00:01.994766 and 2000-01-02 00:00:00.000000. After searching, it is found that A completed a current account withdrawal transaction of the same amount at the ATM at 2000-01-01 10:10:01.994766. During this period, A also signed a small loan agreement and the system automatically issued a small loan to A. The program determines that the current account withdrawal failed - the small loan agreement was successfully signed - the system loan was successfully issued - the current account withdrawal was successful, forming a repair behavior chain, in which the repair transactions are the signing of the small loan agreement and the system loan. The complexity of the repair behavior chain is judged to be 2. At the same time, test cases for the signing of the small loan agreement and the system loan were also found in the test case pool. The program searches the set of repair behavior chains to find the set of repair behavior chains with insufficient current current withdrawal balance. Assume that two repair behavior chains (current transfer, T+0 financial product redemption) are searched out, the length of the two repair behavior chains is 1, and the number of occurrences is 20 and 10 respectively. Therefore, the program determines that the repair behavior chain (micro-loan agreement signing-system loan) is a new repair behavior chain that appears for the first time. Assume that the complexity of the repair behavior chain is scored using a linear strategy (1:100, 2:90, 3:80..........10 or above:10), with a weight of 40%, and the historical frequency of use of the repair behavior chain is scored using a ranking scoring strategy (first place: 100, second place: 90, third place: 80........10th place or later 10), with a weight of 60%. The scores of the three existing repair behavior chains are (current transfer: 100*40%+100*60%=100, T+0 financial product redemption: 100*40%+90*60%=94, micro-loan agreement signing-system loan: 90*40%+80*60%=84). Because the current repair behavior chain ranking order is current transfer, T+0 financial product redemption, micro-loan agreement signing-system loan. Finally, the latest results of the three repair behavior chains are updated to the repair behavior chain set.

[0077] In the specific testing process, assume that there are the following six test cases in the test case pool: A, B, C, D, E, F

[0078] The order of execution of use cases is A->B->C->D->E->F.

[0079] The repair behavior chain of each function is shown in the following table:

[0080] Function Name Repair behavior chain A C->F B A C E D F->B E D F C

[0081] After the test is started, the test cases are executed in the order of A->B->C->D->E->F. Assume that A, B, and C are all executed successfully, and an exception occurs when executing D. At this time, the system executes the following steps:

[0082] 1. Extract D’s repair behavior chain (F->B).

[0083] 2. Execute use case F. If F also executes abnormally, you need to recursively repair F first and extract the repair behavior chain of F (C).

[0084] 3. Execute the repair step use case C of F. After C is successfully executed, set the status of C to executed, and then re-execute F.

[0085] 4. After successfully executing use case F, set the status of F to Executed.

[0086] 5. Execute use case B. After successful execution, set the status of B to Executed.

[0087] 6. Re-execute use case D. Since its repair behavior chain (F->B) has been executed, D should be able to execute successfully and set D to the executed state.

[0088] 7. Execute use case E.

[0089] 8. Execute use case F. Since the system finds that F has been executed, it skips F and does not execute it again to avoid unnecessary repeated execution.

[0090] From the above description, it can be seen that the business anomaly repair method based on automated testing of the banking system provided by the present invention realizes autonomous adaptation of the test system by autonomously learning user historical behavior data, avoids intervention in data by human programming, and solves the problem of call failure between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used, and more reasonable repair behavior chains are given priority, making the test practice closer to and simulating actual application situations.

[0091] From the software level, the present application provides an embodiment of a business anomaly repair device based on automated testing of a banking system for executing all or part of the business anomaly repair method based on automated testing of a banking system, see Figure 6 The business anomaly repair device based on automated testing of the banking system specifically includes the following contents:

[0092] A repair behavior chain set determination module 1 determines a repair behavior chain set according to the business exception information in the automated test process and the corresponding relationship between the business exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0093] A repair behavior chain screening module 2 is configured to screen out one of the repair behavior chains from the repair behavior chain set;

[0094] Execute repair module 3, execute the repair behavior chain, and repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0095] In a specific embodiment, the present application provides a business anomaly repair device based on automated testing of a banking system, which is used to perform the following steps:

[0096] S1: determining a repair behavior chain set according to the service exception information in the automated test process and the corresponding relationship between the service exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0097] Specifically, automated testing is a process of converting human-driven test behavior into machine execution. Usually, after the test case is designed and reviewed, the tester performs the test step by step according to the procedures described in the test case to obtain a comparison between the actual result and the expected result. In this process, in order to save manpower, time or hardware resources and improve test efficiency. In the process of automated testing, the business logic in the test case cannot be executed normally due to some reasons, and the business exception occurs. These business exception information will be recorded in the test log. For example, a test case is used to test the account withdrawal business. Because the withdrawal amount input into the test case is greater than the total amount of the account, the test case is executed abnormally, and the exception code in the recorded exception information is insufficient balance. According to the business exception information, the corresponding repair behavior chain set is determined, and the repair behavior chain set includes at least one repair behavior chain for the business exception, such as insufficient balance. In a specific embodiment, the repair behavior chain is a behavior chain composed of at least one repair behavior. For example, the repair behavior chain set for insufficient balance includes two repair behavior chains. Among them, the first repair behavior chain is: 1. reduce the withdrawal amount to below the total amount, 2. execute the withdrawal business operation, and the repair behavior chain includes two repair behaviors; the second repair behavior chain is: 1. replenish the total amount of the account to above the withdrawal amount, 2. execute the withdrawal business operation, and the repair behavior chain also includes two repair behaviors. The basic logic of the generation of the repair behavior chain is the timeliness requirement for problem solving and the invariance of the processing object. Business errors usually require resolution on the same day or even immediately, and there will be delays in rare cases. When there is an abnormality in the counter transaction of the teller agent, the same teller is usually responsible for solving it. For users, it is limited to handling their own business. And in the end, it must be a closed loop of the final repair through a transaction that is the same business as the failed transaction but is successfully handled. It is only necessary to find a series of transactions from the user's transaction error to the transaction success, and this series of transactions can be regarded as a repair behavior chain to modify the error. In a specific embodiment, the repair behavior chain set generation module in the device is used to perform the following steps:

[0098] S11: searching for all corresponding historical repair behavior chains from the historical repair data according to each historical business exception information;

[0099] Specifically, the set of repair behavior chains for each business anomaly is generated based on the summary of the historical repair behavior chains for the business anomaly, and the historical repair data includes the historical repair behavior chains for the business anomaly. In a specific embodiment, the historical repair data is all the repair data included in a historical time window, and these repair data are the repair behavior data made by users for business anomalies in actual business operations. For example, the end point of the historical time window is set to the current time point, and the starting point of the window is set to the time point corresponding to the current time point minus 24 hours, that is, the duration of the historical time window is 24 hours.

[0100] In a specific embodiment, the repair behavior chain search unit of the device is configured to perform the following steps:

[0101] S111: extracting corresponding characteristic information from historical service exception information, wherein the characteristic information includes: service name, service number, service running time, and exception information code;

[0102] S112: searching the historical repair data for all historical normal service information corresponding to the characteristic information according to the characteristic information;

[0103] S113: Generate a corresponding repair behavior chain for the historical business abnormality according to the behavior chain in each of the historical business normal information.

[0104] Specifically, historical repair data within a set time window is obtained, and all corresponding historical repair behavior chains are found according to features such as the business name, business code, and exception information code in the business exception information. For example, in a business exception information, the business name is a deposit business, the business code is 001, and the exception information code is 01. The corresponding exception information is a password error. For this business exception information, 20 historical repair behavior chains corresponding to password errors in deposit businesses are found in all historical repair data within a time window of 24 hours.

[0105] S12: All historical repair behavior chains found are collected to form a repair behavior chain set corresponding to the business exception information.

[0106] Specifically, all historical repair behavior chains corresponding to a certain business anomaly found are collected together to form a repair behavior chain collection. It can be understood that there are many ways to collect all the repair behavior chains for a certain business anomaly together, such as marking all the repair behavior chains for deposit password errors as 1, or storing them in a folder, or storing them in a database table to form a repair behavior chain collection for subsequent query.

[0107] In a specific embodiment, the repair behavior chain set updating module of the device is used to perform the following steps:

[0108] S121: taking the time point when the exception occurs as the starting point of the set time window and the time point when the exception is resolved as the end point of the set time window, and reselecting historical repair data of multiple users;

[0109] Specifically, when an execution exception occurs when executing a test case, you can directly select the best one from the repair behavior chain. After the exception is repaired and executed, in order to ensure that all repair behavior chains for the exception can be included in the repair behavior chain set for the exception, the time point when the exception occurs will be used as the starting point of the set time window, and the time point when it is resolved will be used as the end point. Multiple user historical repair data will be reselected. The users are the users who actually execute the business. For example, users of deposit business include bank counter operators, ATM users, mobile banking users, etc.

[0110] S122: Generate an updated repair behavior chain set based on the re-selected historical repair data, and replace the original repair behavior chain set with the updated repair behavior chain set to update the repair behavior chain set.

[0111] Specifically, after the historical repair data is reselected, all the repair behavior chains in the new historical repair data are searched again according to the characteristic information in the business exception information, and the collection is an updated repair behavior chain collection, which replaces the original repair behavior chain collection.

[0112] S2: selecting one of the repair behavior chains from the set of repair behavior chains;

[0113] Specifically, when a business execution exception occurs during the test, after the corresponding repair behavior chain set is determined according to the business exception information, a repair behavior chain needs to be screened out from the repair behavior chain set to repair the exception. In a specific embodiment, in order to obtain the optimal repair behavior chain, an evaluation standard for the repair behavior chain is introduced. According to the complexity and historical usage frequency of the repair behavior chain, all repair behavior chain scores are generated, wherein the complexity of the repair behavior chain includes the length of the repair behavior chain and the cyclomatic complexity of the repair behavior chain. For example, if a repair behavior chain consists of 2 repair behaviors and has no loop or recursion, its complexity score can be regarded as 80, another repair behavior chain consists of 8 repair behaviors and has no loop or recursion, then its complexity can be regarded as 20, and another repair behavior chain consists of 6 repair behaviors and has a cyclic behavior, then its complexity can be regarded as 35. The smaller the complexity of the repair behavior chain, the simpler the repair steps, so its score increases in sequence from large to small according to the repair complexity, and the historical usage frequency indicates that it is more general or more reasonable, so its score increases in sequence from small to large according to its number of occurrences.

[0114] The overall scoring formula is: S = S1*W1+S2*W2

[0115] S: Overall score, S1: Single - item score for the complexity of the repair behavior chain (the single - item scoring rule is self - defined, 0 <= S1 <= 100), S2: Single - item score for the historical usage frequency (the single - item scoring rule is self - defined, 0 <= S2 <= 100), W1: Single - item weight value for the complexity of the repair behavior chain (the weight value is self - defined, 0 < W1 < 1), historical usage frequency single - item weight value (the weight value is self - defined, 0 < W2 < 1), W1+W2 = 100%. For example, in the abnormal repair behavior chain for insufficient withdrawal balance, there are 4 repair behavior chains, and their single - item scores and weights are respectively: 80, 0.2, 50, 0.4; 70, 0.6, 90, 0.8; 40, 0.9, 90, 0.4; 45, 0.6, 30, 0.8. Using the scoring formula, the scores of the 4 repair behavior chains are calculated as: 36, 114, 72, 51. Generally, in order to repair the business exceptions that occur in the test fastest and best, the repair behavior chain with the highest score is adopted. In a specific embodiment, the screening and repair behavior chain unit of the device is used to perform the following steps, including:

[0116] S21: Sort each repair behavior chain in the set of repair behavior chains in descending order of the evaluation score to obtain a repair behavior chain sequence;

[0117] In a specific embodiment, for example, the evaluation scores of 4 repair behavior chains are respectively: the first one is 36, the second one is 114, the third one is 72, and the fourth one is 51. Then, sort the repair behavior chains in descending order of the evaluation score to obtain a repair behavior chain sequence, that is, the second one, the third one, the fourth one, and the first one.

[0118] S22: Select the repair behavior chain at the set position in the repair behavior chain sequence as the screened repair behavior chain information.

[0119] Specifically, the set position is generally at the head position of the sequence, such as the first position of the sequence. In a specific embodiment, if the repair behavior chain sequence is 1, 2, 3, 4, 5, then first select repair behavior chain 1. If repair behavior chain 1 cannot obtain an effective repair effect, then select repair behavior chain 2, and so on.

[0120] S3: Execute the repair behavior chain to repair the business exception information; wherein, each repair behavior chain in the set of repair behavior chains is determined based on the historical repair data of multiple users; the historical repair data includes historical business exception information and the corresponding historical repair behavior chain.

[0121] In combination with a specific scenario, the present invention is further described.

[0122] The program scanned a current account withdrawal transaction at an ATM and found a business error. The error message was insufficient account balance. The customer who handled the transaction was A, and the time of occurrence was 2000-01-01 10:00:01.994766. Therefore, the program continues to search the anonymized log pool with customer A as the condition, and extracts all transaction records about A between 2000-01-01 10:00:01.994766 and 2000-01-02 00:00:00.000000. After searching, it is found that A completed a current account withdrawal transaction of the same amount at the ATM at 2000-01-01 10:10:01.994766. During this period, A also signed a small loan agreement and the system automatically issued a small loan to A. The program determines that the current account withdrawal failed - the small loan agreement was successfully signed - the system loan was successfully issued - the current account withdrawal was successful, forming a repair behavior chain, in which the repair transactions are the signing of the small loan agreement and the system loan. The complexity of the repair behavior chain is judged to be 2. At the same time, test cases for the signing of the small loan agreement and the system loan were also found in the test case pool. The program searches the set of repair behavior chains to find the set of repair behavior chains with insufficient current current withdrawal balance. Assume that two repair behavior chains (current transfer, T+0 financial product redemption) are searched out, the length of the two repair behavior chains is 1, and the number of occurrences is 20 and 10 respectively. Therefore, the program determines that the repair behavior chain (micro-loan agreement signing-system loan) is a new repair behavior chain that appears for the first time. Assume that the complexity of the repair behavior chain is scored using a linear strategy (1:100, 2:90, 3:80..........10 or above:10), with a weight of 40%, and the historical frequency of use of the repair behavior chain is scored using a ranking scoring strategy (first place: 100, second place: 90, third place: 80........10th place or later 10), with a weight of 60%. The scores of the three existing repair behavior chains are (current transfer: 100*40%+100*60%=100, T+0 financial product redemption: 100*40%+90*60%=94, micro-loan agreement signing-system loan: 90*40%+80*60%=84). Because the current repair behavior chain ranking order is current transfer, T+0 financial product redemption, micro-loan agreement signing-system loan. Finally, the latest results of the three repair behavior chains are updated to the repair behavior chain set.

[0123] In the specific testing process, assume that there are the following six test cases in the test case pool: A, B, C, D, E, F

[0124] The order of execution of use cases is A->B->C->D->E->F.

[0125] The repair behavior chain of each function is shown in the following table:

[0126] Function Name Repair behavior chain A C->F B A C E D F->B E D F C

[0127] After the test is started, the test cases are executed in the order of A->B->C->D->E->F. Assume that A, B, and C are all executed successfully, and an exception occurs when executing D. At this time, the system executes the following steps:

[0128] 1. Extract D’s repair behavior chain (F->B).

[0129] 2. Execute use case F. If F also executes abnormally, you need to recursively repair F first and extract the repair behavior chain of F (C).

[0130] 3. Execute the repair step use case C of F. After C is successfully executed, set the status of C to executed, and then re-execute F.

[0131] 4. After successfully executing use case F, set the status of F to Executed.

[0132] 5. Execute use case B. After successful execution, set the status of B to Executed.

[0133] 6. Re-execute use case D. Since its repair behavior chain (F->B) has been executed, D should be able to execute successfully and set D to the executed state.

[0134] 7. Execute use case E.

[0135] 8. Execute use case F. Since the system finds that F has been executed, it skips F and does not execute it again to avoid unnecessary repeated execution.

[0136] From the above description, it can be seen that the business anomaly repair device based on automated testing of a banking system provided by the present invention is used to perform the following steps: autonomous adaptation of the test system is achieved by autonomously learning user historical behavior data, thereby avoiding intervention of data by human programming and solving the problem of failed calls between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used and more reasonable repair behavior chains are given priority, making the test practice closer to and simulating actual application situations.

[0137] From a hardware perspective, the present application provides an embodiment of an electronic device for implementing all or part of the content of a business anomaly repair method based on automated testing of a banking system, wherein the electronic device specifically includes the following content:

[0138] Figure 7 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Figure 7As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Figure 7 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0139] In one embodiment, the business anomaly repair function based on automated testing of the banking system can be integrated into the central processing unit. The central processing unit can be configured to perform the following control:

[0140] S1: determining a repair behavior chain set according to the service exception information in the automated test process and the corresponding relationship between the service exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0141] S2: selecting one of the repair behavior chains from the set of repair behavior chains;

[0142] S3: Execute the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0143] From the above description, it can be seen that the electronic device provided in the embodiment of the present application realizes autonomous adaptation of the test system by autonomously learning the user's historical behavior data, avoids the intervention of human programming on the data, and solves the problem of call failure between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used and more reasonable repair behavior chains are given priority, so that the test practice is closer to and simulates the actual application situation.

[0144] In another embodiment, the business anomaly repair device based on automated testing of the banking system can be configured separately from the central processor 9100. For example, the business anomaly repair device based on automated testing of the banking system can be configured as a chip connected to the central processor 9100, and the business anomaly repair function based on automated testing of the banking system can be implemented through the control of the central processor.

[0145] like Figure 7 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Figure 7 In addition, the electronic device 9600 may also include Figure 7 For components not shown, reference may be made to the prior art.

[0146] like Figure 7 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0147] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0148] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0149] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0150] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0151] The communication module 9110 is a transmitter / receiver 9110 that sends and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0152] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module, etc. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0153] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the business anomaly repair method based on automated testing of a banking system in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps of the business anomaly repair method based on automated testing of a banking system in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0154] S1: determining a repair behavior chain set according to the service exception information in the automated test process and the corresponding relationship between the service exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information;

[0155] S2: selecting one of the repair behavior chains from the set of repair behavior chains;

[0156] S3: Execute the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains.

[0157] From the above description, it can be seen that the computer-readable storage medium provided in the embodiment of the present application realizes autonomous adaptation of the test system by autonomously learning user historical behavior data, avoids the intervention of human programming on the data, and solves the problem of call failure between different subsystems; on the other hand, by introducing an evaluation model for the repair behavior chain to assist, simpler, more commonly used and more reasonable repair behavior chains are given priority, so that the test practice is closer to and simulates the actual application situation.

[0158] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0159] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0160] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0161] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0162] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for repairing business anomalies based on automated testing of banking systems, characterized in that: include: Determine a repair behavior chain set according to the business exception information in the automated test process and the corresponding relationship between the business exception information and the repair behavior chain set; The repair behavior chain information includes at least one repair behavior information, and a series of transactions from a transaction error to a transaction success is a repair behavior chain for modifying the transaction error; Selecting one of the repair behavior chains from the set of repair behavior chains; Executing the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains; The step of generating the repair behavior chain set includes: According to each historical business exception information, searching for all corresponding historical repair behavior chains from the historical repair data; All historical repair behavior chains found are collected to form a repair behavior chain set corresponding to the business exception information; The searching for all corresponding historical repair behavior chains from the historical repair data according to each historical business exception information includes: Extract corresponding characteristic information from historical service exception information, wherein the characteristic information includes: service name, service number, service running time, and exception information code; According to the characteristic information, searching the historical repair data for all historical normal business information corresponding to the characteristic information; According to each behavior chain in the historical normal business information, a corresponding repair behavior chain of the historical business abnormality is generated.

2. A method for repairing business anomalies based on automated testing of banking systems according to claim 1, characterized in that: The step of selecting one of the repair behavior chains from the set of repair behavior chains includes: The repair behavior chain information is filtered out from the repair behavior chain set according to a preset evaluation model.

3. A method for repairing business anomalies based on automated testing of banking systems according to claim 1, characterized in that: Also includes: The set of repair behavior chains is updated.

4. A method for repairing business anomalies based on automated testing of banking systems according to claim 3, characterized in that: The historical repair data is taken from a set time window, and the updating of the repair behavior chain set includes: Taking the time point when the anomaly occurs as the starting point of the set time window and the time point when the anomaly is resolved as the end point of the set time window, reselecting historical repair data of multiple users; An updated repair behavior chain set is generated based on the re-selected historical repair data, and the updated repair behavior chain set is used to replace the original repair behavior chain set to update the repair behavior chain set.

5. A method for repairing business anomalies based on automated testing of banking systems according to claim 1, characterized in that: Each repair behavior chain information corresponds to an evaluation score; The step of selecting one of the repair behavior chains from the set of repair behavior chains includes: Sorting each repair behavior chain in the repair behavior chain set in descending order of evaluation scores to obtain a repair behavior chain sequence; A repair behavior chain at a set position in the repair behavior chain sequence is selected as the filtered repair behavior chain information.

6. A method for repairing business anomalies based on automated testing of banking systems according to claim 5, characterized in that: The set position is the first position in the repair behavior chain sequence, and the selecting the repair behavior chain at the set position in the repair behavior chain sequence as the filtered repair behavior chain information includes: The repair behavior chain at the first position in the repair behavior chain sequence is selected as the filtered repair behavior chain information.

7. A method for repairing business anomalies based on automated testing of banking systems according to claim 1, characterized in that: Each repair behavior chain information corresponds to an evaluation score; The method further comprises: Generate a score for all repair behavior chains based on their complexity and historical frequency of use.

8. A method for repairing business anomalies based on automated testing of banking systems according to claim 7, characterized in that: The complexity of the repair behavior chain includes: the length of the repair behavior chain, the cyclomatic complexity of the repair behavior chain, and the scores of all repair behavior chains are generated according to the complexity of the repair behavior chain and the historical usage frequency, including: A score is generated for all repair action chains based on the length, cyclomatic complexity and historical usage frequency of the repair action chain.

9. A business anomaly repair device based on automated testing of banking systems, characterized in that: include: A repair behavior chain set determination module determines a repair behavior chain set according to business exception information in the automated test process and the corresponding relationship between the business exception information and the repair behavior chain set; the repair behavior chain information includes at least one repair behavior information, and a series of transactions from a transaction error to a transaction success is a repair behavior chain for modifying a transaction error; A repair behavior chain screening module is used to screen out one of the repair behavior chains from the repair behavior chain set; An execution repair module executes the repair behavior chain to repair the business exception information; wherein each repair behavior chain in the repair behavior chain set is determined based on historical repair data of multiple users; the historical repair data includes historical business exception information and corresponding historical repair behavior chains; The step of generating the repair behavior chain set includes: According to each historical business exception information, searching for all corresponding historical repair behavior chains from the historical repair data; All historical repair behavior chains found are collected to form a repair behavior chain set corresponding to the business exception information; The searching for all corresponding historical repair behavior chains from the historical repair data according to each historical business exception information includes: Extract corresponding characteristic information from historical service abnormality information, wherein the characteristic information includes: service name, service number, service running time, and abnormal information code; According to the characteristic information, searching the historical repair data for all historical normal business information corresponding to the characteristic information; According to each behavior chain in the historical normal business information, a corresponding repair behavior chain of the historical business abnormality is generated.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the business anomaly repair method based on automated testing of the banking system as described in any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for repairing business anomalies based on automated testing of a banking system as described in any one of claims 1 to 8 is implemented.

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