An abnormal service scenario detection method and device, computing device, and storage medium

Abstract

The application discloses an abnormal business scenario detection method and device, computing equipment and storage medium, and the method comprises the following steps: acquiring the scene information of the historical abnormal business scenario of a business system, constructing an abnormal business scenario library, recording the processing strategy corresponding to each historical abnormal business scenario in the abnormal business scenario library, and forming a processing strategy library; according to the URL and the scene information of the historical abnormal business scenario, a corresponding coding rule set is constructed; when the business system appears business abnormality, the corresponding target coding rule set is determined according to the URL of the current abnormal business scenario, the scene information of the current abnormal business scenario is matched with the target coding rule set, if the matching is successful, the processing strategy corresponding to the current abnormal business scenario is determined from the processing strategy library. The application detects and processes the corresponding abnormal business scenario in an automatic operation and maintenance mode, thereby assisting the business system in troubleshooting the abnormal business scenario and improving the efficiency of the business system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to an abnormal business scenario detection method and device, computing equipment and storage medium. BACKGROUND

[0002] The development and testing of a web software system need to go through a long development cycle and repeated full-scene business testing. During the business testing process, various business blockages and data anomalies often occur, which require developers to troubleshoot the code and sometimes require testers to reproduce the business scenario to assist in troubleshooting the problems.

[0003] In view of such problems occurring in the development process, the existing solution is generally that the developers write unit tests after completing the business code and execute the unit tests to prove that the behavior of the code is consistent with the developers' expectations. The successful execution of the unit test guarantees that the business system is free of anomalies from the code perspective. To some extent, unit testing can prevent the situation of losing control due to too many system code bugs in the later development. However, from the perspective of function and business, unit testing cannot guarantee that the business process and system are free of anomalies when they are running normally.

[0004] In addition, after the system is strictly tested and successfully delivered online for production activities, various unpredictable situations may occur during the production activities, such as network policy failure, external system anomaly, attack, etc. Once the above situations occur, the business data will be abnormal, which will cause the business process to be unable to execute normally. At this time, system operation and maintenance personnel will troubleshoot the problems and repair the business data, which is very time-consuming and labor-intensive. SUMMARY

[0005] In view of the above problems, the present application is proposed in order to provide an abnormal business scenario detection method, device, computing equipment and storage medium which can overcome the above problems or at least partially solve the above problems.

[0006] According to one aspect of the present application, an abnormal business scenario detection method is provided, comprising:

[0007] Obtaining scenario information of historical abnormal business scenarios of a business system, constructing an abnormal business scenario library according to the scenario information, and recording processing strategies corresponding to each historical abnormal business scenario in the abnormal business scenario library to form a processing strategy library;

[0008] According to the URL of the historical abnormal business scenario in the abnormal business scenario library and the scenario information, a set of encoding rules corresponding to the URL is constructed;

[0009] When the business system has a business exception, a target coding rule set corresponding to a URL of a current abnormal business scenario is determined, the scenario information of the current abnormal business scenario is matched with the target coding rule set, if the matching is successful, a processing strategy corresponding to the current abnormal business scenario is determined from the processing strategy library.

[0010] According to another aspect of the present application, an abnormal business scenario detection device is provided, comprising:

[0011] A database construction module is configured to acquire scenario information of historical abnormal business scenarios of a business system, construct an abnormal business scenario library according to the scenario information, and record a processing strategy corresponding to each historical abnormal business scenario in the abnormal business scenario library to form a processing strategy library.

[0012] A coding rule set construction module is configured to construct a coding rule set corresponding to a URL according to the URL and the scenario information of the historical abnormal business scenarios in the abnormal business scenario library.

[0013] An abnormal business scenario detection module is configured to, when the business system has a business exception, determine a target coding rule set corresponding to a URL of a current abnormal business scenario, match the scenario information of the current abnormal business scenario with the target coding rule set, and if the matching is successful, determine a processing strategy corresponding to the current abnormal business scenario from the processing strategy library.

[0014] According to still another aspect of the present application, a computing device is provided, comprising a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete communication with each other through the communication bus.

[0015] The memory is configured to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the above-mentioned abnormal business scenario detection method.

[0016] According to still another aspect of the present application, a computer storage medium is provided, and the storage medium stores at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the above-mentioned abnormal business scenario detection method.

[0017] According to the abnormal business scenario detection method, device, computing equipment and storage medium, the scene information of the historical abnormal business scenario of the business system is acquired, the abnormal business scenario library is constructed according to the scene information, and the processing strategy corresponding to each historical abnormal business scenario in the abnormal business scenario library is recorded to form the processing strategy library; the URL and the scene information of the historical abnormal business scenario in the abnormal business scenario library are used to construct the code rule set corresponding to the URL; when the business system has a business exception, the target code rule set corresponding to the URL of the current abnormal business scenario is determined according to the URL of the current abnormal business scenario, the scene information of the current abnormal business scenario is matched with the target code rule set, if the matching is successful, the processing strategy corresponding to the current abnormal business scenario is determined from the processing strategy library. The database is constructed by recording the historical abnormal business scenario and the corresponding processing strategy of the business system, the URL corresponding code rule set is constructed by coding, marking and matching the abnormal business scenario, the corresponding abnormal business scenario is detected and processed in the automatic operation mode, so as to assist the business system to investigate the abnormal business scenario and improve the efficiency of the operation of the business system.

[0018] The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application, the content of the specification can be implemented, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described below. BRIEF DESCRIPTION OF DRAWINGS

[0019] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several drawings to designate the same or similar parts. In the drawings:

[0020] Figure 1 A flow chart of an abnormal business scenario detection method provided by an embodiment of the present application is shown;

[0021] Figure 2 An entity-relationship diagram of an abnormal business scenario library and a processing strategy library provided by an embodiment of the present application is shown;

[0022] Figure 3 A schematic diagram of an abnormal business scenario coding rule provided by an embodiment of the present application is shown;

[0023] Figure 4 A tree structure schematic diagram provided by an embodiment of the present application is shown;

[0024] Figure 5 A structure schematic diagram of an abnormal business scenario detection device provided by an embodiment of the present application is shown;

[0025] Figure 6 A structural schematic diagram of a computing device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] Exemplary embodiments of the present application will be described in detail with reference to the drawings. Although exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.

[0027] Figure 1 A flowchart of an embodiment of an abnormal service scenario detection method of the present application is shown, as shown in FIG. 1, the method comprises the following steps: Figure 1

[0028] Step S110: Obtain scenario information of a historical abnormal service scenario of a service system, construct an abnormal service scenario library according to the scenario information, and record a processing strategy corresponding to each historical abnormal service scenario in the abnormal service scenario library to form a processing strategy library.

[0029] In an optional manner, the scenario information of the historical abnormal service scenario comprises one or more of the following information: a uniform resource locator (URL) of the historical abnormal service scenario, an operation reproduction step related to the historical abnormal service scenario, historical abnormal service scenario description information, an exception code, scenario attribute information, an entry time, an associated screenshot ID, an associated video ID, and abnormal features.

[0030] In the present application, a JavaScript (JS) plug-in tool can be introduced in a head tag in an entrance page of a Web service system, thereby globally introducing a JavaScript resource, and the abnormal service scenario detection method of the present application is enabled through a related configuration file.

[0031] In the present application, an abnormal service scenario refers to a Web page in which a service abnormality or a functional abnormality occurs, i.e., a page in which an expected display effect of the page is inconsistent with an expectation of a service tester or an error prompt information appears; Figure 2 An entity-relationship diagram (E-R structure diagram) of the abnormal service scenario library and the processing strategy library of the present application is shown, as shown in FIG. 2, the E-R structure diagram comprises the following elements: Figure 2 ​As shown, in this step, during the entire business system development cycle, the business test personnel can collect and record the scene of the historical abnormal business scene that appears abnormally. The scene information of the historical abnormal business scene includes one or more of the following information: URL of the historical abnormal business scene, operation reproduction steps related to the historical abnormal business scene, historical abnormal business scene description information, abnormal code, scene attribute information, entry time, associated screenshot ID, associated video ID, abnormal characteristics, etc. The business operation and maintenance personnel receive the business work order of the abnormal business scene proposed by the business test personnel according to the background business interface provided by the plug-in tool, investigate the business abnormality, and record the investigation results in the abnormal business scene library through the plug-in tool.

[0032] Further, by recording the processing strategy corresponding to each historical abnormal business scene in the abnormal business scene library, a processing strategy library is formed. In an optional manner, the processing strategy corresponding to the abnormal business scene includes one or more of the following information: processing strategy code corresponding to the abnormal business scene, processing strategy description corresponding to the abnormal business scene, creator of the processing strategy, processing time, abnormal code of the associated abnormal business scene, and automatic operation and maintenance application programming interface (API) corresponding to the processing strategy.

[0033] Step S120: According to the URL and scene information of the historical abnormal business scene in the abnormal business scene library, a code rule set corresponding to the URL is constructed.

[0034] In an optional manner, step S120 further includes: for the historical abnormal business scenes with the same URL in the abnormal business scene library, feature extraction is performed on the historical abnormal business scenes to obtain feature values, and the item values of the feature values are set according to the scene information of the historical abnormal business scenes; according to the feature values, the abnormal classification is divided to construct the code rule set corresponding to the URL.

[0035] In this step, for the historical abnormal business scenes with the same URL in the abnormal business scene library, feature extraction is performed on the historical abnormal business scenes to obtain feature values, and the item values of the feature values are set according to the scene information of the historical abnormal business scenes. It should be particularly noted that for the case of abnormal business scene in the business system operation process, the developer or the operation and maintenance personnel matches the corresponding abnormal business scene through the method of the present application, and compares and analyzes the matched abnormal business scene with the case, so as to quickly locate the cause of the abnormal business scene and repair it, and enrich the feature values of such abnormal business scenes.

[0036] Figure 3 The schematic diagram of the abnormal business scene coding rule is as follows: Figure 3As shown, business operations and maintenance personnel investigate and repair abnormal business scenarios, and follow the procedures outlined above. Figure 3 The rules shown encode abnormal business scenarios. For abnormal business scenarios caused by system defects, they can be archived after repair work is carried out. For abnormal business scenarios not caused by system defects, the abnormal business scenarios are encoded and recorded according to the feature values ​​and the pre-set encoding rules (such as S000 to 999 in the figure), and the relevant processing strategies are recorded and put into the processing strategy library. Specifically, the entry point for abnormal business scenarios is identified by the URL wildcard of the business system. For example, abnormal business scenarios triggered by interactions can be marked as interaction-related exceptions (which can be encoded and recorded using Q000 to 999); abnormal business scenarios caused by business data display or user interface (UI) problems can be marked as display-related exceptions (which can be encoded and recorded using S000 to 999); throughout the entire development cycle of the business system and subsequent production cycles, the feature values ​​of the abnormal business scenarios are continuously extracted to enrich the feature values. The abnormal business scenarios are infinitely subdivided according to the feature values ​​until the abnormal business scenario can be uniquely identified. The higher the uniqueness identification rate of the abnormal business scenarios, the higher the automatic detection rate of abnormal business scenarios in the business system.

[0037] It should be noted that for uniquely marked abnormal business scenarios, the corresponding processing strategy needs to be bound.

[0038] Step S130: When a business system encounters a business exception, determine the corresponding target encoding rule set based on the URL of the current exception business scenario, match the scenario information of the current exception business scenario with the target encoding rule set, and if the match is successful, determine the processing strategy corresponding to the current exception business scenario from the processing strategy library.

[0039] In an optional approach, step S130 further includes: extracting the URL of the current abnormal business scenario; searching the abnormal business scenario library for the encoding rule set corresponding to the URL of the current abnormal business scenario as the target encoding rule set; abstracting the target encoding rule set into a tree structure and calculating the depth of the tree structure; dividing the abnormal encoding of the current business scenario according to the depth of the tree structure by a preset step size, and mapping the division result to the nodes of the target encoding rule set to generate an abnormal scenario tree structure; and traversing the abnormal scenario tree structure according to the last value of the division result to obtain the matching result.

[0040] In an optional manner, the step S130 further includes: if the last value of the division result obtained through the traversal is a leaf node of the abnormal scenario tree structure, the matching is successful, and the historical abnormal service scenario corresponding to the leaf node is determined as the target historical abnormal service scenario corresponding to the current abnormal service scenario; if the last value of the division result obtained through the traversal is not a leaf node of the abnormal scenario tree structure, the matching fails.

[0041] In an optional manner, the step S130 further includes: determining the processing strategy corresponding to the target historical abnormal service scenario in the processing strategy library as the processing strategy corresponding to the current abnormal service scenario.

[0042] In an optional manner, the method further includes: if the matching fails, updating the abnormal service scenario library and the target coding rule set according to the scenario information of the current abnormal service scenario, and recording the processing strategy corresponding to the current abnormal service scenario in the processing strategy library.

[0043] Specifically, the abnormal scenario coding rule set corresponding to the current abnormal service scenario is located as the target coding rule set according to the URL value of the current abnormal service scenario; the target coding rule set is abstracted as a tree structure, Figure 4 as shown in a tree structure diagram, Figure 4 the depth of the tree structure is calculated; the current service scenario coding is divided according to a preset step length according to the depth of the tree structure, the division result is mapped with the nodes of the abnormal scenario coding rule set, and the abnormal scenario tree structure is generated; the last value of the division result is traversed in the abnormal scenario tree structure, if the last value of the traversal is a leaf node of the abnormal scenario tree structure, the matching is successful, and the historical abnormal service scenario corresponding to the leaf node is determined as the target historical abnormal service scenario corresponding to the current abnormal service scenario, and the processing strategy corresponding to the target historical abnormal service scenario in the processing strategy library is determined as the processing strategy corresponding to the current abnormal service scenario. For problems that can be automatically maintained by the system, after the coding of the abnormal service scenario is uniquely adapted, a repair action can be automatically triggered, and the repair action can be realized by a provided maintenance interface.

[0044] If the current abnormal service scenario cannot uniquely match the corresponding historical abnormal service scenario, the characteristic value of the current abnormal service scenario is extracted according to the scenario information of the current abnormal service scenario, and is recorded in the abnormal service scenario library, so as to expand the coding rule set, and record the corresponding processing strategy in the processing strategy library.

[0045] The method of the embodiment is adopted, the scene information of the historical abnormal business scene of the business system is acquired, the abnormal business scene library is constructed according to the scene information, and the processing strategy corresponding to each historical abnormal business scene in the abnormal business scene library is recorded, so that the processing strategy library is formed;According to the URL and the scene information of the historical abnormal business scene in the abnormal business scene library, the coding rule set corresponding to the URL is constructed;When the business system appears business exception, the target coding rule set corresponding to the URL of the current abnormal business scene is determined according to the URL of the current abnormal business scene, the scene information of the current abnormal business scene is matched with the target coding rule set, if the matching is successful, the processing strategy corresponding to the current abnormal business scene is determined from the processing strategy library.The abnormal business scene detection method of the application can be embedded into any Web business system through the static resource introduction mode, the database is constructed by recording the historical abnormal business scene and the corresponding processing strategy of the business system, the abnormal business scene is coded, marked and matched, the coding rule set corresponding to the URL is constructed, through the automatic operation and maintenance mode, the corresponding abnormal business scene is detected and processed, so as to assist the business system to investigate the abnormal business scene, and improve the efficiency of the operation and maintenance work of the business system.

[0046] Figure 5 The structure schematic diagram of an embodiment of the abnormal business scene detection device of the application is shown. Figure 5 As shown in the figure, the device comprises a database construction module 510, a coding rule set construction module 520 and an abnormal business scene detection module 530.

[0047] The database construction module 510 is used for acquiring the scene information of the historical abnormal business scene of the business system, constructing the abnormal business scene library according to the scene information, and recording the processing strategy corresponding to each historical abnormal business scene in the abnormal business scene library, so as to form the processing strategy library.

[0048] In an optional mode, the scene information of the historical abnormal business scene comprises one or more of the following information: the URL of the historical abnormal business scene, the operation reproduction step related to the historical abnormal business scene, the historical abnormal business scene description information, the abnormal coding, the scene attribute information, the entry time, the associated screenshot ID, the associated video ID and the abnormal feature.

[0049] The coding rule set construction module 520 is used for constructing the coding rule set corresponding to the URL according to the URL and the scene information of the historical abnormal business scene in the abnormal business scene library.

[0050] In an optional manner, the encoding rule set construction module 520 is further configured to: perform feature extraction on the historical abnormal service scenarios with the same URL in the abnormal service scenario library, to obtain feature values, and set item values of the feature values according to the scenario information of the historical abnormal service scenarios; and perform abnormal classification division according to the feature values, to construct the encoding rule set corresponding to the URL.

[0051] The abnormal service scenario detection module 530 is configured to, when the service system has a service exception, determine a target encoding rule set corresponding to the URL of a current abnormal service scenario, match the scenario information of the current abnormal service scenario with the target encoding rule set, and if the matching is successful, determine a processing strategy corresponding to the current abnormal service scenario from the processing strategy library.

[0052] In an optional manner, the abnormal service scenario detection module 530 is further configured to: extract the URL of the current abnormal service scenario, and find the encoding rule set corresponding to the URL of the current abnormal service scenario in the abnormal service scenario library as a target encoding rule set; abstract the target encoding rule set into a tree structure, and calculate the depth of the tree structure; divide the abnormal encoding of the current service scenario according to a preset step length according to the depth of the tree structure, and map the division result with the nodes of the target encoding rule set to generate an abnormal scenario tree structure; and traverse the abnormal scenario tree structure according to the last value of the division result, to obtain a matching result.

[0053] In an optional manner, the abnormal service scenario detection module 530 is further configured to: if the last value of the division result obtained through the traversal is a leaf node of the abnormal scenario tree structure, the matching is successful, and a historical abnormal service scenario corresponding to the leaf node is determined as a target historical abnormal service scenario corresponding to the current abnormal service scenario; and if the last value of the division result obtained through the traversal is not a leaf node of the abnormal scenario tree structure, the matching fails.

[0054] In an optional manner, the abnormal service scenario detection module 530 is further configured to: determine the processing strategy corresponding to the target historical abnormal service scenario in the processing strategy library as the processing strategy corresponding to the current abnormal service scenario.

[0055] In an optional manner, the abnormal service scenario detection module 530 is further configured to: if the matching fails, update the abnormal service scenario library and the target encoding rule set according to the scenario information of the current abnormal service scenario, and record the processing strategy corresponding to the current abnormal service scenario in the processing strategy library.

[0056] The device of the embodiment adopts a database construction module to acquire scene information of historical abnormal business scenes of a business system, constructs an abnormal business scene library according to the scene information, and records processing strategies corresponding to each historical abnormal business scene in the abnormal business scene library to form a processing strategy library; a coding rule set construction module constructs a coding rule set corresponding to a URL according to the URL and the scene information of the historical abnormal business scene in the abnormal business scene library; when the business system has a business abnormality, an abnormal business scene detection module determines a target coding rule set corresponding to the URL of a current abnormal business scene, matches the scene information of the current abnormal business scene with the target coding rule set, and if the matching is successful, determines a processing strategy corresponding to the current abnormal business scene from the processing strategy library. The device can be embedded into any Web business system in a static resource introduction mode, a database is constructed by recording historical abnormal business scenes and corresponding processing strategies of the business system, the abnormal business scenes are coded, marked and matched, a coding rule set corresponding to the URL is constructed, and the corresponding abnormal business scenes are detected and processed in an automatic operation and maintenance mode, thereby assisting the business system in troubleshooting the abnormal business scenes and improving the efficiency of operation and maintenance of the business system.

[0057] The embodiment of the application provides a nonvolatile computer storage medium, and the computer storage medium stores at least one executable instruction.

[0058] The executable instruction can be specifically used for causing the processor to perform the following operations:

[0059] Acquire scene information of historical abnormal business scenes of a business system, construct an abnormal business scene library according to the scene information, and record processing strategies corresponding to each historical abnormal business scene in the abnormal business scene library to form a processing strategy library;

[0060] Construct a coding rule set corresponding to a URL according to the URL and the scene information of a historical abnormal business scene in the abnormal business scene library;

[0061] When the business system has a business abnormality, determine a target coding rule set corresponding to the URL of a current abnormal business scene, match the scene information of the current abnormal business scene with the target coding rule set, and if the matching is successful, determine a processing strategy corresponding to the current abnormal business scene from the processing strategy library.

[0062] Figure 6 The structure schematic diagram of the computing device embodiment of the application is shown, and the specific implementation of the computing device is not limited in the specific embodiment of the application.

[0063] As Figure 6As shown, the computing device can include:

[0064] a processor, a communications interface, a memory, and a communications bus.

[0065] The processor, the communications interface, and the memory communicate with each other through the communications bus. The communications interface is configured to communicate with network elements such as clients or other servers. The processor is configured to execute programs, and can execute the steps of the above-described abnormal service scenario detection method embodiments.

[0066] Specifically, the program can include program code including computer operation instructions.

[0067] The processor can be a central processing unit (CPU) or an application specific integrated circuit (ASIC) or one or more integrated circuits configured to implement embodiments of the present application. The one or more processors included in the server can be the same type of processor, such as one or more CPUs; or can be different types of processors, such as one or more CPUs and one or more ASICs.

[0068] The memory is configured to store programs. The memory can include a high-speed RAM memory and can also include a non-volatile memory such as at least one disk memory.

[0069] The program can be specifically configured to cause the processor to perform the following operations:

[0070] Obtain scenario information of historical abnormal service scenarios of a service system, construct an abnormal service scenario library according to the scenario information, and record processing strategies corresponding to each historical abnormal service scenario in the abnormal service scenario library to form a processing strategy library;

[0071] Construct a set of encoding rules corresponding to the URL according to the URL and the scenario information of the historical abnormal service scenario in the abnormal service scenario library;

[0072] When a service exception occurs in the service system, determine a target set of encoding rules corresponding to the URL of the current abnormal service scenario, match the scenario information of the current abnormal service scenario with the target set of encoding rules, and if the matching is successful, determine a processing strategy corresponding to the current abnormal service scenario from the processing strategy library.

[0073] The algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems can be used with programs in accordance with the teachings herein, or it can prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will be apparent from the description above. In addition, the present embodiments are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages can be used to implement the teachings of the application as described herein, and any references below to specific languages are provided for disclosure of enablement only.

[0074] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to avoid obscuring the understanding of this description.

[0075] Similarly, it is to be understood that the mechanical details of the application that have been set forth in the description above of exemplary embodiments of the application are intended to be illustrative only. As such, the scope of the application is not to be construed as being limited to such preferred embodiments. In other instances, well-known structures and techniques have not been described in detail in order to avoid obscuring aspects of the present application.

[0076] It will be appreciated by those skilled in the art that the modules in the device of the embodiments can be adapted and placed in one or more devices other than the device of the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component and further can be divided into sub-modules or sub-units or sub-components. Any combination of all or some of the disclosed features and any method or device of the embodiments disclosed in the specification (including accompanying claims, abstract and drawings), or any method or device so disclosed, can be combined with any other of the disclosed features or any method or device so disclosed. Unless explicitly stated otherwise, each feature disclosed in the specification (including accompanying claims, abstract and drawings) is implied to be combinable with any other feature disclosed in the specification (including accompanying claims, abstract and drawings) or with any method or device so disclosed.

[0077] Furthermore, those skilled in the art will recognize that, while certain embodiments described herein include certain features that are not included in other embodiments, combinations of features of the different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the claims below, any of the claimed embodiments can be used in any combination.

[0078] Various component embodiments of the application can be implemented in hardware, or as software modules running in one or more processors, or in combinations thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functionality of some or all of the components according to embodiments of the application. The application can also be implemented as a program of instructions for performing part or all of the methods described herein, e.g., a computer program and a computer program product. Such program of the application can be stored on a computer readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier medium, or in any other form.

[0079] It is noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a unitary claim, several devices, apparatuses or means can be listed, comprising means for performing a certain function. The means performed by one device, apparatus or means can also be performed by one or more of the other devices, apparatuses or means. The word 'processor' should be construed to cover any hardware component, and meanwhile one or more processors in a processing system. The word 'processor' can also cover a plurality of processors, e.g., in a multi-processor system. The embodiments were chosen and described in order to explain the principles of the application and the practical application thereof, and to allow others skilled in the art to understand the application for various embodiments with various modifications that are suited to the particular use contemplated.

Claims

1. A method for detecting abnormal business scenarios, characterized in that, include: Obtain scenario information of historical abnormal business scenarios from the business system, construct an abnormal business scenario library based on the scenario information, and record the processing strategies corresponding to each historical abnormal business scenario in the abnormal business scenario library to form a processing strategy library. Based on the URLs of historical abnormal business scenarios in the abnormal business scenario library and the scenario information, construct a set of encoding rules corresponding to the URLs; When the business system experiences a business anomaly, the corresponding target encoding rule set is determined based on the URL of the current abnormal business scenario. The scenario information of the current abnormal business scenario is matched with the target encoding rule set. If the match is successful, the processing strategy corresponding to the current abnormal business scenario is determined from the processing strategy library. The step of determining the corresponding target encoding rule set based on the URL of the current abnormal business scenario, and matching the scenario information of the current abnormal business scenario with the target encoding rule set, further includes: Extract the URL of the current abnormal business scenario, and search the abnormal business scenario library for the set of encoding rules corresponding to the URL of the current abnormal business scenario as the target encoding rule set; The target encoding rule set is abstracted into a tree structure, and the depth of the tree structure is calculated; Based on the depth of the tree structure, the abnormal codes of the current abnormal business scenario are divided according to a preset step size, and the division results are mapped to the nodes of the target coding rule set to generate an abnormal scenario tree structure. Based on the last value of the partitioning result, the abnormal scenario tree structure is traversed to obtain the matching result; wherein, if the last value of the partitioning result obtained after traversal is a leaf node of the abnormal scenario tree structure, the matching is successful, and the historical abnormal business scenario corresponding to the leaf node is determined as the target historical abnormal business scenario corresponding to the current abnormal business scenario; if the last value of the partitioning result obtained after traversal is not a leaf node of the abnormal scenario tree structure, the matching fails.

2. The method according to claim 1, characterized in that, The scenario information of the historical abnormal business scenarios includes one or more of the following: the URL of the historical abnormal business scenario, the operation reproduction steps related to the historical abnormal business scenario, the description information of the historical abnormal business scenario, the abnormal code, the scenario attribute information, the entry time, the associated screenshot ID, the associated video ID, and the abnormal characteristics.

3. The method according to claim 1, characterized in that, The step of constructing a set of encoding rules corresponding to the URLs based on the URLs of historical abnormal business scenarios in the abnormal business scenario library and the scenario information further includes: For historical abnormal business scenarios with the same URL in the abnormal business scenario library, feature extraction is performed on the historical abnormal business scenarios to obtain feature values, and the item values ​​of the feature values ​​are set according to the scenario information of the historical abnormal business scenarios. Based on the aforementioned feature values, anomaly classification is performed, and a set of encoding rules corresponding to the URL is constructed.

4. The method according to claim 1, characterized in that, The step of determining the processing strategy corresponding to the current abnormal business scenario from the processing strategy library further includes: The processing strategy corresponding to the target historical abnormal business scenario in the processing strategy library is determined as the processing strategy corresponding to the current abnormal business scenario.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: If the matching fails, the abnormal business scenario library and the target encoding rule set are updated according to the scenario information of the current abnormal business scenario, and the processing strategy corresponding to the current abnormal business scenario is recorded in the processing strategy library.

6. An abnormal business scenario detection device, characterized in that, include: The database construction module is used to obtain scenario information of historical abnormal business scenarios of the business system, construct an abnormal business scenario library based on the scenario information, and record the processing strategies corresponding to each historical abnormal business scenario in the abnormal business scenario library to form a processing strategy library. The encoding rule set construction module is used to construct an encoding rule set corresponding to the URL based on the URL of the historical abnormal business scenarios in the abnormal business scenario library and the scenario information. An abnormal business scenario detection module is used to determine the corresponding target encoding rule set based on the URL of the current abnormal business scenario when the business system experiences a business abnormality, match the scenario information of the current abnormal business scenario with the target encoding rule set, and if the match is successful, determine the processing strategy corresponding to the current abnormal business scenario from the processing strategy library. The abnormal business scenario detection module is further used for: Extract the URL of the current abnormal business scenario, and search the abnormal business scenario library for the set of encoding rules corresponding to the URL of the current abnormal business scenario as the target encoding rule set; The target encoding rule set is abstracted into a tree structure, and the depth of the tree structure is calculated; Based on the depth of the tree structure, the abnormal codes of the current abnormal business scenario are divided according to a preset step size, and the division results are mapped to the nodes of the target coding rule set to generate an abnormal scenario tree structure. Based on the last value of the partitioning result, the abnormal scenario tree structure is traversed to obtain the matching result; wherein, if the last value of the partitioning result obtained after traversal is a leaf node of the abnormal scenario tree structure, the matching is successful, and the historical abnormal business scenario corresponding to the leaf node is determined as the target historical abnormal business scenario corresponding to the current abnormal business scenario; if the last value of the partitioning result obtained after traversal is not a leaf node of the abnormal scenario tree structure, the matching fails.

7. A computing device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the abnormal business scenario detection method as described in any one of claims 1-5.

8. A computer storage medium, characterized in that, The storage medium stores at least one executable instruction, which causes the processor to perform the operation corresponding to the abnormal business scenario detection method as described in any one of claims 1-5.

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