Test method and system

Abstract

The embodiments of this specification provide a testing method and system, wherein the testing method includes: determining a test point factor for a target function included in an updated target system, and performing a regression test on the test point factor. Based on the target function and the test point factor, global test data is acquired, and the global test data is standardized to obtain data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

Description

Technical Field

[0001] The embodiments of the present specification relate to the field of computer technology, and more particularly to testing methods and systems. Background Art

[0002] Regression testing is used to test whether the update of functions will cause new problems when the functions are updated. It is usually necessary to generate test cases to complete functional testing, and the test cases can be constructed based on the desensitized test data. In the prior art, full data is usually obtained according to the business scope, and regression testing of functions is performed based on the full data. However, this method has a long testing cycle and low testing efficiency. In the case of regression testing of functions based on partial data, the comprehensiveness of the test will be reduced because the selected partial data cannot cover more test points. Therefore, a more effective testing method is urgently needed to solve the above problems. Summary of the invention

[0003] In view of this, an embodiment of this specification provides a testing method. One or more embodiments of this specification also relate to a testing system, a testing device, a computing device, a computer-readable storage medium and a computer program product to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, a testing method is provided, including:

[0005] Determine test point factors for target functions included in the updated target system;

[0006] Acquire global test data based on the target function and the test point factor, and standardize the global test data to obtain data to be trimmed;

[0007] The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and target data is determined according to the trimming results;

[0008] A functional test task corresponding to the target function is executed based on the target data.

[0009] According to a second aspect of an embodiment of this specification, a testing system is provided, including a business party and a service end;

[0010] The business party is used to submit a test request to the server for the updated target system;

[0011] The server is used to determine the test point factor for the target function included in the updated target system based on the test request; obtain global test data based on the target function and the test point factor, and standardize the global test data to obtain the data to be trimmed; trim the data to be trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and determine the target data according to the trimming results; execute the functional test task corresponding to the target function based on the target data, obtain the test result and send the test result to the business party.

[0012] According to a third aspect of an embodiment of this specification, a testing device is provided, including:

[0013] A determination module is configured to determine a test point factor for a target function included in the updated target system;

[0014] An acquisition module is configured to acquire global test data based on the target function and the test point factor, and to standardize the global test data to obtain data to be trimmed;

[0015] A clipping module is configured to clip the to-be-cut data in sequence based on at least two data clipping sub-strategies included in the data clipping strategy, and determine target data according to the clipping result;

[0016] An execution module is configured to execute a functional test task corresponding to the target function based on the target data.

[0017] According to a fourth aspect of an embodiment of this specification, a computing device is provided, including:

[0018] Memory and processor;

[0019] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above-mentioned testing method are implemented.

[0020] According to a fifth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned test method are implemented.

[0021] According to a sixth aspect of the embodiments of this specification, a computer program product is provided, including a computer program or instructions, which implement the steps of the above-mentioned test method when executed by a processor.

[0022] A test method provided by an embodiment of the present specification determines test point factors for a target function included in an updated target system, and performs regression testing on the test point factors. Global test data is acquired based on the target function and the test point factors, and the global test data is standardized to obtain data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic diagram of a testing method provided by an embodiment of this specification;

[0024] Figure 2 is a flow chart of a testing method provided by an embodiment of this specification;

[0025] Figure 3 is a processing flow chart of a testing method provided by an embodiment of this specification;

[0026] Figure 4 It is a schematic diagram of object clipping of a test method provided by an embodiment of this specification;

[0027] Figure 5 It is a time clipping schematic diagram of a test method provided by an embodiment of this specification;

[0028] Figure 6 It is a combined cutting schematic diagram of a test method provided by an embodiment of this specification;

[0029] Figure 7 is a structural schematic diagram of a test system provided by an embodiment of this specification;

[0030] Figure 8 is a structural schematic diagram of a testing device provided by an embodiment of this specification;

[0031] Fig. 9 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0032] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0033] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0034] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0035] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0036] The testing method provided by one or more embodiments of the present specification can cover a larger test range of the target system with a smaller amount of data after the target system is updated, and ensure the accuracy of the test of the updated target system. Figure 1A schematic diagram of a testing method provided according to an embodiment of the present specification is shown, in which test point factors are determined for target functions included in an updated target system, and regression tests are performed on the test point factors. Global test data after data desensitization is obtained based on the target function and the test point factor, and the global test data is standardized to obtain data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

[0037] In this specification, a testing method is provided. This specification also relates to a testing system, a testing apparatus, a computing device, a computer-readable storage medium and a computer program product, which are described in detail one by one in the following embodiments.

[0038] See also Figure 2 , Figure 2 A flow chart of a testing method provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0039] Step 202: Determine test point factors for target functions included in the updated target system.

[0040] Specifically, the target system can be a business system in the fields of finance, e-commerce, teaching, games, etc. After the target system is updated, in order to ensure that the updated target system can provide services normally, it is necessary to perform regression testing on the updated target system to test whether new functional anomalies and logic processing errors are introduced after the target system is updated. The target function refers to the function provided in the target system that includes data processing and / or logic processing. The test point factor can be an element that affects the core direction of the target system program.

[0041] Based on this, after the target system is updated, the multiple functions included in the updated target system are determined, the target function that needs to be regression tested is selected from the multiple functions, and the test point factors included in the target function are determined. Data collection and analysis are performed on the test point factors, and full coverage test data is screened to perform regression testing on the target function.

[0042] In practical applications, before performing regression testing on the target function, the test coverage dimensions of the target function can be analyzed, and the components of the test point factors of each test coverage dimension can be defined. Then, SQL statements for data collection can be created based on the test point factors to achieve efficient extraction of globally standardized test data.

[0043] Step 204: Acquire global test data based on the target function and the test point factor, and standardize the global test data to obtain data to be trimmed.

[0044] Specifically, after determining the test point factors for the target functions included in the updated target system, global test data can be obtained based on the target functions and test point factors, and the global test data can be standardized to obtain the data to be trimmed, wherein the global test data is the global historical data that has been generated for the associated target functions and test point factors obtained in the system database of the target system. The global test data is used to perform regression testing on the test point factors of the target function. The global test data can be data collected within a set time interval for the target function, and the set time interval can be a time interval such as one month, one year, or two years. The standardized processing of the global test data can be clustering the global test data, summarizing and counting the dates and frequencies of the test point codes in the global test data. The data to be trimmed refers to the test data that still needs to be conditionally filtered or conditionally screened after the global test data is standardized. The data to be trimmed can be directly used for the test of the target function after trimming.

[0045] Based on this, after determining the test point factors for the target functions included in the updated target system, the global test data within the preset time interval is obtained based on the target functions and the test point factors, and the global test data is standardized. The objects and dates associated with the test point codes in the global test data are summarized and counted, and the frequency of occurrence corresponding to each test point code is obtained, and the data to be trimmed containing the global test data and frequency data is obtained.

[0046] Furthermore, considering that the amount of global test data involved in the target function and test point factors is large, the global test data can be obtained by constructing and executing data query statements, which is specifically implemented as follows:

[0047] Determine the function identifier of the target function and the test point factor corresponding to the target function; construct a data query statement based on the function identifier and the test point factor; and obtain the global test data by executing the data query statement against the system database of the target system.

[0048] Specifically, the function identifier is used to mark the target function among the multiple functions included in the target system. The function identifier can be a function code, the test point factor can be expressed in the form of code, and the data query statement can be an SQL statement used to perform conditional data query in a database or data set. The system database is used to store data generated during the operation of the target system.

[0049] Based on this, determine the function identifier of the target function and the test point factor corresponding to the target function. Use the function identifier and test point factor as query conditions and the system database of the target system as the query object to construct a data query statement. Global test data can be queried by executing the data query statement against the system database of the target system.

[0050] For example, when the target system is an accounting system in the financial field, the target function can be an accounting calculation function, and the functional test coverage rule identifier can be the rule code tradesubtype. The test point factor can be trade_type, trade_subtype, etc. Since the data is queried in the system database "***" of the target system, the SQL statement "select contcat('tradesubtype', '_', trade_type, '_', trade_subtype)astestpoint_key from ***" can be constructed. By executing the SQL statement, the global test data can be queried in the system database.

[0051] In summary, by constructing data query statements and executing the data query statements on the system database of the target system to obtain global test data, the efficiency of obtaining global test data is improved.

[0052] Furthermore, the global test data contains repeated data corresponding to multiple test point factors. It is necessary to perform frequency statistics on the repeated data corresponding to the test point factors in the date and product dimensions, so as to standardize the global test data. The specific implementation is as follows:

[0053] Determine at least two test point data in the global test data; perform frequency calculation on the at least two test point data to obtain frequency data respectively corresponding to the at least two test point data; and use the at least two test point data and the frequency data respectively corresponding to the at least two test point data as the data to be trimmed.

[0054] Specifically, the test point data may be the test point coding data or the test point identification data in the global test data. The frequency calculation may be the statistics of the test point data in the time dimension, including but not limited to calculating the occurrence frequency of the test point corresponding to each test point identification within a preset time interval, the number of products involved in the test point corresponding to each test point identification within the preset time interval, the number of dates involved, the number of accounting tasks involved, the most frequently occurring date and product in a single day, the latest occurrence date, and the most frequently occurring product.

[0055] Based on this, at least two test point data are determined in the global test data. The frequency of the at least two test point data is calculated in the time and product dimensions to obtain the frequency data corresponding to the at least two test point data, and the frequency data indicates the frequency of occurrence of the test point corresponding to the test point data within a preset time interval. The at least two test point data and the frequency data corresponding to the at least two test point data are used as the data to be trimmed, and the user subsequently trims the data to be trimmed.

[0056] Using the above example, both global test data and data to be tailored can be stored in the form of data tables. Table 1 below is a data table to be tailored consisting of data to be tailored obtained by standardizing global test data within the preset time interval from January 3, 2024 to January 11, 2024. The data table to be tailored contains test points, products, dates, and the frequency of occurrence of test points obtained after standardization.

[0057]

[0058] Table 1

[0059] In summary, by standardizing the global test data and calculating the frequency of at least two test point data in the time and product dimensions, frequency statistics for the test points can be achieved, which facilitates subsequent data trimming for the data to be trimmed.

[0060] Step 206: based on at least two data clipping sub-strategies included in the data clipping strategy, the data to be clipped is clipped in sequence, and target data is determined according to the clipping result.

[0061] Specifically, after obtaining the global test data based on the target function and the test point factor, and standardizing the global test data to obtain the data to be trimmed, the data to be trimmed can be trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined according to the trimming results, wherein the data trimming strategy is used to perform multiple rounds of data trimming on the data to be trimmed in sequence, and at least two data trimming sub-strategies have a sequential execution order, and multiple rounds of ordered data trimming of the data to be trimmed can be completed by sequentially executing the data trimming sub-strategies. At least two data trimming sub-strategies correspond to different data trimming dimensions, and the data trimming dimensions can be time dimensions, product dimensions, and dimensions of comprehensive time products. The trimming result is the data trimming result obtained after at least two rounds of data trimming. The target data can be directly used for regression testing of the target function, and the target data has a high coverage of the target function and the test point factor.

[0062] Based on this, after obtaining the global test data based on the target function and the test point factor and standardizing the global test data to obtain the data to be trimmed, the execution order corresponding to at least two data trimming sub-strategies contained in the data trimming strategy is determined, and the data trimming sub-strategies are executed in sequence for the data to be trimmed according to the execution order, so as to trim the data to be trimmed in sequence, and determine the target data for regression testing of the target function according to the trimming results.

[0063] Furthermore, considering that the data to be clipped contains many parameters such as objects and time, the at least two data clipping sub-strategies included in the data clipping strategy can correspond to different parameter dimensions respectively, and the specific implementation is as follows:

[0064] Determine the object trimming sub-strategy, time trimming sub-strategy and combined trimming sub-strategy included in the data trimming strategy; based on the object trimming sub-strategy, the time trimming sub-strategy and the combined trimming sub-strategy, the data to be trimmed is trimmed in sequence, and the target data is determined according to the trimming results.

[0065] Specifically, the object trimming sub-strategy is used to trim the data to be trimmed in the object dimension, and the time trimming sub-strategy is used to continue trimming the data to be trimmed that has been trimmed once in the time dimension after the object trimming sub-strategy is executed. The combined trimming sub-strategy is used to continue trimming the data to be trimmed that has been trimmed twice in the combined dimension of time and object after the object trimming sub-strategy and the time trimming sub-strategy are executed.

[0066] Based on this, the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy included in the data trimming strategy are determined. The object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy are arranged in sequence, and there is an order of execution. Based on the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy, the data to be trimmed is trimmed in sequence, and the target data is determined according to the trimming results.

[0067] Using the above example, the object trimming sub-strategy is used to trim data for the parameter "product" in Table 1. The time trimming sub-strategy is used to trim data for the parameter "date" in Table 1. The combined trimming sub-strategy is used to trim data based on the parameters "product" and "date" after Table 1 has been trimmed by the object trimming sub-strategy and the time trimming sub-strategy.

[0068] In summary, by sequentially trimming the data to be trimmed based on the object trimming sub-strategy, the time trimming sub-strategy and the combined trimming sub-strategy, the amount of data to be trimmed can be gradually reduced, and the target function can be regressed with data with a larger coverage and less data volume.

[0069] Furthermore, in order to facilitate data tailoring for the data table to be tailored, the data table can be constructed respectively according to the parameters such as objects and time in the data table to be tailored, and the specific implementation is as follows:

[0070] A data table to be trimmed is constructed based on the data to be trimmed, and a test point data table, an object data table and a time data table are respectively constructed based on the test point data, object data and time data contained in the data table to be trimmed; the data table to be trimmed is trimmed in sequence based on the object trimming sub-strategy, the time trimming sub-strategy, the combined trimming sub-strategy, the test point data table, the object data table and the time data table, and target data is determined according to the trimming results.

[0071] Specifically, the test point data refers to the test points in the data table to be cut, the object data can be the product data in the data table to be cut, and the time data can be the date data in the data table to be cut. The test point data table only contains the test points to be covered, the object data table only contains the object data, and the time data table only contains the date data.

[0072] Based on this, the data table to be trimmed is constructed according to the object parameters, test point parameters, date parameters and frequency parameters contained in the data to be trimmed, and the test point data table, object data table and time data table are constructed respectively based on the test point data, object data and time data contained in the data table to be trimmed, so as to realize statistical summary for time, test point and object respectively. Based on the object trimming sub-strategy, time trimming sub-strategy, combined trimming sub-strategy, test point data table, object data table and time data table, the data table to be trimmed is trimmed in sequence, and the target data is determined according to the trimming results.

[0073] Using the above example, after obtaining Table 1, the data table to be trimmed, statistics can be summarized for the products, dates, and test points in the data table to be trimmed, and the test point data table, object data table, and time data table can be obtained. The following Table 2 is the test point data table (test points to be covered), Table 3 is the object data table (products to be screened), and Table 4 is the time data table (dates of products to be screened). Based on the object trimming sub-strategy, time trimming sub-strategy, combined trimming sub-strategy, test point data table, object data table, and time data table, the data table to be trimmed is trimmed in sequence to obtain the target data.

[0074]

[0075] Table 2

[0076]

[0077] Table 3

[0078]

[0079] Table 4

[0080] In summary, based on the test point data, object data and time data contained in the data table to be trimmed, the test point data table, object data table and time data table are constructed respectively. Based on the object trimming sub-strategy, time trimming sub-strategy, combined trimming sub-strategy, test point data table, object data table and time data table are trimmed in sequence to obtain target data. The accuracy of data trimming of the data to be trimmed is improved.

[0081] Furthermore, considering that the data trimming strategy includes object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy, and each strategy has a fixed execution order. Therefore, when trimming the data to be trimmed, the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy need to be executed in sequence. The specific implementation is as follows:

[0082] The data table to be trimmed is trimmed based on the object trimming sub-strategy, the test point data table and the object data table to obtain an object trimming data table; the object trimming data table is trimmed based on the time trimming sub-strategy, the test point data table and the time data table to obtain a time trimming data table; the time trimming data table is trimmed based on the combined trimming sub-strategy and the test point data table to obtain a target data table, and the data contained in the target data table is used as the target data.

[0083] Specifically, the object tailoring data table is a data table obtained by tailoring the data table to be tailored based on the object tailoring sub-strategy, and is a data table for data screening in the object dimension of the data to be tailored. The time tailoring data table is a data table obtained by tailoring the object tailoring data table in the time dimension based on the time tailoring sub-strategy.

[0084] Based on this, the data table to be trimmed is trimmed based on the object trimming sub-strategy, and the test points contained in the test point data table are used to ensure that the object trimming data table obtained by trimming the data table to be trimmed can cover all the test points contained in the test point data table. The object trimming data table is further trimmed based on the time trimming sub-strategy, and the test points contained in the test point data table are used to continue trimming the object trimming data table in the time dimension, so that the obtained time trimming data table can cover all the test points contained in the test point data table. The time trimming data table is further trimmed based on the combination trimming sub-strategy, and the test points contained in the test point data table are used to ensure that the target data table obtained by trimming the time trimming data table can cover all the test points contained in the test point data table. The data contained in the target data table is used as the target data, and regression testing is performed on the target function based on the target data to ensure the comprehensiveness of the test.

[0085] In summary, the object pruning sub-strategy, time pruning sub-strategy and combination pruning sub-strategy are executed in sequence to complete multiple rounds of pruning of the data table to be tested, which reduces the amount of data while ensuring the coverage of the target data, thereby improving the accuracy of subsequent regression testing.

[0086] Furthermore, when data in the data table to be clipped is clipped based on the object clipping sub-strategy, it is necessary to ensure that the object clipping data table obtained by clipping covers all test points included in the test point data table. The specific implementation is as follows:

[0087] Based on the data table to be cropped, determine the number of object test points corresponding to each object in the object data table; determine the target object associated with the test points in the test point data table in the object data table according to the number of object test points corresponding to each object; and crop the data table to be cropped based on the target object to obtain the object cropped data table.

[0088] Specifically, the number of object test points refers to the number of test points covered by each object in the to-be-cut data table within a preset time interval. There is at least one target object, and the target object may cover all test points in the test point data table.

[0089] Based on this, the number of object test points corresponding to each object in the object data table is determined based on the data table to be trimmed, the first object with a higher number of object test points is selected, the first test point to be covered by the first object is determined in the test point data table with reference to the data table to be trimmed, the first test point is deleted in the test point data table, the data row associated with the first test point in the data table to be trimmed is deleted, and the initial object trimming data table is obtained. After deleting the first object in the object data table, the object data table is updated based on the initial object trimming data table, and based on the number of object test points corresponding to each object in the updated object data table, the second object with a higher number of object test points is selected, the second test point covered by the second object is determined in the initial object trimming data table, the second test point is deleted in the test point data table, the data associated with the second test point in the initial object trimming data table is deleted, the second object is deleted in the object data table, and so on, until the target object is obtained. The data table to be trimmed is trimmed based on the target object to obtain the object trimming data table.

[0090] Continuing with the above example, we conduct frequency statistics on the products in Table 1 and obtain the following Table 5.

[0091]

[0092] Table 5

[0093] Select product F3 with a higher number of covered test points, and refer to the data table to be cut, and delete the first test points A3, A4, A5, A6, A7, and A8 covered by product F3 in the test point data table (Table 2). Delete the data rows associated with the first test points A3, A4, A5, A6, A7, and A8 in the data table to be cut (Table 1) to obtain the initial object cutting data table. The initial object cutting data table is shown in Table 6 below.

[0094]

[0095] Table 6

[0096] After deleting the first object (product F3) in the object data table (Table 5), the data table is trimmed based on the initial object (Table 6

[0097] ) updates the object data table, and based on the number of object test points corresponding to each object in the updated object data table, selects the second object F1 (covering 2 test points) with a higher number of object test points, determines the second test points A1 and A2 covered by the second object in the initial object clipping data table, and continues to delete the second test points in the test point data table (Table 2). After the second test points are deleted, A9 and A10 remain in the test point data table (Table 2). Delete the data associated with the second test points A1 and A2 in the initial object clipping data table, delete the second object in the object data table, and update the object data table again based on the initial object clipping data table with the second test points A1 and A2 deleted, and so on, until the target objects F3, F1 and F4 that can cover all the data points in the test point data table are selected. At this time, the data to be clipped (Table 1) table is clipped based on the target objects F3, F1 and F4 to obtain the object clipping data table. See Table 7 below for the object clipping data table.

[0098]

[0099] Table 7

[0100] In summary, by clipping the to-be-clipped data table based on the target object to obtain the object clipping data table, it is possible to ensure that the object clipping data table covers all the test points included in the test point data table.

[0101] Furthermore, when data in the object clipping data table is clipped based on the time clipping sub-strategy, it is necessary to ensure that the clipped time clipping data table covers all test points included in the test point data table. The specific implementation is as follows:

[0102] Based on the object clipping data table, determine the number of time test points corresponding to each time point in the time data table; determine the target time point associated with the test point in the test point data table in the time data table according to the number of time test points corresponding to each time point; clip the object clipping data table based on the target time point to obtain the time clipping data table.

[0103] Specifically, the number of time test points refers to the number of test points covered by each time in the data table to be trimmed within a preset time interval. There is at least one target time point, and the target time point can cover all test points in the test point data table.

[0104] Based on this, the number of time test points corresponding to each time point in the time data table is determined based on the object clipping data table, the first time point with a higher number of time test points is selected, the third test point covered by the first time point is determined in the test point data table with reference to the object clipping data table, the third test point is deleted in the test point data table, the data row associated with the third test point in the object clipping data table is deleted, and the initial time clipping data table is obtained. After deleting the first time point in the time data table, the time data table is updated based on the initial time clipping data table, and the second time point with a higher number of time test points is selected based on the number of time test points corresponding to each time point in the updated time data table, the fourth test point covered by the second time point is determined in the initial time clipping data table, the fourth test point is deleted in the test point data table, the data associated with the fourth test point in the initial time clipping data table is deleted, the second time point is deleted in the time data table, and so on, until the target time point is obtained. The object clipping data table is clipped based on the target time point to obtain the time clipping data table.

[0105] Continuing with the above example, we perform frequency statistics on the dates in Table 1 and obtain the following Table 8.

[0106]

[0107] Table 8

[0108] Select the first time point with a higher number of covered test points: date 20240103, refer to the object clipping data table (Table 7), and delete the third test points A1, A2, A3, A4, and A5 covered by date 20240103 in the test point data table (Table 2). Delete the data rows associated with the third test points A1, A2, A3, A4, and A5 in the object clipping data table (Table 7) to obtain the initial time clipping data table. The initial time clipping data table is shown in Table 9 below.

[0109]

[0110] Table 9

[0111] After deleting the first time point (date 20240103) in the time data table (Table 4), the time data table is updated based on the initial time clipping data table (Table 9), and based on the number of time test points corresponding to each time in the updated time data table, the second time point with a higher number of time test points is selected: date 20240105 (the number of covered test points is 2), and the fourth test points A8 and A10 covered by the second time point are determined in the initial time clipping data table, and the fourth test point is continued to be deleted in the test point data table (Table 2). After the fourth test point is deleted, A6, A7 and A9 remain in the test point data table (Table 2). The data associated with the fourth test points A8 and A10 in the initial object clipping data table are deleted, and after deleting the second time point in the time data table, the time data table is updated again based on the initial time clipping data table from which the fourth test points A8 and A10 are deleted, and so on, until the target time points that can cover all the data points in the test point data table are selected: date 20240103, date 20240105, date 20240104, and date 20240107. At this time, the object clipping data table (Table 7) is clipped based on the target time points: date 20240103, date 20240105, date 20240104, and date 20240107 to obtain the time clipping data table. The time clipping data table is shown in Table 10 below.

[0112]

[0113] Table 10

[0114] In summary, by clipping the object clipping data table based on the target time point to obtain the time clipping data table, it is possible to ensure that the time clipping data table covers all the test points included in the test point data table.

[0115] Furthermore, when data in the time clipping data table is clipped based on the combined clipping sub-strategy, it is necessary to ensure that the clipped target data table covers all test points included in the test point data table, which is specifically implemented as follows:

[0116] Based on the time clipping data table, an object time data table is determined, and the number of data pair test points of each object time data pair in the object time data table is determined; according to the number of data pair test points of each object time data pair, target object time data pairs associated with each test point in the test point data table are determined in the object time data table; based on the target object time data pairs, the time clipping data table is clipped to obtain a target data table.

[0117] Specifically, the number of test points of the data pair refers to the number of test points covered by each object time data pair in the time clipping data table within a preset time interval. There is at least one target object time data pair, and the target object time data pair can cover all test points in the test point data table.

[0118] Based on this, the object time data table is determined based on the time clipping data table, and the number of data pair test points of each object time data pair in the object time data table is determined. According to the number of data pair test points of each object time data pair, a first data pair with a higher number of data pair test points is selected, and the fifth test point covered by the first data pair is determined in the test point data table with reference to the time clipping data table, and the fifth test point is deleted in the test point data table, and the data row associated with the fifth test point in the time clipping data table is deleted to obtain an initial data pair clipping data table, and after deleting the first data pair in the object time data table, the object time data table is updated based on the initial data pair clipping data table, and based on the number of data pair test points corresponding to each data pair in the updated object time data table, a second data pair with a higher number of data pair test points is selected, and the sixth test point covered by the second data pair is determined in the initial data pair clipping data table, and the sixth test point is deleted in the test point data table, and the data associated with the sixth test point in the initial data pair clipping data table is deleted, and the second data pair is deleted in the object time data table, and so on, until the target object time data pair is obtained. The time-cutting data table is cut based on the target object time data to obtain a target data table.

[0119] Continuing with the above example, the object time data pairs are integrated for the products and dates in Table 1 to obtain the object time data table, Table 11.

[0120]

[0121] Table 11

[0122] Select the first data pair with a higher number of covered test points: F1-20240103, refer to the time clipping data table (Table 10), delete the fifth test points A1, A2, A3, A4, A5 covered by the first data pair: F1-20240103 in the test point data table (Table 2). Delete the data rows associated with the fifth test points A1, A2, A3, A4, A5 in the time clipping data table (Table 10) to obtain the initial data pair clipping data table, and refer to the following Table 12 for the initial data pair clipping data table.

[0123]

[0124] Table 12

[0125] After deleting the first data pair: F1-20240103 in the object time data table (Table 11), the object time data table is updated based on the initial data pair trimming data table (Table 12), and based on the number of data pair test points corresponding to each object time data pair in the updated object time data table, the second data pair with a higher number of data pair test points is selected: F4-20240105 (the number of covered test points is 2), and the sixth test points A8 and A10 covered by the second data pair are determined in the initial data pair trimming data table, and the sixth test point continues to be deleted in the test point data table (Table 2). After the sixth test point is deleted, A6, A7 and A9 remain in the test point data table (Table 2). The data associated with the sixth test points A8 and A10 in the initial data pair clipping data table are deleted, and after deleting the second data pair in the object time data table, the object time data table is updated again based on the initial data pair clipping data table from which the sixth test points A8 and A10 are deleted, and so on, until the target object time data pairs that can cover all the data points in the test point data table are selected: F1-20240103, F4-20240105, F4-20240104, and F3-20240107. At this time, the time clipping data table (Table 10) is clipped based on the target object time data pairs: F1-20240103, F4-20240105, F4-20240104, and F3-20240107 to obtain the target data table. The target data table is shown in Table 13 below.

[0126]

[0127] Table 13

[0128] In summary, by clipping the time clipping data table based on the target object time data to obtain the target data table, it is possible to ensure that the target data table covers all the test points included in the test point data table.

[0129] Step 208: Execute a functional test task corresponding to the target function based on the target data.

[0130] Specifically, the at least two data trimming sub-strategies included in the above-mentioned data trimming strategy trim the data to be trimmed in sequence. After the target data is determined according to the trimming results, the functional testing task corresponding to the target function can be executed based on the target data, wherein the functional testing task is used to perform regression testing on the target function. The regression testing of the target function can be completed by executing the functional testing task, and whether the function of the target system has an impact on the target function can be tested.

[0131] Based on this, at least two data trimming sub-strategies included in the above-mentioned data trimming strategy trim the data to be trimmed in sequence, determine the target data according to the trimming results, determine the functional testing task corresponding to the target function, execute the functional testing task based on the target data, and realize regression testing of the target function.

[0132] A test method provided by an embodiment of the present specification determines test point factors for a target function included in an updated target system, and performs regression testing on the test point factors. Global test data is acquired based on the target function and the test point factors, and the global test data is standardized to obtain data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

[0133] The following combination Figure 3 , taking the application of the test method provided in this specification in the valuation system in the financial field as an example, the test method is further explained. Figure 3 A processing flow chart of a testing method provided in an embodiment of the present specification is shown, which specifically includes the following steps.

[0134] Step 302: Determine test point factors for target functions included in the updated target system.

[0135] In practical applications, the target system can be a valuation system. When the market has new business needs, relevant financial institutions need to upgrade their valuation systems. During the upgrade, they need to ensure the quality of the key links of the upgraded version, that is, to ensure that the update of the target system does not introduce new problems. Determine the target functions that need to be regression tested in the target system, analyze the test coverage dimensions of the target functions, and define the factors that make up the test points, that is, the test point factors.

[0136] Step 304: Determine the function identifier of the target function, construct a data query statement based on the function identifier and the test point factor, and obtain global test data by executing the data query statement on the system database of the target system.

[0137] Confirm the test coverage dimension unique identification code coverrule_code, confirm the test point factor, the test point unique identification is a string composed of the test coverage dimension unique identification code coverrule_code + multiple test point factors plus separators to make a unique identification. As shown below: select contcat('tradesubtype', '_', m.trade_type, '_', m.trade_subtype)as testpoint_key from XXX. Determine the date range covered by the test, the start date beginDate, the end date endDate, the default is 1 year. Collect global test data by executing SQL statements. Global test data is the test point distribution details, including test point code, product, date, number of occurrences, etc.

[0138] Step 306: Determine at least two test point data in the global test data, perform frequency calculation on the at least two test point data, obtain frequency data corresponding to the at least two test point data, and use the at least two test point data and the frequency data corresponding to the at least two test point data as data to be trimmed.

[0139] Perform statistical analysis on the global test data to obtain test point codes, total frequency of occurrence, minimum occurrence date, maximum occurrence date, the product with the highest frequency of daily occurrence, the date with the highest frequency of daily occurrence, the product with the latest occurrence, the date of the latest occurrence, and other analytical data. The data obtained from the statistical analysis of the global test data will be used as the data to be trimmed.

[0140] Step 308: construct a data table to be cut based on the data to be cut, and construct a test point data table, an object data table and a time data table respectively based on the test point data, object data and time data included in the data table to be cut.

[0141] The data to be cut is sampled and initialized to generate the test point data table, object data table and time data table. The test point data table is the list of test points to be covered PL, the data table to be cut is the distribution list of test points to be analyzed PDL0, the object data table is the list of products to be selected FL0, and the time data table is the list of dates to be selected DL0.

[0142] Step 310: Determine the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy included in the data trimming strategy.

[0143] The object trimming sub-strategy is used to select the minimum product set based on the test point distribution list PDL0 to be analyzed. The products in the minimum product set can cover all test points included in the test point list PL to be covered. The time trimming sub-strategy is used to continue to select the minimum date set based on the date after the test point distribution list PDL0 to be analyzed is trimmed based on the object trimming sub-strategy to obtain a new test point distribution list PDL0 to be analyzed. The dates in the minimum date set can cover all test points included in the test point list PL to be covered. The combination trimming sub-strategy is used to select the minimum workload accounting task list based on the further trimmed test point distribution list PDL0 to be analyzed, and obtain the data collection results corresponding to the test points.

[0144] Step 312: based on the object clipping sub-strategy, the test point data table and the object data table, clip the data table to be clipped to obtain the object clipping data table.

[0145] Based on the object clipping sub-strategy, the test point distribution list PDL0 to be analyzed is clipped in the product dimension. Before clipping the data to be clipped, multiple data tables are initialized based on the data to be clipped, such as Figure 4 As shown, the initialized data table includes: a list of test points to be covered PL, containing a total number of test points numtotal; a list of products to be screened FLO; a list of remaining test points to be covered PLO, PLO=PL; covered test points num1=0; and a list of minimum product sets FminL=null.

[0146] In practical applications, the specific clipping steps include: 1) Based on the test point distribution detailed data PDL0, count the number of uncovered test points covered by each product. 2) Find the product Fi that covers the maximum number of test points; a) Add product Fi to the product minimum set list FminL; b) Delete product Fi from the list of products to be selected FL0; c) Delete the test points that can be covered by the currently selected product Fi in PL0; e) Delete the test point related detailed data covered by the currently selected product Fi in PDL0; At this time, the number of covered test points num1=num[Fi], calculate the test coverage rate num / numtotal, and repeat steps 1) and 2) when the coverage rate is less than 100%, until the list of test points to be covered PL0 is empty, and obtain the minimum product set, that is, the minimum set list FminL, and clip the distribution detailed list of test points to be analyzed PDL0 based on the minimum product set to obtain the object clipping data table.

[0147] Step 314: based on the time clipping sub-strategy, the test point data table and the time data table, clip the object clipping data table to obtain the time clipping data table.

[0148] After the test point distribution list PDL0 to be analyzed is trimmed in the product dimension based on the object trimming sub-strategy, the new test point distribution list PDL0 to be analyzed obtained by trimming is trimmed in the product dimension based on the time trimming sub-strategy. Before trimming, multiple data tables are initialized, such as Figure 5 As shown, the initialized data table includes: the distribution list PDLO of the test points to be analyzed obtained by cutting according to the minimum product set list FminL; the list PL of test points to be covered, the total number of test points is numtotal; the list of dates to be screened DLO; the list of remaining test points to be covered PLO, PLO=PL; the covered test points num1=0; the product minimum set list DminL=null.

[0149] In practical applications, the specific trimming steps include: 1) re-extracting the test point distribution detail data PDL0 according to the product minimum set; 2) re-initializing the test points to be covered PL0=PL; 3) based on the test point distribution detail data PDL0, counting the number of uncovered test points for each date; 4) finding the date Di that covers the maximum number of test points; a) adding the date Di to the DminL list; b) deleting the date Di from the candidate date list DL0; c) deleting the test points that can be covered by the date Di in PL0; e) deleting the test point related detailed data that can be covered by the date Di in PDL0; at this time, the number of covered test points num1=num[Di], and calculating the test coverage rate num1 / numtotal. When the coverage rate is less than 100%, repeat steps 3) and 4) until the test point list PL0 to be covered is empty, and the minimum date set is obtained, that is, the minimum date list DminL. Based on the minimum date set, the new test point distribution detail list PDL0 to be analyzed is continued to be trimmed to obtain the time trimming data table.

[0150] Step 316: based on the combined clipping sub-strategy and the test point data table, the time clipping data table is clipped to obtain a target data table, and the data contained in the target data table is used as target data.

[0151] After the new test point distribution list PDL0 obtained by clipping is clipped in the product dimension based on the time clipping sub-strategy, the test point distribution list PDL0 obtained after the two clippings is clipped in the product + date dimension based on the combined clipping sub-strategy. Before clipping, initialize multiple data tables, such as Figure 6As shown, the initialized data table includes: PDLO is obtained by cutting the data of PDL according to the minimum product set FminL and the minimum date set DminL; a list of test points to be covered PL, a total number of test points numtotal; a list of accounting tasks to be screened VLO; a list of remaining test points to be covered PLO, PLO=PL; covered test points num1=0; a list of minimum set of accounting tasks VminL=null.

[0152] In practical applications, the specific tailoring steps include: 1) Initialize the list of pending accounting tasks VL0, one product per day, and the test points to be covered PL0=PL; 2) Re-extract the test point distribution detailed data PDL0 according to the minimum set of products and the minimum set of dates; 3) Based on the test point distribution detailed data PDL0, count the number of uncovered test points covered by each accounting task; 4) Find the accounting task Vi with the coverage capability max; a) Add the accounting task Vi to the regression test accounting task list VLmin; b) Delete the accounting task Vi from the pending accounting task list VL0; c) Update P L contains the sampled products + date information of the test points covered this time; d) delete the test points that can be covered by the current accounting task Vi in PL0; e) delete the detailed data related to the test points that can be covered by the current accounting task Vi in PDL0; at this time, the number of covered test points num1=num[Vi], calculate the test coverage rate num1 / numtotal, and when the coverage rate is less than 100%, repeat steps 3) and 4) until the list of test points to be covered PL0 is empty, and the minimum accounting workload set is obtained, that is, the accounting regression accounting task VLmin, and the sampling results corresponding to the test points are obtained. Based on the minimum accounting workload set, the distribution list of test points to be analyzed PDL0 obtained by the two trimmings is further trimmed to obtain the target data that can be directly used for regression testing.

[0153] Step 318: Execute the functional test task corresponding to the target function based on the target data.

[0154] A functional test task for performing regression testing on the target function is constructed based on the target data, and the regression testing on the target function is completed by executing the functional test task.

[0155] In summary, the test point factors are determined for the target functions included in the updated target system, and regression tests are performed on the test point factors. Global test data is obtained based on the target functions and test point factors, and the global test data is standardized to obtain the data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

[0156] Corresponding to the above method embodiment, this specification also provides a test system embodiment. Figure 7 FIG. 1 is a schematic diagram showing a structure of a test system provided by an embodiment of the present specification. Figure 7 As shown, the test system 700 includes a business party 710 and a server 720; the business party 710 is used to submit a test request to the server 720 for the updated target system; the server 720 is used to determine the test point factor for the target function included in the updated target system based on the test request; obtain global test data based on the target function and the test point factor, and standardize the global test data to obtain data to be trimmed; based on at least two data trimming sub-strategies included in the data trimming strategy, the data to be trimmed are trimmed in sequence, and the target data is determined according to the trimming result; based on the target data, the functional test task corresponding to the target function is executed, the test result is obtained and the test result is sent to the business party 710.

[0157] In actual applications, when the business party has a regression test requirement for the updated target system, a test request can be submitted to the server for the updated target system. After receiving the test request, the server determines the test point factor for the target function contained in the updated target system, and performs regression testing on the test point factor. Based on the target function and the test point factor, global test data is obtained, and the global test data is standardized to obtain the data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. Based on at least two data trimming sub-strategies contained in the data trimming strategy, the data to be trimmed is trimmed in sequence, and the target data is determined according to the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

[0158] The above is a schematic scheme of a test system of this embodiment. It should be noted that the technical scheme of the test system and the technical scheme of the above test method belong to the same concept, and the details of the technical scheme of the test system that are not described in detail can be found in the description of the technical scheme of the above test method.

[0159] Corresponding to the above method embodiment, this specification also provides a test device embodiment, Figure 8 FIG. 1 is a schematic diagram showing the structure of a testing device provided by an embodiment of the present specification. Figure 8 As shown, the device comprises:

[0160] A determination module 802 is configured to determine a test point factor for a target function included in the updated target system;

[0161] An acquisition module 804 is configured to acquire global test data based on the target function and the test point factor, and to standardize the global test data to obtain data to be trimmed;

[0162] A clipping module 806 is configured to clip the to-be-cut data in sequence based on at least two data clipping sub-strategies included in the data clipping strategy, and determine target data according to the clipping result;

[0163] The execution module 808 is configured to execute the functional test task corresponding to the target function based on the target data.

[0164] In an optional embodiment, the acquisition module 804 is further configured to:

[0165] Determine the function identifier of the target function and the test point factor corresponding to the target function;

[0166] Constructing a data query statement based on the function identifier and the test point factor;

[0167] The global test data is obtained by executing the data query statement on the system database of the target system.

[0168] In an optional embodiment, the acquisition module 804 is further configured to:

[0169] Determining at least two test point data in the global test data;

[0170] Performing frequency calculation on the at least two test point data to obtain frequency data respectively corresponding to the at least two test point data;

[0171] The at least two test point data and the frequency data respectively corresponding to the at least two test point data are used as the data to be trimmed.

[0172] In an optional embodiment, the cropping module 806 is further configured to:

[0173] Determine the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy included in the data trimming strategy;

[0174] The data to be trimmed is trimmed in sequence based on the object trimming sub-strategy, the time trimming sub-strategy and the combined trimming sub-strategy, and the target data is determined according to the trimming result.

[0175] In an optional embodiment, the cropping module 806 is further configured to:

[0176] Constructing a to-be-cut data table based on the to-be-cut data, and constructing a test point data table, an object data table, and a time data table respectively based on the test point data, object data, and time data contained in the to-be-cut data table;

[0177] The data table to be trimmed is trimmed in sequence based on the object trimming sub-strategy, the time trimming sub-strategy, the combination trimming sub-strategy, the test point data table, the object data table and the time data table, and the target data is determined according to the trimming results.

[0178] In an optional embodiment, the cropping module 806 is further configured to:

[0179] Clipping the to-be-cut data table based on the object clipping sub-strategy, the test point data table and the object data table to obtain an object clipping data table;

[0180] Tailoring the object tailoring data table based on the time tailoring sub-strategy, the test point data table and the time data table to obtain a time tailoring data table;

[0181] The time clipping data table is clipped based on the combined clipping sub-strategy and the test point data table to obtain a target data table, and the data contained in the target data table is used as the target data.

[0182] In an optional embodiment, the cropping module 806 is further configured to:

[0183] Determine the number of object test points corresponding to each object in the object data table based on the to-be-cut data table;

[0184] Determine, in the object data table, target objects associated with the test points in the test point data table according to the number of object test points corresponding to each object;

[0185] The to-be-cut data table is cut based on the target object to obtain the object-cut data table.

[0186] In an optional embodiment, the cropping module 806 is further configured to:

[0187] Determine the number of time test points corresponding to each time point in the time data table based on the object clipping data table;

[0188] Determine, in the time data table, a target time point associated with a test point in the test point data table according to the number of time test points corresponding to each time point;

[0189] The object clipping data table is clipped based on the target time point to obtain the time clipping data table.

[0190] In an optional embodiment, the cropping module 806 is further configured to:

[0191] Determine an object time data table based on the time clipping data table, and determine the number of data pair test points of each object time data pair in the object time data table;

[0192] Determine, in the object time data table, target object time data pairs associated with each test point in the test point data table according to the number of data pair test points of each object time data pair;

[0193] The time clipping data table is clipped based on the target object time data to obtain a target data table.

[0194] A test device provided by an embodiment of the present specification determines test point factors for a target function included in an updated target system, and performs regression testing on the test point factors. Global test data is acquired based on the target function and the test point factors, and the global test data is standardized to obtain data to be trimmed. By standardizing the global test data, statistical analysis of the data can be achieved to facilitate subsequent data trimming. The data to be trimmed is trimmed in sequence based on at least two data trimming sub-strategies included in the data trimming strategy, and the target data is determined based on the trimming results, so that the target data can cover more test points, thereby improving the comprehensiveness of the test of the target function. Executing the functional test task corresponding to the target function based on the target data can improve the efficiency of testing the target function.

[0195] The above is a schematic scheme of a test device of this embodiment. It should be noted that the technical scheme of the test device and the technical scheme of the above test method belong to the same concept, and the details of the technical scheme of the test device that are not described in detail can be found in the description of the technical scheme of the above test method.

[0196] Fig. 9The structure block diagram of a computing device 900 provided according to an embodiment of the present specification is shown. The components of the computing device 900 include but are not limited to a memory 910 and a processor 920. The processor 920 is connected to the memory 910 via a bus 930, and a database 950 is used to store data.

[0197] The computing device 900 also includes an access device 940 that enables the computing device 900 to communicate via one or more networks 960. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 940 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0198] In one embodiment of the present specification, the above components of the computing device 900 and Fig. 9 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Fig. 9 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0199] The computing device 900 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 900 may also be a mobile or stationary server.

[0200] The processor 920 is used to execute the following computer executable instructions, which implement the steps of the above-mentioned test method when executed by the processor.

[0201] The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above-mentioned testing method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above-mentioned testing method.

[0202] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the above-mentioned test method when executed by a processor.

[0203] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above-mentioned test method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above-mentioned test method.

[0204] An embodiment of the present specification also provides a computer program product, including a computer program or instructions, which implement the steps of the above-mentioned test method when executed by a processor.

[0205] The above is a schematic scheme of a computer program product of this embodiment. It should be noted that the technical scheme of the computer program product and the technical scheme of the above test method belong to the same concept, and the details not described in detail in the technical scheme of the computer program product can be referred to the description of the technical scheme of the above test method.

[0206] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0207] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0208] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0209] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0210] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can understand and use this specification well.

Claims

1. A testing method, characterized in that: include: Determine test point factors for target functions included in the updated target system; Acquire global test data based on the target function and the test point factor, and standardize the global test data to obtain data to be trimmed; Based on at least two data clipping sub-strategies included in the data clipping strategy, and a test point data table, an object data table, and a time data table constructed based on the to-be-cut data table corresponding to the to-be-cut data, the to-be-cut data are clipped in sequence, and target data are determined according to the clipping results; A functional test task corresponding to the target function is executed based on the target data.

2. The testing method according to claim 1, characterized in that: The acquiring of global test data based on the target function and the test point factor comprises: Determine the function identifier of the target function and the test point factor corresponding to the target function; Constructing a data query statement based on the function identifier and the test point factor; The global test data is obtained by executing the data query statement on the system database of the target system.

3. The testing method according to claim 1, characterized in that: The step of normalizing the global test data to obtain the data to be cut includes: Determining at least two test point data in the global test data; Performing frequency calculation on the at least two test point data to obtain frequency data respectively corresponding to the at least two test point data; The at least two test point data and the frequency data respectively corresponding to the at least two test point data are used as the data to be trimmed.

4. The testing method according to claim 1, characterized in that: The at least two data clipping sub-strategies included in the data clipping strategy are used to clip the data to be clipped in sequence, and target data is determined according to the clipping results, including: Determine the object trimming sub-strategy, time trimming sub-strategy and combination trimming sub-strategy included in the data trimming strategy; The data to be trimmed is trimmed in sequence based on the object trimming sub-strategy, the time trimming sub-strategy and the combined trimming sub-strategy, and the target data is determined according to the trimming result.

5. The testing method according to claim 4, characterized in that: The step of sequentially clipping the data to be clipped based on the object clipping sub-strategy, the time clipping sub-strategy and the combined clipping sub-strategy, and determining target data according to the clipping results includes: Constructing a to-be-cut data table based on the to-be-cut data, and constructing a test point data table, an object data table, and a time data table respectively based on the test point data, object data, and time data contained in the to-be-cut data table; The data table to be trimmed is trimmed in sequence based on the object trimming sub-strategy, the time trimming sub-strategy, the combination trimming sub-strategy, the test point data table, the object data table and the time data table, and the target data is determined according to the trimming results.

6. The testing method according to claim 5, characterized in that: The method of sequentially clipping the data table to be clipped based on the object clipping sub-strategy, the time clipping sub-strategy, the combined clipping sub-strategy, the test point data table, the object data table, and the time data table, and determining target data according to the clipping result includes: Clipping the to-be-cut data table based on the object clipping sub-strategy, the test point data table and the object data table to obtain an object clipping data table; Tailoring the object tailoring data table based on the time tailoring sub-strategy, the test point data table and the time data table to obtain a time tailoring data table; The time clipping data table is clipped based on the combined clipping sub-strategy and the test point data table to obtain a target data table, and the data contained in the target data table is used as the target data.

7. The testing method according to claim 6, characterized in that: The step of clipping the to-be-cut data table based on the object clipping sub-strategy, the test point data table and the object data table to obtain the object clipping data table includes: Determine the number of object test points corresponding to each object in the object data table based on the to-be-cut data table; Determine, in the object data table, target objects associated with the test points in the test point data table according to the number of object test points corresponding to each object; The to-be-cut data table is cut based on the target object to obtain the object-cut data table.

8. The testing method according to claim 6, characterized in that: The step of clipping the object clipping data table based on the time clipping sub-strategy, the test point data table and the time data table to obtain the time clipping data table includes: Determine the number of time test points corresponding to each time point in the time data table based on the object clipping data table; Determine, in the time data table, a target time point associated with a test point in the test point data table according to the number of time test points corresponding to each time point; The object clipping data table is clipped based on the target time point to obtain the time clipping data table.

9. The testing method according to claim 6, characterized in that: The step of trimming the time trimming data table based on the combined trimming sub-strategy and the test point data table to obtain a target data table includes: Determine an object time data table based on the time clipping data table, and determine the number of data pair test points of each object time data pair in the object time data table; Determine, in the object time data table, target object time data pairs associated with each test point in the test point data table according to the number of data pair test points of each object time data pair; The time clipping data table is clipped based on the target object time data to obtain a target data table.

10. A testing system, characterized in that: Including business side and service side; The business party is used to submit a test request to the server for the updated target system; The server is used to determine the test point factor for the target function included in the updated target system based on the test request; Acquire global test data based on the target function and the test point factor, and standardize the global test data to obtain data to be trimmed; Based on at least two data clipping sub-strategies included in the data clipping strategy, and a test point data table, an object data table, and a time data table constructed based on the to-be-cut data table corresponding to the to-be-cut data, the to-be-cut data are clipped in sequence, and target data are determined according to the clipping results; A functional test task corresponding to the target function is performed based on the target data, a test result is obtained and the test result is sent to the business party.

11. A computing device, characterized in that: include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method described in any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, implement the steps of the method described in any one of claims 1 to 9.

13. A computer program product, characterized in that The method comprises a computer program or an instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 9.

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