Test data management method and system based on database retrieval of corresponding information

Abstract

This invention discloses a test data management method and system based on database call information, belonging to the field of test data processing technology. The method includes the following steps: monitoring and classifying test tasks requesting data from a specified database at the current monitoring point; calculating a core level index based on the core characteristic parameters of each test table to determine whether it enters the data processing module; if it enters the data processing module, firstly, prioritizing the test tasks based on their priority factor evaluation values, and then classifying and managing the test tables and requesting test tasks according to the priority factor evaluation values ​​and the core level index; if it does not enter the data processing module, monitoring the database status indicators to determine whether an abnormal status warning is needed. The entire process ensures database health and task priority management through real-time monitoring and analysis, improving the efficiency of database management.

Description

Technical Field

[0001] This invention relates to the field of test data processing technology, and in particular to a test data management method and system based on database retrieval of corresponding information. Background Technology

[0002] With the explosive growth of data in modern society, database technology has become a core support for various application systems due to its efficient data management, storage, retrieval, and security mechanisms. Test data management methods utilize database technology to achieve centralized storage, efficient retrieval, regular updates, and rigorous verification of test data, ensuring its accuracy, consistency, and validity.

[0003] Existing test data management methods mainly process concurrent requests in a pre-defined priority queuing order or commit time order, while using exclusive locks to ensure that other transactions cannot read or write the data while one transaction is writing to it.

[0004] For example, patent application CN114185807A discloses a test data management method, apparatus, computer equipment, and storage medium, including: acquiring the functional architecture of a target terminal, wherein the functional architecture consists of multiple functional units; configuring verification rules for each functional unit based on the functional architecture and a preset rule database, wherein the rule database is used to store the verification rules corresponding to various functional units; extracting test data from the target terminal and splitting the test data according to each functional unit to generate multiple functional test data; verifying the corresponding functional test data according to the verification rules of each functional unit; and sending verification error information to the target terminal when any functional test data verification fails.

[0005] For example, patent application CN118277449A discloses a test data management method and system for industrial production, including: S10: setting up a product test database and a backend program connecting to the test database in a server; the test database is used to acquire and store test data uploaded by various testing terminals; the backend program is used to connect to various query terminals; S20: the backend program obtains the query conditions input by the user from the query terminal; S30: the backend program retrieves test data that meets the query conditions from the test database and performs statistical analysis on the retrieved test data, sending the test data and corresponding statistical analysis results to the query terminal for display. An industrial production test data management system is also provided, which displays test data and corresponding statistical analysis results according to the query conditions when test data needs to be queried.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, when processing request test tasks according to the queuing order, the failure to dynamically adjust the queuing tasks according to the requirements leads to some low-priority tasks unnecessarily blocking the execution of high-priority tasks. This slows down the overall processing speed and results in low database management efficiency. Summary of the Invention

[0008] This invention provides a test data management method and system based on database call information. It solves the problem in the prior art where, when processing request test tasks according to the queuing order, the queuing tasks are not dynamically adjusted according to the needs, causing some low-priority tasks to unnecessarily block the execution of high-priority tasks, slowing down the overall processing speed and resulting in low database management efficiency. This invention reduces the overall processing time of tasks, thereby improving the efficiency of database management.

[0009] This invention provides a test data management method based on database call information, comprising the following steps: real-time acquisition of each requested test task and each requested test task type of a specified database at the current time monitoring point; classification of the test tables of each requested test task at the current time monitoring point to obtain the requested test tasks of each test table at the current time monitoring point; real-time monitoring of the core characteristic parameters of each test table of the specified database to obtain the core degree index of each test table; and determining whether each test table has entered the data processing stage based on the number of requested test tasks and the core degree index of each test table at the current time monitoring point; the data processing stage specifically involves real-time acquisition of priority factor data and influence parameters of each requested test task of each test table of the specified database to obtain the priority evaluation value of each requested test task of each test table; and classification and management of each test table and each requested test task based on the core degree index and the priority evaluation value of each requested test task of each test table; if the data processing stage has not been entered, monitoring the database status data of the specified database at the current time monitoring point to obtain the database status index; and determining whether to issue an abnormal status warning based on the database status index at the current time monitoring point.

[0010] Furthermore, the steps for determining whether each test table should enter the data processing stage based on the number of requested test tasks for each test table at the current time monitoring point and the core level index of each test table include: matching the core level index of each test table to obtain the threshold for the number of requested test tasks for each test table; comparing the number of requested test tasks for each test table at the current time monitoring point with the threshold for the number of requested test tasks for each test table; if the number of requested test tasks for a certain test table is greater than or equal to the threshold for the number of requested test tasks for that test table, then that test table is not allowed to enter the data processing stage; if the number of requested test tasks for a certain test table is less than the threshold for the number of requested test tasks for that test table, then that test table is allowed to enter the data processing stage.

[0011] Furthermore, the step of real-time monitoring of the core feature parameters of each test table in the specified database to obtain the coreness index of each test table includes: the core feature parameters include the number of associated tables, the number of nested associations, and the number of test data references; obtaining the number of critical associated tables, the number of critical nested associations, and the number of critical test data references from the data management database; and performing ratio processing on the number of associated tables, the number of nested associations, and the number of test data references of each test table with the number of critical associated tables, the number of critical nested associations, and the number of critical test data references, respectively, to further analyze and obtain the coreness index of each test table; the coreness index represents the quantitative data on the degree of influence of the number of associated tables, the number of nested associations, and the number of test data references on the coreness of the test table in the specified database.

[0012] Furthermore, the step of obtaining priority factor data and influence parameters of each requested test task in each test table of a specified database in real time to obtain the priority evaluation value of each requested test task in each test table includes: the priority factor data includes the number of test steps, the number of conditional branches, and the remaining time before the task deadline; the influence parameters of the requested test tasks include the number of dependent tables and the number of dependent tasks; obtaining the number of critical test steps, the number of critical conditional branches, the remaining time before the critical task deadline, the number of critical dependent tables, and the number of critical dependent tasks from the data management database; and comprehensively analyzing the number of test steps and the number of critical test steps, the number of conditional branches and the number of critical conditional branches, the remaining time before the task deadline and the remaining time before the critical task deadline, and the influence parameters of the requested test tasks to obtain the priority evaluation value of each requested test task in each test table. The priority evaluation value represents the quantitative data of the combined influence of the number of test steps, the number of conditional branches, and the remaining time before the task deadline on the urgency of the requested test task.

[0013] Furthermore, the steps for classifying and managing each test table and each requested test task based on the core importance index of each test table and the priority evaluation value of each requested test task in each test table include: classifying each test table according to the core importance index of each test table to obtain each important test table and each unimportant test table, wherein the unimportant test tables are divided into a first unimportant test table and a second unimportant test table; sorting each requested test task from largest to smallest according to the priority evaluation value of each requested test task in each test table to obtain a first ranking of the requested test tasks in each test table; processing the first ranking of the requested test tasks in each test table according to the type of each requested test task to obtain a second ranking of the requested test tasks in each test table; and managing each requested test task according to the second ranking of the requested test tasks in each test table.

[0014] Furthermore, the step of processing the first sort of the request test tasks in each test table according to the type of each request test task to obtain the second sort of the request test tasks in each test table includes: the request test task types include view request tasks and modify request tasks; obtaining the task time data of each view request task in each test table, the task time data including task prediction time and task waiting time; obtaining the critical task prediction time, critical task waiting time and critical priority evaluation value from the data management database; comprehensively analyzing the task time data and priority evaluation value of each view request task in each test table to obtain the priority evaluation value of each view request task in each test table, the priority evaluation value representing the quantitative data of the degree of influence of task prediction time, task waiting time and priority evaluation value on the execution order of view request tasks; processing the first sort of the request test tasks in each test table according to the priority evaluation value of each view request task in each test table to obtain the second sort of the request test tasks in each test table.

[0015] Furthermore, the steps for processing the first ranking of the request test tasks for each test table based on the priority evaluation value of each view request task in each test table to obtain the second ranking of the request test tasks for each test table include: obtaining the priority evaluation threshold from the data management database; comparing the priority evaluation value of each view request task in each test table with the priority evaluation threshold; if the priority evaluation value of a view request task in a certain test table is greater than or equal to the priority evaluation threshold, then moving the order of that view request task to the previous view request ranking; if the priority evaluation value of a view request task in a certain test table is less than the priority evaluation threshold, then no additional operation is performed; and marking the processed ranking of the request test tasks for each test table as the second ranking of the request test tasks for each test table.

[0016] Furthermore, the step of managing each requested test task according to the second ranking of the requested test tasks of each test table includes: performing management operations on each requested test task of each important test table according to the second ranking of the requested test tasks of each important test table, and evaluating and providing feedback on the status of each important test table after the management operations are completed; performing management operations on each requested test task of each non-important test table according to the second ranking of the requested test tasks of each non-important test table and the database status indicators; the management operations include backup, rate limiting, and queuing.

[0017] Furthermore, the steps of monitoring the database status data of a designated database at the current time monitoring point to obtain database status indicators, and determining whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point, include: the database status data, including the task table ratio and the total processing time of requested test tasks, wherein the task table ratio represents the ratio of the number of requested test tasks to the number of test tables; obtaining the critical task table ratio, the critical total processing time of requested test tasks, and the database status indicator threshold from the data management database; obtaining the database status indicator by comprehensively analyzing the ratio of the task table ratio to the critical task table ratio and the ratio of the average of the total processing time of requested test tasks to the average of the critical total processing time of requested test tasks, wherein the database status indicator represents the quantitative data of the degree of influence of the task table ratio and the total processing time of requested test tasks on the database status; comparing the database status indicator with the database status indicator threshold, if the database status indicator is greater than or equal to the database status indicator threshold, then entering the data processing stage, and if the database status indicator is less than the database status indicator threshold, then issuing an abnormal status warning.

[0018] This application provides a test data management system based on database call information, comprising a task classification module, a stage judgment module, a data processing module, a database monitoring module, and a data management database. The task classification module is used to acquire, in real time, all request test tasks and their types at the current time monitoring point for a specified database, and classify them based on the test tables of each request test task at the current time monitoring point to obtain the request test tasks for each test table at the current time monitoring point. The stage judgment module is used to monitor the core feature parameters of each test table in the specified database in real time to obtain the core level index of each test table, and determine the stage based on the number of request test tasks for each test table at the current time monitoring point. The system uses quantity and core performance indicators of each test table to determine whether each test table has entered the data processing stage. The data processing module is used to acquire priority factor data and influence parameters of each requested test task for each test table in a specified database in real time to obtain priority evaluation values ​​for each requested test task in each test table. At the same time, it classifies and manages each test table and each requested test task based on the core performance indicators and priority evaluation values ​​of each requested test task in each test table. The database monitoring module is used to monitor the database status data of a specified database at the current time monitoring point to obtain database status indicators, and determine whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point.

[0019] This application provides a computer-readable storage medium for storing a program, which, when executed by a processor, implements a test data management method based on database retrieval of corresponding information.

[0020] This application provides an electronic device, including: a processor, and a memory for storing processor-executable instructions; when the processor is configured to execute the instructions, the electronic device enables a test data management method based on database retrieval of corresponding information.

[0021] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0022] 1. This invention provides a test data management method and system based on database call information, thereby effectively classifying and managing the request test tasks of each test table, and thus achieving efficient scheduling of database test tasks, optimized resource allocation, and guaranteed system stability, comprehensively improving the efficiency and security of database management.

[0023] 2. This invention performs secondary sorting of the request test tasks in each test table, thereby enabling more refined management of different tasks. This allows for more efficient allocation of resources under different task priorities, optimizes the execution order of tasks, ensures that critical tasks can be processed in a timely manner, avoids resource waste of low-priority tasks, and improves the overall operating efficiency and responsiveness of the system.

[0024] 3. This invention classifies and manages test tables and tasks based on the core level indicators of each test table and the priority evaluation value of each requested test task. This enables accurate identification and processing of key tasks, priority allocation of resources and processing capabilities, and thus achieves more efficient data management and optimized task execution processes, improving the overall system stability and responsiveness. Attached Figure Description

[0025] Figure 1 A flowchart of a test data management method based on database access to corresponding information provided in this application embodiment;

[0026] Figure 2 A graph showing the change in the core index of a test table based on a test data management method, provided in an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of the structure of a test data management system based on database calls for corresponding information, provided in an embodiment of this application. Detailed Implementation

[0028] This application provides a test data management method and system based on database call information. This solves the problem in the prior art where, when processing request test tasks according to queuing order, the queuing tasks are not dynamically adjusted according to demand, leading to some low-priority tasks unnecessarily blocking the execution of high-priority tasks, slowing down the overall processing speed, and resulting in low database management efficiency. The method obtains the request test tasks and their types in a specified database at the current time monitoring point in real time, classifies them based on the test tables of each request test task at the current time monitoring point, and obtains the request test tasks for each test table at the current time monitoring point. It also monitors the core feature parameters of each test table in the specified database in real time to obtain the core degree index of each test table, and then classifies the test tables according to the current time monitoring point. The system determines whether a test table has entered the data processing stage based on the number of requested test tasks and the core competency indicators of each test table. Specifically, the data processing stage involves real-time acquisition of priority factor data and influence parameters for each requested test task in each test table of a specified database to obtain a priority evaluation value. Simultaneously, based on the core competency indicators and priority evaluation values ​​of each requested test task, each test table and request task is categorized and managed. If the system has not entered the data processing stage, it monitors the database status data of the specified database at the current time point to obtain database status indicators. Based on these indicators, it determines whether to issue an abnormal status warning, thereby reducing the overall task processing time and improving database management efficiency.

[0029] The technical solution in this application embodiment addresses the problem that, when processing request test tasks according to queuing order, the failure to dynamically adjust the queuing tasks according to demand leads to some low-priority tasks unnecessarily blocking the execution of high-priority tasks, slowing down the overall processing speed, and resulting in low database management efficiency. The overall approach is as follows:

[0030] By monitoring the request test tasks and task types of a specified database in real time, and classifying test tables based on time monitoring points, the number of request tasks for each test table is obtained. Then, by monitoring the core characteristic parameters of the test tables in real time, the core degree index of each table is evaluated to determine whether it has entered the data processing stage. If it has entered the data processing stage, the priority factors and influencing parameters of the task are obtained, the priority evaluation value is calculated, and the task is classified and managed based on the core degree index and priority. If it has not entered the processing stage, the status index of the specified database is monitored to determine whether an abnormal status warning is needed. This achieves optimized task management, intelligent decision support, and reasonable resource allocation.

[0031] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0032] like Figure 1 The diagram shows a flowchart of a test data management method based on database call information provided in this application embodiment. The method includes the following steps: Real-time acquisition of each requested test task and its type from a specified database at the current time monitoring point; Classification of each requested test task based on its test table at the current time monitoring point, where the test table is used to organize and store structured data related to the test task, the test data is the actual data required for the test task execution, stored in the test table, and the requested test task is the execution unit of the test, relying on the test data stored in the test table to perform specific test operations; Classification of each requested test task with the same test table to obtain the requested test tasks for each test table at the current time monitoring point; Real-time monitoring of the core feature parameters of each test table in the specified database to obtain the relevant information. The system assesses the core competency of each test table and determines whether it has entered the data processing stage based on the number of requested test tasks and the core competency indicators of each test table at the current time monitoring point. If it has entered the data processing stage, the system acquires the priority factor data and influence parameters of each requested test task for each test table in the specified database in real time to obtain the priority evaluation value of each requested test task for each test table. Simultaneously, it categorizes and manages each test table and each requested test task based on the core competency indicators and priority evaluation values ​​of each requested test task for each test table. If it has not entered the data processing stage, the system monitors the database status data of the specified database at the current time monitoring point to obtain the database status indicators and determines whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point.

[0033] In this embodiment, classifying test tables according to requested test tasks allows for precise tracking of the requested test task status of each test table at different time points, ensuring the accuracy and relevance of data processing, as different test tables may carry different test requirements and levels of importance. Determining whether each test table should prioritize entering the data processing stage ensures that critical and urgent data is processed promptly. Upon entering the data processing stage, calculating the priority evaluation value of each requested test task allows for categorized management based on task priority and the core nature of the test table, helping to optimize the data processing flow and ensure the most efficient use of resources. If a test table has not entered the data processing stage, the system continues to monitor the status of the designated database and triggers warnings when necessary, enhancing system stability and reliability, as timely abnormal status warnings help administrators quickly take measures to prevent potential problems from escalating.

[0034] In addition, the designated database is used to store data related to request test tasks and test tables, while the data management database is used to store data related to test data management methods based on database call information, including: the number of critically related tables, the number of critically nested related tables, the number of critical test data references, the core degree index influence factor and priority evaluation threshold corresponding to the number of related tables, etc. The data in the data management database can be directly queried from public databases such as CNKI and Wanfang Data, or it can be obtained by signing data sharing agreements with other organizations or enterprises to mutually open some data resources, so as to achieve data exchange and joint utilization.

[0035] Furthermore, the steps for determining whether each test table should enter the data processing stage based on the number of requested test tasks for each test table at the current time monitoring point and the core level index of each test table include: matching the core level index of each test table to obtain the threshold for the number of requested test tasks for each test table; comparing the number of requested test tasks for each test table at the current time monitoring point with the threshold for the number of requested test tasks for each test table; if the number of requested test tasks for a certain test table is greater than or equal to the threshold for the number of requested test tasks for that test table, then that test table is not allowed to enter the data processing stage; if the number of requested test tasks for a certain test table is less than the threshold for the number of requested test tasks for that test table, then that test table is allowed to enter the data processing stage.

[0036] In this embodiment, the request test task quantity threshold represents a critical value for the number of request test tasks that the test table can handle. A mapping set of request test task quantity thresholds corresponding to each core level indicator is obtained from the data management database. This mapping set is obtained by mapping each core level indicator to each request test task quantity threshold. When obtaining the request test task quantity threshold for each test table, the core level indicator of each test table is input into the mapping set to obtain the request test task quantity threshold corresponding to each core level indicator. By comparing the request test task quantity of each test table at the current time monitoring point with the request test task quantity threshold of each test table, priority processing of core tables can be ensured, guaranteeing the quality of data processing, improving the overall utilization of database resources, and enhancing system stability.

[0037] Furthermore, the step of real-time monitoring of the core feature parameters of each test table in the specified database to obtain the coreness index of each test table includes: the core feature parameters include the number of associated tables, the number of nested associations, and the number of test data references; obtaining the number of critical associated tables, the number of critical nested associations, and the number of critical test data references from the data management database; and performing ratio processing on the number of associated tables, the number of nested associations, and the number of test data references of each test table with the number of critical associated tables, the number of critical nested associations, and the number of critical test data references, respectively, to further analyze and obtain the coreness index of each test table. The coreness index represents the quantitative data on the degree of influence of the number of associated tables, the number of nested associations, and the number of test data references on the coreness of the test table in the specified database.

[0038] In this embodiment, the number of associated tables refers to the number of other tables directly related to a test table. These associations can be established through foreign keys, references, joins, etc., and can be directly obtained by querying the number of foreign key constraints and JOIN conditions between tables in the database. The number of nested associations refers to the number of tables associated with the target table that have deeper levels of association. This can be obtained by recursively querying multi-level associations in the database to obtain the hierarchical structure of table nesting. The number of test data references refers to the total number of times all test data in a test table is referenced by other tables and tasks in the system. This can be directly obtained by analyzing SQL query logs and database dependencies. These three are interrelated. For example, if a test table has established foreign key associations or references with multiple tables, its data may be used by more queries, operations, or tasks. Therefore, the more associated tables there are, the higher the number of test data references. The more nested associations there are, the more data and queries are involved, leading to an increase in the number of references. The core index obtained from comprehensive analysis can help identify the core test tables and data in the system. At the same time, by understanding the relationships and references between each table, task scheduling and resource allocation can be optimized to ensure that important tasks are processed first. Based on the core index, the priority of data processing can be adjusted to ensure that complex or highly dependent tasks are processed in a timely manner and to avoid system bottlenecks.

[0039] The core indicators for each test table are obtained as follows:

[0040] ;

[0041] In the formula, This represents the coreness index of the i-th test table. This indicates the core level indicator impact factor corresponding to the number of related tables. The core degree indicator influencing factor represents the number of nested relationships. This indicates the core index influence factor corresponding to the number of times test data is cited. This represents the number of associated tables for the i-th test table. Indicates the number of critically related tables. This represents the number of nested relationships in the i-th test table. Indicates the critical number of nested associations. This represents the number of times the test data in the i-th test table has been referenced. This indicates the number of times the critical test data is referenced, where i is the number of each test table, i=1,2,3,...,Z, and Z is the total number of test tables. The sinh function is a hyperbolic sine function, which is convenient for querying the relationship between the core feature parameters and the core degree index.

[0042] , and These are the core severity index influence factors corresponding to the number of associated tables, the number of nested associations, and the number of test data references preset in the data management database. These influence factors are numerical indicators that measure the magnitude of the influence of the aforementioned core characteristic parameters on the core severity index. Specifically, there is a mapping relationship table for the number of associated tables, the number of nested associations, and the number of test data references. The table records each possible core characteristic parameter value and its corresponding core severity index influence factor. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the core severity index of a certain test table, the measured number of associated tables, the number of nested associations, and the number of test data references can be entered into their respective mapping relationship tables to quickly find the core severity index influence factors corresponding to these values. The influence factors range from 0 to 1.

[0043] The impact factor for the coreity index corresponding to the number of associated tables is set to 0.3, the impact factor for the coreity index corresponding to the number of nested associations is set to 0.3, and the impact factor for the coreity index corresponding to the number of test data citations is set to 0.4. The number of associated tables for the i-th test table is set to 5, the number of critical associated tables is set to 3, the number of nested associations for this test table is set to 3, the number of critical nested associations is set to 3, and the critical number of test data citations is set to 50. As the number of test data citations for this test table continuously increases, the coreity index of this test table is calculated. Table 1 shows the coreity index data of test tables based on the test data management method.

[0044] Table 1. Data Table of Core Indicators for Test Tables Based on Test Data Management Methods

[0045] serial number <![CDATA[RD 1i ]]> <![CDATA[CL i <!-- 7 -->]]> 1 30 1.238 2 40 1.369 3 50 1.509 4 60 1.659 5 70 1.820

[0046] like Figure 2 As shown in Table 1, this is a graph illustrating the changes in the core index of the test table based on the test data management method provided in this application embodiment. Figure 2 It can be seen that when the number of core degree index influence factors corresponding to the number of associated tables, the number of nested associations, the number of test data citations, the number of associated tables of the i-th test table, the number of critical associated tables, the number of nested associations of the test table, the number of critical nested associations, and the number of critical test data citations remain unchanged, and the number of test data citations of the test table continuously increases, the core degree index of the test table also continuously increases.

[0047] Furthermore, the step of obtaining priority factor data and influence parameters of each requested test task in each test table of a specified database in real time to obtain the priority evaluation value of each requested test task in each test table includes: the priority factor data includes the number of test steps, the number of conditional branches, and the remaining time before the task deadline; the influence parameters of the requested test tasks include the number of dependent tables and the number of dependent tasks; obtaining the number of critical test steps, the number of critical conditional branches, the remaining time before the critical task deadline, the number of critical dependent tables, and the number of critical dependent tasks from the data management database; and comprehensively analyzing the number of test steps and the number of critical test steps, the number of conditional branches and the number of critical conditional branches, the remaining time before the task deadline and the remaining time before the critical task deadline, and the influence parameters of the requested test tasks to obtain the priority evaluation value of each requested test task in each test table. The priority evaluation value represents the quantitative data of the combined influence of the number of test steps, the number of conditional branches, and the remaining time before the task deadline on the urgency of the requested test task.

[0048] In this embodiment, the number of test steps refers to the number of specific steps or operations contained in a test task, which can be counted by analyzing the steps in test case documents, test plans, or automated test scripts; the number of conditional branches refers to the number of decision points in the test task, which can be obtained directly by analyzing branch statements (such as if, else, switch, etc.) in the test code; the remaining deadline refers to the remaining time between the current time and the deadline of the test task, which can be obtained by querying the deadline in the task scheduling system, project management tools, or test management system and calculating the difference between the current time and the deadline. These three are interrelated. For example, a test task with more test steps may have more conditional branches because more operation steps may lead to more decisions; if there are many test steps or many conditional branches, it usually means that the task is complex and requires more time, but if the remaining deadline of the task is short, it must be processed first, even if it is complex.

[0049] The impact parameters of request test tasks quantify the dependency impact of request test tasks on the priority evaluation value of request test tasks, allowing for dynamic adjustment of the priority evaluation value. The number of dependent tables refers to the number of tables in a specified database required by a test task, which can be obtained by analyzing the business logic or SQL queries of the test task. The number of dependent tasks refers to the number of other tasks that need to be completed before a test task can be completed, which can be directly queried using the task management module built into the specified database. These two are interrelated; generally, tasks that depend on more tables may also require more tasks to complete, as complex data requirements may require more complex preconditions or dependent tasks. The comprehensive analysis of the impact parameters of request test tasks helps assess the complexity of tasks and their dependence on the system, thereby further determining their priority. Based on the priority factor data of each request test task in each test table and the comprehensive analysis of the impact parameters of each request test task, the priority evaluation value of each request test task in each test table can be determined, preventing low-priority tasks from consuming excessive resources and ensuring that critical tasks can be executed on time. It also provides a clear view of the dependencies between tasks, helping to predict potential delays and adjust plans accordingly.

[0050] The priority evaluation value of each request test task in each test table is obtained in the following way:

[0051] ;

[0052] ;

[0053] In the formula, This represents the priority evaluation value of the k-th request test task in the i-th test table. This indicates the priority evaluation impact factor corresponding to the number of test steps. This indicates the priority evaluation impact factor corresponding to the number of conditional branches. This indicates the priority assessment impact factor corresponding to the remaining time before the task deadline. This represents the number of test steps for the k-th request test task in the i-th test table. Indicates the number of critical test steps. This represents the number of conditional branches for the k-th request test task in the i-th test table. Indicates the number of critical condition branches. This represents the remaining time until the deadline for the k-th request test task in the i-th test table. This indicates the remaining time until the critical task deadline. This represents the parameter affected by the k-th request test task in the i-th test table. This represents the impact factor of the request test task parameter corresponding to the number of dependency tables. This represents the impact factor of the request test task parameter corresponding to the number of dependent tasks. This represents the number of tables that the i-th test table depends on for the k-th request test task. This indicates the number of critical dependency tables. This represents the number of tasks that the k-th request test task in the i-th test table depends on. This represents the number of critical dependent tasks, e is a natural constant, k is the number of each requested test task, k=1,2,3,...,K, K is the total number of requested test tasks, and the tanh function is the hyperbolic tangent function, which normalizes the priority evaluation values ​​of each requested test task in each test table so that higher and lower evaluation values ​​can be reasonably represented within the range.

[0054] , and These are priority evaluation influencing factors preset in the data management database for the number of test steps, the number of conditional branches, and the remaining task deadline. These influencing factors are numerical indicators that measure the magnitude of the impact of the aforementioned priority factors on the priority evaluation value. Specifically, there is a mapping relationship table for the number of test steps, the number of conditional branches, and the remaining task deadline. The table records each possible priority factor data value and its corresponding priority evaluation influencing factor. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the priority evaluation value of a specific test task in a certain test table, the measured number of test steps, the number of conditional branches, and the remaining task deadline can be entered into their respective mapping relationship tables to quickly find the priority evaluation influencing factors corresponding to these values. The value range of the influencing factors is between 0 and 1.

[0055] and These are the impact factors of the request test task influence parameters, corresponding to the preset number of dependent tables and dependent tasks in the data management database. These impact factors are numerical indicators that measure the magnitude of the influence of the aforementioned request test task influence parameters on the overall request test task influence parameters. Specifically, there is a mapping table for the number of dependent tables and the number of dependent tasks. The tables record each possible number of dependent tables and dependent tasks and their corresponding request test task influence parameter impact factors. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the influence parameter of a specific request test task for a particular test table, the measured number of dependent tables and the number of dependent tasks can be entered into their respective mapping tables to quickly find the corresponding request test task influence parameter impact factors. The value of the influence factor ranges from 0 to 1.

[0056] Furthermore, the steps for classifying and managing each test table and each requested test task based on the core level indicators of each test table and the priority evaluation values ​​of each requested test task for each test table include: classifying each test table according to its core level indicators; comparing the core level indicators of each test table with the core level indicator thresholds obtained from the data management database; if the core level indicator of a test table is greater than or equal to the core level indicator threshold, the test table is marked as an important test table; if the core level indicator of a test table is less than the core level indicator threshold, the test table is marked as an unimportant test table; statistically analyzing each important test table and each unimportant test table, the unimportant test tables are divided into a first unimportant test table and a second unimportant test table; sorting each requested test task from highest to lowest priority evaluation value for each requested test task for each test table to obtain a first ranking of the requested test tasks for each test table; processing the first ranking of the requested test tasks for each test table according to the type of each requested test task to obtain a second ranking of the requested test tasks for each test table; and managing each requested test task according to the second ranking of the requested test tasks for each test table.

[0057] In this embodiment, the first sorting of request test tasks involves initially ranking all request test tasks according to priority. The second sorting modifies the ranking of view request test tasks that can be executed earlier within the target time period, moving them to the currently processed view request test task ranking for simultaneous processing. By prioritizing important and urgent test tasks, time and resources can be utilized more effectively, reducing unnecessary delays and waste. Allocating resources based on the core nature of the test table and the priority of the request test tasks ensures that critical tasks receive sufficient attention and support. Furthermore, a clear classification and management process helps project managers better track and control test progress, and adjust strategies in a timely manner to address potential risks and challenges.

[0058] Furthermore, the step of processing the first sort of the request test tasks in each test table according to the type of each request test task to obtain the second sort of the request test tasks in each test table includes: the request test task types include view request tasks and modify request tasks; obtaining the task time data of each view request task in each test table, the task time data including task prediction time and task waiting time; obtaining the critical task prediction time, critical task waiting time and critical priority evaluation value from the data management database; comprehensively analyzing the task time data and priority evaluation value of each view request task in each test table to obtain the priority evaluation value of each view request task in each test table, the priority evaluation value representing the quantitative data of the degree of influence of task prediction time, task waiting time and priority evaluation value on the execution order of view request tasks; processing the first sort of the request test tasks in each test table according to the priority evaluation value of each view request task in each test table to obtain the second sort of the request test tasks in each test table.

[0059] In this embodiment, the task prediction time includes the prediction time of the view request task to be processed and the prediction time of the view request task to be processed. When the first request test task in the sorting is a view request task, a secondary sorting process is performed. Simultaneously, a task length threshold is retrieved from the data management database as an adjustable task range. It is then determined whether other view request tasks exist within the task length threshold range of the first request test task. If so, these other view request tasks are merged into the current view request task order. The task time data mainly reflects the time requirements and waiting time of each request test task. The task prediction time is the estimated time required to complete the task, which can be calculated based on the average execution time of historical tasks of the same type. The task waiting time is the time the task has been waiting to be executed at the current time monitoring point, which can be directly queried from the database. By combining task time data with priority evaluation values, the system can better allocate resources and avoid resource conflicts between urgent and complex tasks.

[0060] The priority evaluation value of each viewing request task in each test table is obtained in the following way:

[0061] ;

[0062] ;

[0063] In the formula, This represents the priority evaluation value of the j-th view request test task in the i-th test table. This indicates the priority assessment factor corresponding to the task prediction time. This indicates the priority assessment factor corresponding to the task waiting time. This indicates the priority assessment impact factor corresponding to the priority assessment value. This represents the predicted time for the j-th view request test task in the i-th test table. This indicates the predicted time for critical tasks. This represents the waiting time for the j-th view request test task in the i-th test table. This indicates the waiting time for critical tasks. This represents the priority evaluation value of the j-th view request test task in the i-th test table. This represents the critical priority evaluation value. This indicates the predicted time for the j-th view request task to be processed in the i-th test table. This represents the predicted time for the j-th pending view request task in the i-th test table, where j is the view request task number, j=1,2,3,...,M, and M is the total number of view request tasks.

[0064] , and These are priority evaluation influencing factors corresponding to the pre-set task prediction time, task waiting time, and priority evaluation value in the data management database. These influencing factors are numerical indicators that measure the magnitude of the influence of the aforementioned parameters on the priority evaluation value. Specifically, each of the task prediction time, task waiting time, and priority evaluation value has a mapping relationship table. The tables record each possible parameter value and its corresponding priority evaluation influencing factor. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the priority evaluation value of a specific test task in a test table, the measured task prediction time, task waiting time, and priority evaluation value can be entered into their respective mapping relationship tables to quickly find the corresponding priority evaluation influencing factors. The values ​​of these influencing factors range from 0 to 1.

[0065] Furthermore, the steps for processing the first ranking of the request test tasks for each test table based on the priority evaluation value of each view request task in each test table to obtain the second ranking of the request test tasks for each test table include: obtaining the priority evaluation threshold from the data management database; comparing the priority evaluation value of each view request task in each test table with the priority evaluation threshold; if the priority evaluation value of a view request task in a certain test table is greater than or equal to the priority evaluation threshold, then moving the order of that view request task to the previous view request ranking; if the priority evaluation value of a view request task in a certain test table is less than the priority evaluation threshold, then no additional operation is performed; and marking the processed ranking of the request test tasks for each test table as the second ranking of the request test tasks for each test table.

[0066] In this embodiment, the priority evaluation threshold is a preset value used to assess whether the view request test task has a higher priority. Since the completion time of the view request test task is much shorter than that of the modify request test task, prioritizing the view request test tasks helps to allocate time for computation reasonably, reduces waiting time during resource contention, and thus reduces the overall processing time of the tasks, thereby improving the efficiency of database management.

[0067] Furthermore, the step of managing each requested test task according to the second ranking of the requested test tasks of each test table includes: performing management operations on each requested test task of each important test table according to the second ranking of the requested test tasks of each important test table, and evaluating and providing feedback on the status of each important test table after the management operations are completed; performing management operations on each requested test task of each non-important test table according to the second ranking of the requested test tasks of each non-important test table and the database status indicators; the management operations include backup, rate limiting, and queuing.

[0068] In this embodiment, when managing each request test task, multiple view request test tasks with adjacent order can be performed simultaneously. Specifically, for each important test table, high-frequency backups (e.g., once per minute) are required. Then, each request test task is processed according to the second order of request test tasks for each important test table, with a restriction that only one modification request test task can be performed at a time. After the management operation is completed, the test data content of each important test table is obtained and compared according to the order. If abnormal test data content is found, the test data is immediately replaced with the previous backup content, and error alerts are issued for completed request test tasks with abnormal content according to the order. For the first non-important test table, differential backup (only recording data that has changed since the last backup) can be used, and the restriction is relaxed to 20 modification requests per second. For the second non-important test table, a simpler backup method can be used (e.g., a full backup once a week), and rate limiting is only applied when the database status indicator exceeds the database status indicator threshold; otherwise, no rate limiting is applied.

[0069] Furthermore, the steps of monitoring the database status data of a designated database at the current time monitoring point to obtain database status indicators, and determining whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point, include: the database status data, including the task table ratio and the total processing time of requested test tasks, wherein the task table ratio represents the ratio of the number of requested test tasks to the number of test tables; obtaining the critical task table ratio, the critical total processing time of requested test tasks, and the database status indicator threshold from the data management database; obtaining the database status indicator by comprehensively analyzing the ratio of the task table ratio to the critical task table ratio and the ratio of the average of the total processing time of requested test tasks to the average of the critical total processing time of requested test tasks, wherein the database status indicator represents the quantitative data of the degree of influence of the task table ratio and the total processing time of requested test tasks on the database status; comparing the database status indicator with the database status indicator threshold, if the database status indicator is greater than or equal to the database status indicator threshold, then entering the data processing stage, and if the database status indicator is less than the database status indicator threshold, then issuing an abnormal status warning.

[0070] In this embodiment, a higher task-table ratio means more tasks are processed on each table, which may increase the database load and thus lower the database status index. The total processing time for request test tasks may indicate poor system performance or high load, resulting in delayed task processing and also lower database status indexes. These two are interrelated; when the task-table ratio increases, more tasks may need to be processed on a single table, potentially increasing the total processing time. By analyzing the relationship between the task-table ratio and the total processing time for request test tasks, the database performance under different loads can be determined.

[0071] The database status indicators are obtained in the following ways:

[0072] ,

[0073] In the formula, Indicates database status metrics. This indicates the influence factor of the task table compared to the corresponding database status indicator. This represents the database status metric impact factor corresponding to the total processing time of the request test task. Indicates the ratio of task lists, This indicates the ratio of critical tasks. This indicates the total processing time for the requested test task. This indicates the total processing time for the critical request test task.

[0074] and These are the database status indicator influence factors corresponding to the pre-defined task table ratio and total processing time of request test tasks in the data management database. These influence factors are numerical indicators that measure the magnitude of the impact of the aforementioned database status data on the priority evaluation value. Specifically, there is a mapping relationship table for both the task table ratio and the total processing time of request test tasks. These tables record each possible database status data value and its corresponding database status indicator influence factor. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate database status indicators, the measured task table ratio and total processing time of request test tasks can be entered into their respective mapping relationship tables to quickly find the corresponding database status indicator influence factors. The influence factors range from 0 to 1.

[0075] like Figure 3The diagram shows the structure of a test data management system based on database call information provided in this embodiment of the application. The test data management system includes: a task classification module, a stage judgment module, a data processing module, a database monitoring module, and a data management database. The task classification module is used to obtain in real-time the request test tasks and their types at the current time monitoring point of a specified database, and classifies them based on the test tables of each request test task at the current time monitoring point to obtain the request test tasks for each test table at the current time monitoring point. The stage judgment module is used to monitor the core feature parameters of each test table in the specified database in real-time to obtain the core degree index of each test table, and classify them according to the current... The number of requested test tasks for each test table at each time monitoring point and the core level index of each test table determine whether each test table has entered the data processing stage. The data processing module is used to acquire priority factor data and influence parameters of each requested test task for each test table in a specified database in real time to obtain priority evaluation values ​​for each requested test task in each test table. At the same time, it classifies and manages each test table and each requested test task based on the core level index and priority evaluation values ​​of each requested test task in each test table. The database monitoring module is used to monitor the database status data of a specified database at the current time monitoring point to obtain database status indicators, and determine whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point.

[0076] In summary, this embodiment of the application obtains the request test tasks and their types for a specified database at the current time monitoring point in real time, classifies the test tables of each request test task at the current time monitoring point, and obtains the request test tasks for each test table at the current time monitoring point; it monitors the core feature parameters of each test table in the specified database in real time to obtain the core degree index of each test table, and determines whether each test table enters the data processing module based on the number of request test tasks and the core degree index of each test table at the current time monitoring point; if it enters the data processing module, it obtains the priority factor data and influence parameters of each request test task for each test table in the specified database in real time to obtain the priority evaluation value of each request test task for each test table, and classifies and manages each test table and each request test task based on the core degree index and the priority evaluation value of each request test task for each test table; if it does not enter the data processing module, it monitors the database status data of the specified database at the current time monitoring point to obtain the database status index, and determines whether to issue an abnormal status warning based on the database status index at the current time monitoring point, thereby reducing the overall processing time of tasks and improving the efficiency of database management.

[0077] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.

[0078] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0079] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0081] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0082] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A test data management method based on database retrieval of corresponding information, characterized in that, Includes the following steps: The system acquires the request test tasks and their types from the specified database at the current time monitoring point in real time. Based on the test tables of the request test tasks at the current time monitoring point, the system categorizes the request test tasks for each test table at the current time monitoring point. Real-time monitoring of the core characteristic parameters of each test table in the specified database to obtain the coreness index of each test table, and determining whether each test table has entered the data processing stage based on the number of requested test tasks and the coreness index of each test table at the current time monitoring point. If the data processing stage is entered, priority factor data and impact parameters of each requested test task in each test table of the specified database are obtained in real time to obtain priority evaluation values ​​of each requested test task in each test table. At the same time, each test table and each requested test task are classified and managed based on the core degree index of each test table and the priority evaluation values ​​of each requested test task in each test table. If the data processing stage has not yet begun, the database status data of the specified database at the current time monitoring point will be monitored to obtain database status indicators, and an abnormal status warning will be issued based on the database status indicators at the current time monitoring point. The steps for determining whether each test table should enter the data processing stage based on the number of requested test tasks for each test table at the current time monitoring point and the coreness index of each test table include: The threshold for the number of request test tasks for each test table is obtained by matching the coreness index of each test table. The number of requested test tasks for each test table at the current time monitoring point is compared with the threshold number of requested test tasks for each test table. If the number of requested test tasks for a test table is greater than or equal to the threshold number of requested test tasks for that test table, then that test table is not allowed to enter the data processing stage. If the number of requested test tasks for a test table is less than the threshold number of requested test tasks for that test table, then that test table is allowed to enter the data processing stage. The step of obtaining priority factor data and influence parameters of each requested test task in each test table of a specified database in real time to obtain priority evaluation values ​​for each requested test task in each test table includes: The priority factor data includes the number of test steps, the number of conditional branches, and the remaining time before the task deadline; The parameters affected by the request test task include the number of dependency tables and the number of dependency tasks; Retrieve the number of critical test steps, the number of critical condition branches, the remaining time before the deadline for critical tasks, the number of critical dependency tables, and the number of critical dependency tasks from the data management database; Based on the number of test steps and critical test steps, the number of conditional branches and critical conditional branches, the remaining time before the task deadline and the remaining time before the critical task deadline, and the influence parameters of the requested test tasks, a comprehensive analysis is conducted to obtain the priority evaluation value of each requested test task in each test table.

2. The test data management method based on database call of corresponding information as described in claim 1, characterized in that: The steps for real-time monitoring of the core feature parameters of each test table in a specified database to obtain the coreness index of each test table include: The core feature parameters include the number of associated tables, the number of nested associations, and the number of times test data is referenced; Retrieve the number of critically related tables, the number of critically nested relationships, and the number of critical test data references from the data management database; The coreness index of each test table is obtained by comparing the number of related tables, the number of nested related tables, and the number of test data references of each test table with the number of critical related tables, the number of critical nested related tables, and the number of critical test data references, respectively. The core importance index of each test table is used to quantify the importance of the test table in the database environment.

3. The test data management method based on database access to corresponding information as described in claim 1, characterized in that: The steps for classifying and managing each test form and each requested test task based on the coreity index of each test form and the priority evaluation value of each requested test task in each test form include: Based on the coreness index of each test form, the test forms are classified into important test forms and unimportant test forms. The unimportant test forms are further divided into first unimportant test forms and second unimportant test forms. Based on the priority evaluation value of each request test task in each test table, sort the request test tasks from largest to smallest to obtain the first priority of each test table's request test tasks. The first sort of the request test tasks in each test table is processed according to the type of each request test task to obtain the second sort of the request test tasks in each test table. The request test tasks are managed according to the second sorting of the request test tasks in each test form.

4. The test data management method based on database call of corresponding information as described in claim 3, characterized in that: The step of processing the first sorting of the request test tasks in each test table according to the type of each request test task to obtain the second sorting of the request test tasks in each test table includes: The request test task types include viewing request tasks and modifying request tasks; Obtain the task time data for each viewing request task in each test table. The task time data includes the task prediction time and the task waiting time. The critical task prediction time, critical task waiting time, and critical priority evaluation value are obtained from the data management database. Based on the task time data of each viewing request task in each test table and the priority evaluation value of each viewing request task in each test table, the priority evaluation value of each viewing request task in each test table is obtained through comprehensive analysis. Based on the priority evaluation value of each viewing request task in each test table, the first ranking of the request test tasks for each test table is processed to obtain the second ranking of the request test tasks for each test table.

5. The test data management method based on database call of corresponding information as described in claim 4, characterized in that: The step of processing the first ranking of the request test tasks for each test table based on the priority evaluation value of each view request task for each test table, and obtaining the second ranking of the request test tasks for each test table, includes: Obtain priority assessment thresholds from the data management database; The priority evaluation value of each viewing request task in each test table is compared with the priority evaluation threshold. If the priority evaluation value of a viewing request task in a certain test table is greater than or equal to the priority evaluation threshold, the order of the viewing request task is moved to the previous viewing request sorting. If the priority evaluation value of a viewing request task in a certain test table is less than the priority evaluation threshold, no additional operation is performed. The sorting and marking of the request test tasks for each processed test table is designated as the second sorting of request test tasks for each test table.

6. The test data management method based on database call of corresponding information as described in claim 3, characterized in that: The step of managing each requested test task according to the second sorting of the requested test tasks in each test table includes: Based on the second priority of the request test tasks for each important test form, the management operations for each request test task for each important test form are performed, and the status of each important test form is evaluated and feedback is provided after the management operations are completed. Based on the second sorting of the request test tasks for each non-critical test table and the database status indicators, manage the request test tasks for each non-critical test table. The management operations include backup, rate limiting, and queuing.

7. The test data management method based on database call of corresponding information as described in claim 1, characterized in that: The steps of monitoring the database status data of a specified database at the current time monitoring point to obtain database status indicators, and determining whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point, include: The database status data includes the task table ratio and the total processing time for requested test tasks. The task table ratio represents the ratio of the number of requested test tasks to the number of test tables. Obtain the critical task table ratio, total processing time of critical request test tasks, and database status indicator thresholds from the data management database; Database status indicators are obtained through comprehensive analysis of the ratio of task list to critical task list and the ratio of total processing time of request test tasks to the average total processing time of critical request test tasks. The database status indicators are compared with the database status indicator thresholds. If the database status indicators are greater than or equal to the database status indicator thresholds, the data processing stage begins. If the database status indicators are less than the database status indicator thresholds, an abnormal status warning is issued.

8. A test data management system based on database retrieval of corresponding information, employing the test data management method based on database retrieval of corresponding information as described in any one of claims 1-7, characterized in that: It includes a task classification module, a stage judgment module, a data processing stage, a database monitoring stage, and a data management database; The task classification module is used to obtain in real time the request test tasks and the types of each request test task in the specified database at the current time monitoring point, and classify them based on the test tables of each request test task at the current time monitoring point to obtain the request test tasks of each test table at the current time monitoring point. The stage judgment module is used to monitor the core feature parameters of each test table in the specified database in real time to obtain the core degree index of each test table, and to determine whether each test table has entered the data processing stage based on the number of requested test tasks and the core degree index of each test table at the current time monitoring point. The data processing stage is used to obtain in real time the priority factor data and the influence parameters of each requested test task in each test table of the specified database to obtain the priority evaluation value of each requested test task in each test table. At the same time, based on the core degree index of each test table and the priority evaluation value of each requested test task in each test table, the test tables and each requested test task are classified and managed. The database monitoring phase is used to monitor the database status data of a specified database at the current time monitoring point to obtain database status indicators, and to determine whether to issue an abnormal status warning based on the database status indicators at the current time monitoring point.

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