A product online detection method and device

Abstract

The application discloses a product online detection method and device, and relates to the technical field of data analysis, which is used for accelerating the online detection process of products. The method comprises the following steps: determining a basic product category to which a product to be put online belongs; acquiring detection information of at least one cluster product under the basic product category; wherein the detection information of any cluster product is determined according to the detection of each sub-item information of the cluster product; and generating the product to be put online which meets the online detection requirements according to the detection information of a first cluster product corresponding to the product to be put online, and setting a binding relationship between the first cluster product and the product to be put online.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a product online testing method and apparatus. Background Technology

[0002] Currently, when testing whether products meet the requirements for going live, testing tasks are generated manually for each individual product. After receiving the testing tasks, the relevant departments then test each product according to the requirements. This method becomes time-consuming and labor-intensive when dealing with a large number of products (e.g., tens of thousands).

[0003] Therefore, there is an urgent need for a solution to expedite the product testing process before it goes live. Summary of the Invention

[0004] This application provides a product online testing method and apparatus to accelerate the product online testing process.

[0005] In a first aspect, this application provides a product launch testing method, which includes: determining the basic product category to which the product to be launched belongs; obtaining testing information of at least one clustered product under the basic product category; wherein the testing information of any clustered product is determined after testing the information of each sub-item of the clustered product; generating the product to be launched that meets the launch testing requirements based on the testing information of the first clustered product corresponding to the product to be launched, and setting a binding relationship between the first clustered product and the product to be launched.

[0006] In the above technical solution, products that meet the online testing requirements are generated based on the testing information of the first cluster products corresponding to the products to be launched. The process eliminates the need for relevant departments to test whether the products to be launched meet the online requirements, which can shorten the online testing process for products to be launched.

[0007] In one possible design, after generating the product to be launched that meets the online testing requirements, the method further includes: for any launched product, generating and executing the testing tasks of the second cluster product and the testing cycle of the second cluster product, based on the previous testing date of the second cluster product corresponding to the launched product.

[0008] In the above technical solution, the detection date of the second cluster product can be determined based on the previous detection date of the second cluster product corresponding to the online product and the detection cycle of the second cluster product. Then, the detection task of the second cluster product and the detection tasks of each online product that are bound to the second cluster product are automatically triggered before the detection date, without the need for staff to manually trigger the detection task of each online product.

[0009] In one possible design, the method further includes: the detection cycle of any clustering product is determined by: determining the online evaluation result of the clustering product based on the information of each sub-item of the clustering product; determining the online level of the clustering product based on the online evaluation result of the clustering product; and determining the detection cycle corresponding to the clustering product based on the online level of the clustering product.

[0010] In the above technical solution, different online levels of cluster products correspond to different testing cycles, and online products that are bound to cluster products reuse the testing cycle of cluster products. Therefore, cluster products at different online levels and online products that are bound to them can periodically generate corresponding testing tasks according to their corresponding testing cycles.

[0011] In one possible design, the step of generating and executing the detection task of the second cluster product includes: determining whether the information of each sub-item of the second cluster product contains qualitative indicators; if it contains qualitative indicators, the detection fails; if it does not contain qualitative indicators, the online evaluation result of the second cluster product is updated according to the quantitative indicators corresponding to the information of each sub-item of the second cluster product.

[0012] In the above technical solution, if the sub-item information of the second cluster product includes qualitative indicators, it indicates that the second cluster product has a significant risk, and the second cluster product is directly judged to have failed the test. If the sub-item information of the second cluster product does not include qualitative indicators, then evaluating the second cluster product based on multiple quantitative indicators can make the online evaluation results of the second cluster product more accurate, and thus provide a more accurate reference for products that are tied to the second cluster product.

[0013] In one possible design, the method further includes: generating detection tasks for each clustered product and detection tasks for already launched products that are bound to each clustered product when the online detection requirements change.

[0014] In the above technical solution, when the online testing requirements change, the testing tasks for each cluster product and the testing tasks for online products that are bound to each cluster product can be triggered in a timely manner, without the need for staff to manually trigger the testing tasks for each cluster product and each online product.

[0015] In one possible design, before generating a product that meets the online testing requirements based on the detection information of the first cluster product corresponding to the product to be launched and setting the binding relationship between the first cluster product and the product to be launched, the method further includes: determining the cluster product corresponding to the product to be launched based on the business logic of the product to be launched.

[0016] Secondly, embodiments of this application provide an alarm analysis device based on a knowledge graph, comprising:

[0017] The determination module is used to determine the basic product category to which the product to be launched belongs;

[0018] The acquisition module is used to acquire detection information of at least one clustered product under the basic product category; wherein, the detection information of any clustered product is determined after detecting the information of each sub-item of the clustered product;

[0019] The processing module is used to generate a product that meets the online testing requirements based on the detection information of the first cluster product corresponding to the product to be launched, and to set the binding relationship between the first cluster product and the product to be launched.

[0020] In one possible design, the processing module is further configured to, for any online product, generate and execute the detection tasks of the second cluster product and the detection cycle of the second cluster product, based on the previous detection date of the second cluster product corresponding to the online product.

[0021] In one possible design, the processing module further determines the online evaluation result of the cluster product based on the information of each sub-item of the cluster product; determines the online level of the cluster product based on the online evaluation result of the cluster product; and determines the detection cycle corresponding to the cluster product based on the online level of the cluster product.

[0022] In one possible design, the device further includes an evaluation module for determining whether the information of each sub-item of the second clustering product contains qualitative indicators. If qualitative indicators are included, the test fails; if qualitative indicators are not included, the online evaluation result of the second clustering product is updated according to the quantitative indicators corresponding to the information of each sub-item of the second clustering product.

[0023] In one possible design, the processing module is also used to generate detection tasks for each clustered product and detection tasks for already launched products that are bound to each clustered product when the online detection requirements change.

[0024] In one possible design, the determining module is further configured to determine the clustered product corresponding to the product to be launched based on the business logic of the product to be launched.

[0025] Thirdly, embodiments of this application also provide a computing device, including:

[0026] Memory, used to store program instructions;

[0027] A processor is configured to invoke program instructions stored in the memory and execute the method described in any possible design of the first aspect, according to the obtained program instructions.

[0028] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer-readable instructions that, when read and executed by a computer, cause the method described in any possible design of the first aspect to be implemented.

[0029] Fifthly, embodiments of this application also provide a computer program product including computer-readable instructions that, when executed by a processor, cause the method described in any possible design of the first aspect to be implemented. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of a system architecture applicable to an embodiment of this application;

[0032] Figure 2 A flowchart illustrating a product launch analysis method provided in this application embodiment;

[0033] Figure 3 A schematic diagram of a product launch analysis device provided in an embodiment of this application;

[0034] Figure 4 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0036] In the embodiments of this application, "multiple" refers to two or more. Terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0037] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0038] Currently, before a product is launched to the market, the testing process for whether a product meets the launch requirements is done on a product-by-product basis, with testing tasks generated manually. After receiving the testing tasks, the relevant departments then test each product according to the launch requirements or procedures. This method becomes particularly time-consuming and labor-intensive when dealing with a large number of products (e.g., tens of thousands).

[0039] To address the aforementioned issues, this application provides a product online testing method and apparatus to accelerate the product online testing process.

[0040] Figure 1 A system architecture diagram applicable to embodiments of this application is shown, such as Figure 1 As shown, the system architecture includes at least a product management system 101 and a terminal device 102. The product management system 101 and the terminal device 102 can be directly or indirectly connected via wired or wireless communication, which is not specifically limited herein.

[0041] The number of product management systems 101 can be one or more. Product management systems 101 are used to perform pre-launch testing on products before they are launched, based on the clustered products corresponding to the products to be launched. After the products are launched, based on the clustered products corresponding to the products to be launched, they generate testing tasks for the launched products and distribute the testing tasks to the terminal devices 102 of relevant departments. Product management systems 101 can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0042] The number of terminal devices 102 can be one or more. Each terminal device 102 has a product management application pre-installed, which can be a client application, a web application, a mini-program application, etc. Terminal devices 102 can be smartphones, tablets, laptops, desktop computers, smart home appliances, smart voice interaction devices, smart in-vehicle devices, etc. Relevant personnel receive testing tasks for online products through the product management application on the terminal device 102 and re-inspect the online products based on the testing information of clustered products that are bound to the online products.

[0043] It should be noted that the above Figure 1 The system architecture shown is merely an example, and the embodiments in this application do not impose any specific limitations on it.

[0044] Figure 2 The illustration shows a schematic flowchart of a product online testing method provided in an embodiment of this application. The process of this method is executed by a computer device, which may be... Figure 1 The product management system 101 shown is as follows: Figure 2 As shown, the method includes the following steps:

[0045] Step 201: Determine the basic product category to which the product to be launched belongs.

[0046] In this embodiment, the basic product category to which the product to be launched belongs can be determined based on the business logic of the product to be launched. The basic product category can be understood as the basic type of product, such as wealth management products, fund products, insurance products, trust products, bond products, precious metal products, and pension security products. Each basic product category includes multiple products. For example, the wealth management product category includes Series A Wealth Management Product Phase 1, Series A Wealth Management Product Phase 2, Series A Wealth Management Product Phase 3, Series B Wealth Management Product 7-day Phase 1, Series B Wealth Management Product 7-day Phase 2, Series B Wealth Management Product 30-day Phase 1, Series B Wealth Management Product 90-day Phase 1, etc.

[0047] Understandably, a product is called a product awaiting launch before it is launched to the market, and a product launched to the market after it is launched.

[0048] Step 202: Obtain the detection information of at least one clustered product under the basic product category.

[0049] In this embodiment, clustered products refer to enterprise-level management objects that are aggregated according to similar or nearly identical essential characteristics based on the product's business logic for easier classification and management. For example, Series A wealth management products and Series B wealth management products can each be considered as a clustered product item. Series A wealth management products include Series A Wealth Management Product Phase 1, Series A Wealth Management Product Phase 2, and Series A Wealth Management Product Phase n; Series B wealth management products include Series B Wealth Management Product Phase 1 (7 days), Series B Wealth Management Product Phase 2 (7 days), Series B Wealth Management Product Phase 1 (30 days), and Series B Wealth Management Product Phase 1 (90 days).

[0050] It should be noted that the clustering granularity can be adaptively adjusted according to actual needs. For example, the first and second 7-day installments of Series B wealth management products can be clustered into a single 7-day Series B wealth management product; the first and second 30-day installments of Series B wealth management products can be clustered into a single 30-day Series B wealth management product; and the first and second 90-day installments of Series B wealth management products can be clustered into a single 90-day Series B wealth management product. Here, the 7-day, 30-day, and 90-day Series B wealth management products are treated as separate clusters.

[0051] In this embodiment, the detection information of any cluster product is determined after detecting the information of each sub-item of the cluster product. For example, when setting cluster product items or when re-detecting a cluster product, each sub-item that conforms to the characteristics of the cluster product is selected from the detection index table or detection index library.

[0052] Step 203: Based on the detection information of the first cluster product corresponding to the product to be launched, generate a product to be launched that meets the online testing requirements and set the binding relationship between the first cluster product and the product to be launched.

[0053] Before step 203, the first cluster product corresponding to the product to be launched can be determined according to the business logic of the product to be launched. Then, step 203 is executed, referring to the detection information of the first cluster product, generating the product to be launched that meets the launch detection requirements, and setting the binding relationship between the first cluster product and the product to be launched.

[0054] If the product to be launched does not have a corresponding first cluster product, a new cluster product is generated based on the basic product category to which the product to be launched belongs and the business logic of the product to be launched. Then, based on the detection information of the new cluster product, a product to be launched that meets the launch detection requirements is generated, and the binding relationship between the new cluster product and the product to be launched is set.

[0055] For example, there are already two clustered products under the wealth management product category: Series A wealth management products and Series B wealth management products. Series A wealth management products include Series A Wealth Management Product Phase 1 and Series A Wealth Management Product Phase 2; Series B wealth management products include Series B Wealth Management Product Phase 1 and Series B Wealth Management Product Phase 2. For the upcoming Series C Wealth Management Product Phase 1, this product does not belong to these two clustered products. Therefore, a new clustered product is created: Series C Wealth Management Products. Then, based on the testing information of Series C Wealth Management Products, a product to be launched that meets the online testing requirements, "Series C Wealth Management Product Phase 1", is generated, and a binding relationship is set between the new clustered product "Series C Wealth Management Products" and the product to be launched "Series C Wealth Management Product Phase 1".

[0056] In the above technical solution, products that meet the online testing requirements are generated based on the testing information of the first cluster products corresponding to the products to be launched. The process eliminates the need for relevant departments to test whether the products to be launched meet the online requirements, which can shorten the online testing process for products to be launched.

[0057] Furthermore, after generating products that meet the requirements for online testing, the process also includes: for any product already online, based on the previous testing date of the second cluster product corresponding to the product and the testing cycle of the second cluster product, generating and executing the testing tasks of the second cluster product and the testing tasks of each product already online that are bound to the second cluster product.

[0058] In this embodiment, since the binding relationship between the product to be launched and its corresponding cluster product is determined before the product goes live, the launched product reuses the testing cycle of the second cluster product with which it is bound. Based on the previous testing date of the second cluster product corresponding to the launched product and the testing cycle of the second cluster product, the retesting date of the second cluster product can be determined. Therefore, before the testing date, the testing tasks for the second cluster product and each launched product with a binding relationship to the second cluster product are automatically triggered, eliminating the need for staff to manually trigger the testing tasks for each launched product.

[0059] If the re-inspection task of the second cluster product passes, the binding relationship between the second cluster product and its subordinate online products remains unchanged, and re-inspection tasks for online products bound to the second cluster product continue to be generated. If the re-inspection task of the second cluster product fails, the online evaluation result of the second cluster product needs to be re-determined based on the information of each sub-item of the second cluster product, the online level of the second cluster product needs to be re-determined based on the online evaluation result of the second cluster product, and the corresponding testing cycle of the second cluster product needs to be re-determined based on the online level of the second cluster product. Then, re-inspection tasks for online products previously bound to the second cluster product are generated. Based on the re-inspection results of the online products, it is determined whether the online level of each online product has changed. If the online level of the online product has not changed, the online product still has a binding relationship with the second cluster product; if the online level of the online product has changed, a new cluster product corresponding to the online product is re-determined, and its binding relationship with the new cluster product is set.

[0060] In one possible implementation, if the business logic of an already launched product changes, it is necessary to redetermine the third cluster product corresponding to the already launched product and establish a binding relationship between the already launched product and the third cluster product. Subsequently, the already launched product reuses the detection cycle of the third cluster product with which it is bound.

[0061] In one possible implementation, the detection cycle for any clustering product can be determined as follows:

[0062] Step 301: Determine the online evaluation results of the clustering product based on the information of each sub-item of the clustering product.

[0063] Step 302: Determine the launch level of the clustering product based on the launch evaluation results.

[0064] Step 303: Determine the testing cycle corresponding to the clustering product based on the online level of the clustering product.

[0065] In one possible implementation, generating and executing a detection task for a second cluster product includes: determining whether the information of each sub-item of the second cluster product contains qualitative indicators; if it contains qualitative indicators, the detection fails.

[0066] Among them, the judgment of the situation involved in the qualitative index clustering product, such as whether it involves virtual currency, whether it involves online lending, etc., when the clustering product involves any of the above situations, it is considered to have a great risk, and the clustering product is directly judged to fail the test.

[0067] If the information of each sub-item of the second cluster product does not include qualitative indicators, then the online evaluation results of the second cluster product shall be updated according to the quantitative indicators corresponding to the information of each sub-item of the second cluster product.

[0068] For example, quantitative indicators can be divided into indicators based on dimensions such as applicable customer type, transaction channel, and source of funds. Each dimension includes multiple options. For instance, the applicable customer type dimension includes individuals or companies, or ordinary customers and VIP customers; the transaction channel includes whether the product transaction occurs in online banking, mobile banking, telephone banking, or at the counter; each option corresponds to a different score. Based on the scores corresponding to the options selected for the second cluster product, the online evaluation result of the second cluster product is determined.

[0069] In one example, the scores for each option can be summed up, and the total score can be used as the evaluation result for the launch of the second cluster product. In another example, a weight can be set for each dimension's indicator, and the weighted scores of each sub-item can be summed up, and the total score can be used as the evaluation result for the launch of the second cluster product.

[0070] In step 302, the online status of the clustering product is determined based on the online evaluation results. Specifically, the online status of the second clustering product can be determined according to the mapping relationship between the online evaluation score and the online status. For example, the online status can be divided into high, medium, and low risk. The online evaluation score in the first to second score range is the high-risk online status; the online evaluation score in the second to third score range is the medium-risk online status; and the online evaluation score in the third to fourth score range is the low-risk online status.

[0071] In step 303, the testing period for the clustering product is determined based on its qualifying level. Specifically, each qualifying level corresponds to a different testing period; the higher the risk level of the qualifying level, the shorter the testing period. For example, the testing period for a high-risk qualifying level is 1 year, for a medium-risk qualifying level it is 2 years, and for a low-risk qualifying level it is 3 years.

[0072] It should be noted that after performing testing tasks on cluster products and determining the online level of cluster products, online products can reuse the online level of cluster products that are bound to them. However, it is still necessary to generate testing tasks for online products and refer to the sub-item information of cluster products that are bound to them to perform testing tasks for online products in a targeted manner in order to obtain more accurate testing results.

[0073] This application enables the management of testing tasks throughout the entire product lifecycle, with different focuses for testing tasks at different stages of the product's lifecycle. Before a product is launched to the market, the focus is on customer access (i.e., which customer groups can purchase the product) and whether the product uses new technologies (e.g., whether it uses blockchain technology or electronic currency technology). After a product is launched to the market, the focus is on the customer groups who have already purchased the product, the risk level of these customers, and the channels through which the product is traded.

[0074] In one possible implementation, when the online testing requirements change, testing tasks for each cluster product and testing tasks for already online products that are bound to each cluster product are generated.

[0075] When the online testing requirements change, it is necessary to test whether each clustered product and the online products that are bound to each clustered product meet the new requirements. If the testing task of a clustered product passes the test according to the new requirements, the binding relationship between the clustered product and the online products bound to it remains unchanged, and testing tasks for the online products bound to the clustered product continue to be generated. If the testing task of a clustered product fails the test according to the new requirements, the online evaluation result of the clustered product needs to be re-determined based on the information of each sub-item of the clustered product, the online level of the clustered product needs to be re-determined based on the online evaluation result, and the corresponding testing cycle of the clustered product needs to be re-determined based on the online level. Then, testing tasks for the online products that were previously bound to the clustered product are generated. Based on the test results of the products already launched, determine whether the launch level of each product has changed. If the launch level of a product has not changed, the product still has a binding relationship with the cluster product. If the launch level of a product has changed, redetermine the new cluster product corresponding to the product and set its binding relationship with the new cluster product.

[0076] In the above technical solution, when the online testing requirements change, the testing tasks for each cluster product and the testing tasks for online products that are bound to each cluster product can be triggered in a timely manner, without the need for staff to manually trigger the testing tasks for each cluster product and each online product.

[0077] This application provides a product launch testing method. Based on the testing information of the cluster products corresponding to the product to be launched, a list of products that meet the launch testing requirements is generated. The process eliminates the need for relevant departments to further test whether the products meet the launch requirements, thus shortening the launch testing process. After the product is launched, the testing tasks for the cluster products and other launched products that are bound to the cluster products can be automatically triggered before the testing date, eliminating the need for staff to manually trigger the testing tasks for each launched product.

[0078] Based on the same technological concept Figure 3 An exemplary embodiment of a product pre-launch testing device provided in this application is illustrated. For example... Figure 3 As shown, the device 300 includes:

[0079] Module 301 is used to determine the basic product category to which the product to be launched belongs;

[0080] The acquisition module 302 is used to acquire detection information of at least one clustered product under the basic product category; wherein, the detection information of any clustered product is determined after detecting the information of each sub-item of the clustered product;

[0081] The processing module 303 is used to generate a product that meets the online testing requirements based on the detection information of the first cluster product corresponding to the product to be launched, and to set the binding relationship between the first cluster product and the product to be launched.

[0082] In one possible design, the processing module 303 is further configured to, for any online product, generate and execute the detection tasks of the second cluster product and the detection cycle of the second cluster product, based on the previous detection date of the second cluster product corresponding to the online product.

[0083] In one possible design, the processing module 303 further determines the online evaluation result of the cluster product based on the information of each sub-item of the cluster product; determines the online level of the cluster product based on the online evaluation result of the cluster product; and determines the detection cycle corresponding to the cluster product based on the online level of the cluster product.

[0084] In one possible design, the device further includes an evaluation module 304, used to determine whether the information of each sub-item of the second clustering product contains qualitative indicators. If it contains qualitative indicators, the test fails; if it does not contain qualitative indicators, the online evaluation result of the second clustering product is updated according to the quantitative indicators corresponding to the information of each sub-item of the second clustering product.

[0085] In one possible design, the processing module 303 is also used to generate detection tasks for each clustered product and detection tasks for online products that are bound to each clustered product when the online detection requirements change.

[0086] In one possible design, the determining module 301 is further configured to determine the clustered product corresponding to the product to be launched based on the business logic of the product to be launched.

[0087] Based on the same technical concept, embodiments of this application provide a computing device, such as... Figure 4 As shown, it includes at least one processor 401 and a memory 402 connected to at least one processor. In this embodiment, the specific connection medium between the processor 401 and the memory 402 is not limited. Figure 4 Taking the connection between processor 401 and memory 402 via a bus as an example, the bus can be divided into address bus, data bus, control bus, etc.

[0088] In this embodiment of the application, the memory 402 stores instructions that can be executed by at least one processor 401. By executing the instructions stored in the memory 402, at least one processor 401 can perform the above-mentioned product online detection method.

[0089] The processor 401 is the control center of the computing device. It can connect to various parts of the computer device through various interfaces and lines, and perform resource settings by running or executing instructions stored in memory 402 and calling data stored in memory 402.

[0090] Optionally, processor 401 may include one or more processing units. Processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 401. In some embodiments, processor 401 and memory 402 may be implemented on the same chip; in some embodiments, they may be implemented separately on independent chips.

[0091] Processor 401 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0092] Memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 402 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. Memory 402 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 402 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0093] Based on the same technical concept, embodiments of this application also provide a computer-readable storage medium storing computer-readable instructions, which, when read and executed by a computer, enable any of the above-described product online testing methods to be implemented.

[0094] Based on the same technical concept, embodiments of this application also provide a computer program product, including computer-readable instructions, which, when executed by a processor, enable any of the above-described product online detection methods to be implemented.

[0095] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0100] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A product online testing method, characterized in that, The method includes: Determine the basic product category to which the product to be launched belongs; Obtain detection information for at least one clustered product under the basic product category; wherein, the detection information for any clustered product is determined after detecting the information of each sub-item of the clustered product; Based on the detection information of the first cluster product corresponding to the product to be launched, generate the product to be launched that meets the launch detection requirements and set the binding relationship between the first cluster product and the product to be launched; For any online product, based on the previous detection date of the second cluster product corresponding to the online product and the detection cycle of the second cluster product, generate and execute the detection task of the second cluster product and the detection tasks of each online product that are bound to the second cluster product; The step of generating the product to be launched that meets the launch testing requirements based on the detection information of the first cluster product corresponding to the product to be launched includes: Based on the information of each sub-item of the first cluster product corresponding to the product to be launched, determine the launch evaluation result of the first cluster product; When the online evaluation results meet the online testing requirements, the product to be launched that meets the online testing requirements is generated.

2. The method according to claim 1, characterized in that, The method further includes: The testing cycle for any clustering product is determined as follows: The online evaluation result of the clustering product is determined based on the information of each sub-item of the clustering product; The launch level of the clustered product is determined based on the launch evaluation results of the clustered product; The detection cycle corresponding to the clustering product is determined based on the online level of the clustering product.

3. The method according to claim 1, characterized in that, The detection task for generating the second clustering product and its execution includes: Determine whether each sub-item information of the second cluster product contains qualitative indicators. If it contains qualitative indicators, the detection fails. The qualitative indicators include at least one or more of virtual currency and online loans. If no qualitative indicators are included, the online evaluation result of the second cluster product is updated based on the quantitative indicators corresponding to each sub-item information of the second cluster product; wherein, the quantitative indicators include at least one or more dimensions such as customer type, transaction channel, and source of funds, and different dimensions are assigned corresponding weights; The step of updating the online evaluation result of the second clustering product based on the quantitative indicators corresponding to each sub-item information of the second clustering product includes: The total score obtained by summing the scores of each sub-item of the second cluster product or by weighted summing the scores is used as the online evaluation result of the second cluster product.

4. The method according to claim 1, characterized in that, The method further includes: When the online testing requirements change, testing tasks for each cluster product and testing tasks for online products that are bound to each cluster product are generated.

5. The method according to claim 1, characterized in that, Before generating products that meet the online testing requirements based on the detection information of the first cluster product corresponding to the products to be launched, and setting the binding relationship between the first cluster product and the products to be launched, the process also includes: The clustered products corresponding to the products to be launched are determined based on the business logic of the products to be launched.

6. A product online testing device, characterized in that, include: The determination module is used to determine the basic product category to which the product to be launched belongs; The acquisition module is used to acquire detection information of at least one clustered product under the basic product category; wherein, the detection information of any clustered product is determined after detecting the information of each sub-item of the clustered product; The processing module is used to generate the product to be launched that meets the online testing requirements based on the detection information of the first cluster product corresponding to the product to be launched, and to set the binding relationship between the first cluster product and the product to be launched. The processing module is also used to generate, and execute, the detection task of the second cluster product and the detection task of each online product that is bound to the second cluster product for any online product, based on the previous detection date of the second cluster product corresponding to the online product and the detection cycle of the second cluster product; The processing module is specifically used to determine the online evaluation result of the first cluster product based on the sub-item information of the first cluster product corresponding to the product to be launched; and to generate the product to be launched that meets the online testing requirements when the online evaluation result meets the online testing requirements.

7. A computing device, characterized in that, include: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method as described in any one of claims 1 to 5 according to the obtained program instructions.

8. A computer-readable storage medium, characterized in that, Includes computer-readable instructions that, when read and executed by a computer, cause the method as described in any one of claims 1 to 5 to be implemented.

9. A computer program product, characterized in that, Includes computer-readable instructions that, when executed by a processor, cause the method as described in any one of claims 1 to 5 to be implemented.

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