Test regression method and device

Abstract

The invention discloses a test regression method and device, and the method comprises the steps: responding to a test regression request, and determining target data corresponding to the test regression request; determining an execution environment of the target data based on preset configuration information; calling a data processing engine corresponding to the execution environment, performing data processing on the target data, and receiving a data processing result returned after the data processing engine processes the target data; and obtaining a regression test result based on the data processing result. According to the embodiment, the data testing cost can be saved, the comprehensiveness and the real-time performance of the testing process are guaranteed, and then the online stability of the system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a test regression method and device. Background Art

[0002] In the existing technology, when performing technical transformations such as interface migration and application updates, testers and R&D personnel are often required to migrate test data or update results by themselves. However, due to the large number of business scenarios involved, not only does it lead to high testing costs, but there is also the problem of missing certain business scenarios during the testing process, which makes it impossible to guarantee the stability of the system. Summary of the Invention

[0003] In view of this, the embodiments of the present disclosure at least provide a test regression method and apparatus, which can save testing costs, ensure the comprehensiveness of the testing process, and thus ensure the online stability of the system.

[0004] To achieve the above object, according to one aspect of an embodiment of the present disclosure, a test regression method is provided, comprising:

[0005] In response to a test regression request, determining target data corresponding to the test regression request;

[0006] Determining an execution environment of the target data based on preset configuration information;

[0007] calling a data processing engine corresponding to the execution environment to process the target data, and receiving a data processing result returned by the data processing engine after processing the target data;

[0008] Based on the data processing results, a regression test result is obtained.

[0009] Optionally, determining the execution environment of the target data based on preset configuration information includes:

[0010] Determining the data type of the target data according to the identification information in the preset configuration information;

[0011] If the data type of the target data is the first data type and is associated with a data processing result of the target data in the first execution environment, determining that the execution environment of the target data is the second execution environment;

[0012] If the data type of the target data is the second data type and is associated with a data processing result of the target data in the second execution environment, determining that the execution environment of the target data is the first execution environment;

[0013] If the target data is not associated with the data processing result, the execution environment of the target data is determined to be the first execution environment and the second execution environment.

[0014] Optionally, obtaining a regression test result based on the data processing result includes:

[0015] Sampling processing is performed on the data processing results, and regression test results are obtained based on the sampling results obtained after the sampling processing.

[0016] Optionally, the calling of a data processing engine corresponding to the execution environment to process the target data includes:

[0017] Generate a data processing engine call request;

[0018] storing the call request in a first list;

[0019] The data processing engine obtains the call request from the first list, stores the call request in a second list, and performs data processing on the target data based on the call request;

[0020] After processing the target data, the data processing engine removes the call request in the second list.

[0021] Optionally, the configuration information includes name list information; the method further includes: before determining the execution environment of the target data, testing the test regression request according to the name list information, and confirming that the test passes.

[0022] Optionally, the configuration information includes switch degradation information; the method further includes: after obtaining the regression test result, if the regression test fails, generating degradation prompt information based on the switch degradation information, and the degradation prompt information is used to prompt to stop the flow of data associated with the target data in the data flow.

[0023] Optionally, the first execution environment is an online execution environment, and the second execution environment is a pre-release execution environment; if the regression test result fails, the method further includes:

[0024] Obtaining abnormal items in the pre-launch execution environment based on data processing results of the target data in the online execution environment and the pre-launch execution environment;

[0025] Based on the abnormal item, abnormal prompt information is generated.

[0026] According to a second aspect of an embodiment of the present disclosure, a test regression device is provided, comprising:

[0027] an acquisition module, configured to determine, in response to a test regression request, target data corresponding to the test regression request;

[0028] A configuration module, configured to determine an execution environment of the target data based on preset configuration information;

[0029] a data processing module, configured to call a data processing engine corresponding to the execution environment, perform data processing on the target data, and receive a data processing result returned by the data processing engine after processing the target data;

[0030] The testing module is used to obtain regression test results based on the data processing results.

[0031] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0032] one or more processors;

[0033] a memory for storing one or more programs,

[0034] When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method described in any one of the above embodiments.

[0035] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method described in any one of the above embodiments is implemented.

[0036] Any one of the above aspects or any implementation methods of any one of the aspects, by responding to a test regression request, determines the target data corresponding to the test regression request; based on preset configuration information, determines the execution environment of the target data; calls the data processing engine corresponding to the execution environment, processes the target data, and receives the data processing results returned by the data processing engine after processing the target data; obtains the regression test results based on the data processing results; thereby, it is possible to automatically test the data consistency in different environments in real time, save data testing costs, and ensure the comprehensiveness and real-time nature of data testing, thereby ensuring the online stability of the system.

[0037] In further embodiments of the present invention, by configuring the list information and switch degradation information in the configuration information, precise control and flexible management of the test process and data flow can be achieved, ensuring that the system can dynamically adjust according to the preset configuration information, thereby improving system stability and reliability. In addition, when the regression test results fail, an exception prompt message corresponding to the abnormal item can be generated, which helps to locate and promptly fix the abnormal problem, thereby improving system reliability.

[0038] In order to make the above-mentioned objects, features and beneficial effects of the present invention more clearly understood, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and, together with the specification, are used to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without inventive effort.

[0040] Figure 1 A flow chart of a test regression method provided by an embodiment of the present disclosure is shown;

[0041] Figure 2 A flow chart of a test regression method provided in an embodiment of the present disclosure is shown;

[0042] Figure 3 A schematic diagram of a process for data comparison and verification in a test regression method provided by an embodiment of the present disclosure is shown;

[0043] Figure 4 A schematic diagram of a test regression device provided by an embodiment of the present disclosure is shown;

[0044] Figure 5 An exemplary system architecture is shown in which embodiments of the present disclosure may be applied;

[0045] Figure 6 A schematic diagram of the structure of a computer system of a terminal device or server used to implement an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0046] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, in which various details of the disclosed embodiments are included to facilitate understanding, and these should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0047] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, and storage of user personal information involved in the technical solutions disclosed herein all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken with respect to user personal information to prevent unauthorized access to user personal information data and to safeguard the security of user personal information, network security, and national security.

[0048] Research has found that in order to adapt to the rapid development of the Internet and meet people's increasing needs, it is necessary to promptly carry out technical transformations such as interface migration and application updates on related systems or applications.

[0049] However, under the existing development model, for technical transformation scenarios such as interface migration and application updates, testers and developers are often required to test the migrated or updated data themselves. However, due to the large number of business scenarios involved, not only is the testing cost high, but the logic of certain business scenarios may be missed during the testing process, resulting in online problems and a negative impact on the stability and reliability of the system.

[0050] Based on the above research, the disclosed embodiments provide a test regression method that can automatically and in real time complete data testing during the data flow process. Furthermore, through pre-set configuration information, it can achieve precise control and flexible management of the test process and data flow status. This eliminates the need for R&D and test personnel to perform regression testing, firstly avoiding the significant time and labor costs of manual verification, and secondly avoiding the errors and business scenario omissions that may be caused by manual verification. This ensures the comprehensiveness and timeliness of the testing process, thereby guaranteeing the reliability and stability of the business system.

[0051] The defects of the above solutions and the proposed solutions are the results obtained by the inventor after practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed in the present disclosure for the above problems below should be the contributions made by the inventor to the present disclosure during the disclosure process.

[0052] The technical solutions in the present disclosure will be clearly and completely described below in conjunction with the drawings in the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the present disclosure generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present disclosure.

[0053] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0054] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0055] To facilitate understanding of this embodiment, a test regression method disclosed in the embodiment of the present disclosure is first introduced in detail. The execution subject of the test method provided in the embodiment of the present disclosure is generally a computer device with certain computing capabilities.

[0056] The test regression method provided by the embodiment of the present disclosure is described below by taking the execution subject as a terminal device as an example.

[0057] See also Figure 1 FIG. 1 is a flowchart of a test regression method provided by an embodiment of the present disclosure, wherein the method includes S101 to S104, wherein:

[0058] S101: In response to a test regression request, determine target data corresponding to the test regression request.

[0059] In this step, the test regression request initiated by the front end carries the target data that needs to be regression tested. After the front end initiates the request, the platform for regression testing can respond to the request and determine the target data that needs to be regression tested.

[0060] Figure 2 A flow chart of the test regression method provided in the embodiment of the present disclosure is shown as follows: Figure 2 As shown, the front-end types that initiate test regression requests are diverse, that is, the sources of test regression requests are diverse; specifically, test regression requests can be initiated by front-ends such as mini-programs, official accounts, PC (Personal Computer) workstations, and APP (Mobile Application).

[0061] like Figure 2As shown, the test regression request initiated by the front end can also be encapsulated after passing through a specific interface platform. Since the types of front ends that initiate the request are diverse, the applications or interfaces corresponding to the data requested for regression testing are also different, so the encapsulation rules can also be different. For example, the request encapsulation rule can be "interface corresponding to the request + time when the request is initiated + random number", where the random number serves as the unique identifier of the request; in addition to this, the encapsulation rule of the test regression request can also be any other encapsulation rule, and the embodiments of the present disclosure do not make specific limitations on this.

[0062] S102: Determine the execution environment of the target data based on preset configuration information.

[0063] In this step, after determining the target data that needs to be regression tested, the platform for performing regression testing may also determine an execution environment corresponding to the target data according to preset configuration information.

[0064] like Figure 2 As shown, in the disclosed embodiment, the configuration information may include identification information. This identification information is used to identify the interface corresponding to the data for regression testing in the regression test request, thereby identifying the data type corresponding to the target data. Once the data type corresponding to the target data is identified, the execution environment corresponding to the target data can be determined. Furthermore, the configuration information may also include any other information related to regression testing, which is not specifically limited in the disclosed embodiment.

[0065] It should be noted that the data types in the embodiments of the present disclosure can be any data type, and the execution environment can be any execution environment. There is no specific limit on the number of data types and execution environments. The following examples illustrate the technical solution of the present invention using the data types divided into online data and pre-release data, and the execution environments divided into online execution environments and pre-release execution environments. This does not constitute an undue limitation of the present invention. In actual applications, the actual situation should be taken into consideration to ensure that the functionality is achieved.

[0066] Exemplarily, when the target data is online data and is associated with the data processing results of the target data in the online execution environment, since the target data is already associated with the data processing results in the online execution environment, it is only necessary to put the target data into the pre-execution environment for data processing, so that the execution environment of the target data can be determined as the pre-execution environment; when the target data is pre-released data and is associated with the data processing results of the target data in the pre-released execution environment, based on reasons similar to those mentioned above, the execution environment of the target data can be determined as the online execution environment; and when the target data has no data processing results associated with it, regardless of the type of the target data, the execution environment of the target data can be determined as the online execution environment and the pre-released execution environment.

[0067] In one possible implementation, the configuration information may further include list information, which may be a blacklist or whitelist information, used to verify the request source and request initiation authority in the test regression request before determining the execution environment of the target data, and confirm that the verification has passed.

[0068] S103: calling a data processing engine corresponding to the execution environment to process the target data, and receiving a data processing result returned by the data processing engine after processing the target data.

[0069] In this step, after determining the execution environment of the target data, the data processing engine corresponding to the execution environment may be called to process the target data, and the data processing result returned by the data processing engine after processing the target data is received.

[0070] In specific implementations, since different execution environments may have different network or computing resources and security requirements, selecting a data processing engine that is adapted to a specific execution environment can not only ensure the performance and efficiency of the data processing engine, but also ensure the security of data processing. In addition, the same target data may have different optimal processing methods in different execution environments. Selecting corresponding data processing engines for different execution environments to process the target data can also ensure that the target data is processed in the optimal processing method, while also avoiding the problem of data confusion. Therefore, in the embodiments of the present disclosure, corresponding data processing engines can be set in different execution environments, and the corresponding data processing engines can be called in the execution environment to process the target data.

[0071] For example, the data processing engine corresponding to the online execution environment may be an online engine, and the data processing engine corresponding to the pre-execution environment may be an offline engine; the data processing engines corresponding to different execution environments may be set according to actual conditions and needs so as to achieve their purpose, and the embodiments of the present disclosure do not make specific limitations on this.

[0072] In an embodiment of the present disclosure, when calling a data processing engine corresponding to an execution environment to process target data, this can be achieved through a memory-level message queue. In a specific implementation, a data processing engine call request can be generated first and stored in a first list. The data processing engine can obtain the call request from the first list, store it in a second list, and process the target data based on the call request. After the data processing engine completes processing the target data, the call request is removed from the second list. This ensures efficient task scheduling and data processing processes in the data processing engine, as well as orderly and asynchronous processing of target data.

[0073] S104: Obtain regression test results based on the data processing results.

[0074] In this step, after obtaining the data processing results returned by the data processing engine after processing the target data, the data processing results of the target data under different execution environments can be compared. If the comparison results are consistent, the regression test passes.

[0075] Figure 3 Schematic diagram of the process for data comparison and verification.

[0076] For example, Figure 3 As shown, when the target data is online data and is associated with the data processing results in the online execution environment, in the embodiment of the present disclosure, since the data processing results in the online execution environment have been obtained, they can be placed in the cache first, and wait for the target data to be processed in the pre-execution environment and the corresponding data processing results to be returned. Then, the data processing results in the pre-execution environment are placed in the cache and compared with the data processing results in the online execution environment; if the data processing results in the online execution environment are consistent with the data processing results in the pre-execution environment, the regression test is deemed to have passed, otherwise the test fails.

[0077] like Figure 2 As shown, in the embodiment of the present disclosure, the data processing results can also be compared and processed by the result collection system in a sampling and comparison manner, that is, the data processing results are first sampled and processed; then the sampling results obtained after sampling and processing of different data processing results are compared to obtain the regression test results. Before sampling and processing the data processing results, it is necessary to first determine the sampling method, sample size, sampling frequency and other issues for the sampling processing.

[0078] Specifically, the sampling method can be any sampling method such as simple random sampling, stratified random sampling, etc., which depends on the data properties and distribution of the data processing results, etc., and the embodiments of the present disclosure do not make specific limitations on this.

[0079] It should be noted that if sampling comparison is used to compare data processing results, the sample size of the data processing results must be large enough to ensure the reliability of the results obtained from the sampling comparison. In addition, the sample size must also be considered when determining the sampling frequency. If the sampling frequency is too low, the sample size may be too small, and accurate comparison results may not be obtained; if the sampling frequency is too high, it may lead to a waste of resources.

[0080] In the disclosed embodiments, comparison dimensions can be pre-set and compared based on the comparison dimensions for data processing results in different environments. For example, the data processing results in different environments can be compared based on the number of calls, call results, call duration, etc. If the comparison results are consistent, the regression test has passed; if the comparison results are inconsistent, the regression test has failed. It should be noted that the above comparison dimensions can be set according to actual needs in actual applications and are not specifically limited in the disclosed embodiments.

[0081] In one possible implementation, Figure 2 As shown, the configuration information mentioned above may also include switch degradation information. After obtaining the regression test results, if the regression test fails, corresponding degradation prompt information may be generated based on the switch degradation information to prompt the system or relevant personnel to stop the flow of data associated with the target data in the data flow.

[0082] For example, continuing the example described above in which the execution environment is divided into an online execution environment and a pre-execution environment, when the regression test result fails, it is also possible to obtain abnormal items in the pre-execution environment by comparing the data processing results obtained after processing the target data in the online execution environment and the pre-execution environment, and generate corresponding abnormal prompt information based on the abnormal items. The abnormal prompt information may include information such as the location and severity of the abnormal problem in the pre-execution environment, so as to remind the system or relevant personnel of the abnormal problem in the pre-execution environment.

[0083] Those skilled in the art will understand that in the above-mentioned method of the specific implementation method, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0084] Based on the same inventive concept, a test regression device corresponding to the test regression method is also provided in the embodiment of the present disclosure. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the above-mentioned test regression method in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0085] Reference Figure 4 FIG. 4 is a schematic diagram of the architecture of a test regression device provided by an embodiment of the present disclosure, wherein the device includes: an acquisition module 401, a configuration module 402, a data processing module 403, and a test module 404; wherein,

[0086] The acquisition module 401 is configured to determine target data corresponding to the test regression request in response to the test regression request;

[0087] Configuration module 402, configured to determine the execution environment of the target data based on preset configuration information;

[0088] The data processing module 403 is configured to call a data processing engine corresponding to the execution environment to process the target data and receive a data processing result returned by the data processing engine after processing the target data.

[0089] The testing module 404 is configured to obtain a regression test result based on the data processing result.

[0090] In a possible implementation, the configuration module 402 is specifically configured to:

[0091] Determining the data type of the target data according to the identification information in the preset configuration information;

[0092] If the data type of the target data is the first data type and is associated with a data processing result of the target data in the first execution environment, determining that the execution environment of the target data is the second execution environment;

[0093] If the data type of the target data is the second data type and is associated with a data processing result of the target data in the second execution environment, determining that the execution environment of the target data is the first execution environment;

[0094] If the target data is not associated with the data processing result, the execution environment of the target data is determined to be the first execution environment and the second execution environment.

[0095] In a possible implementation, the testing module 404 is specifically configured to:

[0096] Sampling processing is performed on the data processing results, and regression test results are obtained based on the sampling results obtained after the sampling processing.

[0097] In a possible implementation, the data processing module 403 is specifically configured to:

[0098] Generate a data processing engine call request;

[0099] storing the call request in a first list;

[0100] The data processing engine obtains the call request from the first list, stores the call request in a second list, and performs data processing on the target data based on the call request;

[0101] After processing the target data, the data processing engine removes the call request in the second list.

[0102] In a possible implementation, the configuration information includes list information;

[0103] The configuration module 402 is specifically configured to verify the test regression request according to the list information before determining the execution environment of the target data, and confirm that the verification is passed.

[0104] In a possible implementation, the configuration information includes switch degradation information;

[0105] The configuration module 402 is specifically configured to: after obtaining the regression test result, if the regression test fails, generate degradation prompt information according to the switch degradation information, wherein the degradation prompt information is used to prompt to stop the flow of data associated with the target data in the data flow.

[0106] In a possible implementation, the first execution environment is an online execution environment, and the second execution environment is a pre-release execution environment; if the regression test result fails;

[0107] The testing module 404 is specifically configured to: obtain abnormal items in the pre-launch execution environment based on data processing results of the target data in the online execution environment and the pre-launch execution environment;

[0108] Based on the abnormal item, abnormal prompt information is generated.

[0109] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference can be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0110] According to a third aspect of an embodiment of the present invention, there is provided an electronic device for regression testing, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method provided in the first aspect of the embodiment of the present invention.

[0111] According to a fourth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method provided by the first aspect of the embodiment of the present invention is implemented.

[0112] Figure 5 An exemplary system architecture 500 is shown to which the regression testing method or regression testing apparatus according to an embodiment of the present invention may be applied.

[0113] like Figure 5As shown, system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. Network 504 is used to provide a medium for communication links between terminal devices 501, 502, 503 and server 505. Network 504 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0114] Users can use terminal devices 501, 502, and 503 to interact with server 505 via network 504 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 501, 502, and 503, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0115] The terminal devices 501 , 502 , and 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0116] Server 505 may be a server that provides various services, such as a backend management server (for example only) that supports shopping websites browsed by users using terminal devices 501, 502, and 503. The backend management server may process the received regression test request and feed back the processing result (for example only) to the terminal device.

[0117] It should be noted that the regression testing method provided in the embodiment of the present invention is generally executed by the server 505, and accordingly, the regression testing apparatus is generally disposed in the server 505. The regression testing method provided in the embodiment of the present invention may also be executed by the terminal devices 501, 502, and 503, and accordingly, the regression testing apparatus may be disposed in the terminal devices 501, 502, and 503.

[0118] It should be understood that Figure 5 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0119] Reference below Figure 6 , which shows a schematic structural diagram of a computer system 600 of a terminal device suitable for implementing an embodiment of the present invention. Figure 6 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0120] like Figure 6As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the system 600 are also stored in the RAM 603. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0121] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed into the storage section 608 as needed.

[0122] In particular, according to the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from a removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the system of the present invention are performed.

[0123] It should be noted that the computer-readable medium described in the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0124] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0125] The modules described in the embodiments of the present invention may be implemented in software or hardware. The modules described may also be provided in a processor. For example, they may be described as: a processor including an acquisition module, a configuration module, a data processing module, and a test module. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, a test module may also be described as "a module for obtaining regression test results based on the data processing results."

[0126] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiments, or may exist independently and not be incorporated into the device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the device, the device implements the following method:

[0127] In response to a test regression request, determining target data corresponding to the test regression request;

[0128] Determining an execution environment of the target data based on preset configuration information;

[0129] calling a data processing engine corresponding to the execution environment to process the target data, and receiving a data processing result returned by the data processing engine after processing the target data;

[0130] Based on the data processing results, a regression test result is obtained.

[0131] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The scope of protection of the present disclosure is not limited thereto. Although the present disclosure has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed in the present disclosure, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A test regression method, characterized in that: include: In response to a test regression request, determining target data corresponding to the test regression request; Determining an execution environment of the target data based on preset configuration information; calling a data processing engine corresponding to the execution environment to process the target data, and receiving a data processing result returned by the data processing engine after processing the target data; Based on the data processing results, a regression test result is obtained.

2. The method according to claim 1, characterized in that The determining the execution environment of the target data based on the preset configuration information includes: Determining the data type of the target data according to the identification information in the preset configuration information; If the data type of the target data is the first data type and is associated with a data processing result of the target data in the first execution environment, determining that the execution environment of the target data is the second execution environment; If the data type of the target data is the second data type and is associated with a data processing result of the target data in the second execution environment, determining that the execution environment of the target data is the first execution environment; If the target data is not associated with the data processing result, the execution environment of the target data is determined to be the first execution environment and the second execution environment.

3. The method according to claim 1, characterized in that Obtaining a regression test result based on the data processing result includes: Sampling processing is performed on the data processing results, and regression test results are obtained based on the sampling results obtained after the sampling processing.

4. The method according to claim 1, wherein The calling of a data processing engine corresponding to the execution environment to process the target data includes: Generate a data processing engine call request; storing the call request in a first list; The data processing engine obtains the call request from the first list, stores the call request in a second list, and performs data processing on the target data based on the call request; After processing the target data, the data processing engine removes the call request in the second list.

5. The method according to any one of claims 1 to 4, characterized in that: The configuration information includes name list information; the method further includes: before determining the execution environment of the target data, verifying the test regression request according to the name list information, and confirming that the verification is passed.

6. The method according to any one of claims 1 to 4, characterized in that: The configuration information includes switch degradation information; the method further includes: after obtaining the regression test result, if the regression test fails, generating degradation prompt information based on the switch degradation information, the degradation prompt information being used to prompt stopping the flow of data associated with the target data in the data flow.

7. The method according to claim 2, characterized in that The first execution environment is an online execution environment, and the second execution environment is a pre-release execution environment; if the regression test result fails, the method further includes: Obtaining abnormal items in the pre-launch execution environment based on data processing results of the target data in the online execution environment and the pre-launch execution environment; Based on the abnormal item, abnormal prompt information is generated.

8. A test regression device, characterized in that: include: an acquisition module, configured to determine, in response to a test regression request, target data corresponding to the test regression request; A configuration module, configured to determine an execution environment of the target data based on preset configuration information; a data processing module, configured to call a data processing engine corresponding to the execution environment, perform data processing on the target data, and receive a data processing result returned by the data processing engine after processing the target data; The testing module is used to obtain regression test results based on the data processing results.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 7.

10. A computer-readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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