Identification method for non-domestic components of application system and related equipment

Abstract

The invention provides a method for identifying non-domestic components of an application system and related equipment, and belongs to the field of computers, the method comprises the following steps: determining application monitoring data; the application monitoring data is data collected by a probe in the system; performing component calling analysis on the application monitoring data to obtain an application calling link; determining behavior data corresponding to each component in the application calling link according to the application monitoring data and the application calling link; forming an original data set by the behavior data, the component metadata and the code data corresponding to the component; based on the original data set of the component, performing feature analysis on the component from a plurality of feature dimensions to obtain a feature data set of the component; and according to a preset feature rule base and the feature data set of the component, determining whether the component is a non-domestic component. By applying the method, the component type can be automatically identified through feature analysis and feature rule matching, and the efficiency and accuracy of component identification can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method for identifying non-domestic components of an application system and related equipment. Background Art

[0002] With the development of computer technology, various application systems have become widely used to handle various business operations in various fields. Components are one of the basic units in an application system. Components have independent functions and interfaces, and they work together to achieve complex system functions. In real-world business scenarios, it is often necessary to identify whether components in an application system are non-domestic components.

[0003] At present, the component types of components in the application system are generally identified through manual investigation. That is, the inspection personnel manually check the component information of each component in the system, such as component name, developer information, etc., and judge whether the component is a domestic component or a non-domestic component based on the component information.

[0004] Application systems typically contain a large number of components. Existing identification methods require manual inspection of component information one by one, consuming significant manpower and time, resulting in low component type identification efficiency. Furthermore, manual identification is affected by individual experience and energy, and some component information may be disguised. This often leads to biased identification, resulting in poor component type identification accuracy. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides a method for identifying non-domestic components of an application system to solve the problem that the existing component identification method relies on manual judgment of component information one by one, resulting in low efficiency and accuracy of component identification.

[0006] The embodiment of the present invention also provides a device for identifying non-domestic components of an application system to ensure the actual implementation and application of the above method.

[0007] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0008] A method for identifying non-domestic components of an application system, comprising:

[0009] Determine application monitoring data corresponding to the business process flow of the application system; the application monitoring data is data collected by various probes preset in the application system;

[0010] Performing component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component;

[0011] Determining behavior data corresponding to each component based on the application monitoring data and the application call link;

[0012] For each of the components, obtain component metadata and code data corresponding to the component, and combine the behavior data, component metadata, and code data corresponding to the component to form an original data set of the component;

[0013] For each of the components, based on the original data set of the component, feature analysis is performed on the component from multiple preset feature dimensions to obtain a feature data set corresponding to the component, where the feature data set includes feature data of each of the feature dimensions;

[0014] For each of the components, whether the component is a non-domestic component is determined based on a preset feature rule library and a feature data set corresponding to the component.

[0015] In the above method, optionally, the preset multiple feature dimensions include a metadata feature dimension, and performing feature analysis on the component based on the metadata feature dimension includes:

[0016] Perform metadata feature analysis on the component metadata corresponding to the component to obtain metadata feature analysis results;

[0017] The metadata feature analysis result is used as feature data of the metadata feature dimension.

[0018] In the above method, optionally, the preset multiple feature dimensions include a behavioral feature dimension, and performing feature analysis on the component based on the behavioral feature dimension includes:

[0019] Performing a behavioral feature analysis on the component based on the behavioral data corresponding to the component to obtain a behavioral feature analysis result; the behavioral feature analysis result reflects the behavioral pattern of the component in the application call link;

[0020] The behavior feature analysis result is used as feature data of the behavior feature dimension.

[0021] In the above method, optionally, the preset multiple feature dimensions include a code structure feature dimension, and performing feature analysis on the component based on the code structure feature dimension includes:

[0022] Perform code structure feature analysis on the code data corresponding to the component to obtain a code structure feature analysis result;

[0023] The code structure feature analysis result is used as feature data of the code structure feature dimension.

[0024] In the above method, optionally, the preset multiple feature dimensions include a compatibility feature dimension, and performing feature analysis on the component based on the compatibility feature dimension includes:

[0025] Performing a compatibility analysis on the component based on code data corresponding to the component to obtain a compatibility analysis result corresponding to the component, wherein the compatibility analysis result reflects the compatibility of the component with a domestic chip or a domestic operating system;

[0026] The compatibility analysis result is used as feature data of the compatibility feature dimension.

[0027] Optionally, the above method includes determining whether the component is a non-local component based on a preset feature rule library and a feature data set corresponding to the component, including:

[0028] Obtaining, from the feature rule library, feature rules corresponding to each feature dimension;

[0029] For each feature dimension of the feature data in the feature data set corresponding to the component, determine whether the feature data matches the feature rule corresponding to the feature dimension, and use the determination result as the feature matching result corresponding to the feature dimension;

[0030] If the feature matching results corresponding to each of the feature dimensions indicate that the feature data of the feature dimension matches the feature rule corresponding to the feature dimension, then the component is determined to be a domestically produced component.

[0031] The above method may optionally further include:

[0032] If there is a feature matching result corresponding to at least one feature dimension, and the feature data representing the feature dimension does not match the feature rule corresponding to the feature dimension, then the component is determined to be a non-domestic component.

[0033] A device for identifying non-domestic components of an application system, comprising:

[0034] A first determining unit is configured to determine application monitoring data corresponding to a business process flow of an application system; the application monitoring data is data collected by various probes preset in the application system;

[0035] A call analysis unit, configured to perform component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component;

[0036] A second determining unit is configured to determine behavior data corresponding to each of the components based on the application monitoring data and the application call link;

[0037] A data acquisition unit, configured to acquire, for each component, component metadata and code data corresponding to the component, and combine the behavior data, component metadata and code data corresponding to the component into an original data set of the component;

[0038] a feature analysis unit configured to perform feature analysis on each component based on an original data set of the component from a plurality of preset feature dimensions to obtain a feature data set corresponding to the component, the feature data set including feature data of each of the feature dimensions;

[0039] The third determining unit is used to determine, for each of the components, whether the component is a non-domestic component based on a preset feature rule library and a feature data set corresponding to the component.

[0040] A storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the above-mentioned method for identifying non-domestic components of the application system.

[0041] An electronic device includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the above-mentioned method for identifying non-domestic components of an application system.

[0042] Based on the above embodiment of the present invention, a method for identifying non-domestic components of an application system is provided, comprising: determining application monitoring data corresponding to the business processing flow of the application system; the application monitoring data is data collected by various probes preset in the application system; performing component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes various components called by the application system and the call relationship between the various components; determining the behavior data corresponding to each component based on the application monitoring data and the application call link; for each component, obtaining the component metadata and code data corresponding to the component, and combining the behavior data, component metadata and code data corresponding to the component to form an original data set of the component; for each component, based on the original data set of the component, performing feature analysis on the component from multiple preset feature dimensions to obtain a feature data set corresponding to the component, the feature data set including feature data of each feature dimension; for each component, determining whether the component is a non-domestic component based on a preset feature rule library and the feature data set corresponding to the component. Applying the method provided by the embodiment of the present invention, the operation data of the application system business processing process can be monitored by implanting probes to obtain application monitoring data, and the components called during the system operation process can be identified based on the application monitoring data. Based on the behavioral data, code data, and metadata of the identified components, a multi-dimensional feature analysis is performed on the components, and feature rule judgment is used to determine whether the components are non-domestic components. Based on the calls to each component during system operation, it is possible to automatically identify whether each component in the system is a non-domestic component, eliminating the need for manual component inspection to identify components, which helps reduce manpower consumption and improve the efficiency of component type identification. Secondly, during the component type identification process, the component type is identified through a feature rule library, which can be adaptively adjusted according to needs, which helps improve the accuracy of component type identification. Moreover, during the identification process, the component code and component behavior, which reflect the characteristics of the component operation, are combined for identification. Components can be identified based on their actual operating characteristics. Even components with disguised component information can be effectively identified, which helps further improve the accuracy of component type identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0044] Figure 1A flow chart of a method for identifying non-domestic components of an application system provided by an embodiment of the present invention;

[0045] Figure 2 An example diagram of an application system architecture provided by an embodiment of the present invention;

[0046] Figure 3 An example diagram of an application call link provided by an embodiment of the present invention;

[0047] Figure 4 A schematic diagram of a component identification process provided by an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of the structure of a device for identifying non-domestic components of an application system provided by an embodiment of the present invention;

[0049] Figure 6 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0052] The embodiment of the present invention provides a method for identifying non-domestic components of an application system. The method can be applied to a component identification tool, and the execution subject can be a processor of the component identification tool. The flow chart of the method is as follows: Figure 1 Shown, including:

[0053] S101: Determine application monitoring data corresponding to a business process flow of an application system; the application monitoring data is data collected by various probes preset in the application system;

[0054] The method provided in the embodiment of the present invention is used to detect the type of each component in the application system and identify whether the component is a non-domestic component or a domestic component. The application system in the embodiment of the present invention can be an enterprise-level business system, a mobile application, or a cloud-native application and other types of system objects. According to actual needs, probes are implanted in various nodes of the application system in advance. These nodes can cover various important links such as application system startup, component loading, service calls, etc. For example, the probes can be implanted in the initialization code segment when the application system is started and at the entry of various component loading functions. Taking the application system (e-commerce application system) that implements e-commerce services as an example, the architecture of the application system can be as follows Figure 2 As shown, the system specifically includes a client, a server, and a database. Initialization modules are deployed in each of the client and server. Probes can be implanted in both the client and server initialization modules. The probes can be lightweight to minimize their impact on application system performance, preventing slowdowns or anomalies caused by the implantation of probes.

[0055] The probe in the embodiment of the present invention is a tool for data collection, which is mainly used to collect various types of data in the running process of the application system in real time, including but not limited to the loading order of components, call parameters, return values ​​and other information. Taking the e-commerce application system as an example, you can refer to Figure 2 In the illustrated architecture, probes embedded in the client can collect relevant data from the client, and probes embedded in the server can collect relevant data from the server. When a user initiates a product query request, the probes deployed on the client and server can record the participation of each component and related data from the time the client page initiates the request to the backend server calling the relevant components to query the data, process it, and return the results. For example, the time and parameters of the client-side order query component sending the request to the server, the time the server-side product data query component receives the request, the processing time, and the result data returned to the client are recorded.

[0056] In the method provided by the embodiment of the present invention, during the operation of the application system, the preset probes will collect various operating data of the system in real time. According to actual identification needs, after the application system performs business processing in response to the business request, the relevant data in the business processing flow collected by the probes can be obtained to identify the components involved in the business processing flow. Specifically, after the application system completes the processing of a business request, the components involved in the business processing flow of this type can be identified based on the relevant data of the request. Alternatively, after the application system completes the processing of multiple business requests of the same business type, the components involved in the business processing flow of this type can be identified based on the relevant data of the multiple requests.

[0057] When it is necessary to identify the components involved in the business processing flow of a certain type of business, the component identification tool can determine the request data that needs to be obtained based on actual needs. For example, if it is necessary to obtain relevant data of a certain business request, the trace ID corresponding to the business request can be used to obtain the relevant data of the request from the data collected by each probe through the trace ID, and the obtained data can be used as the application monitoring data corresponding to the business processing flow.

[0058] S102: Analyze component calls on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes components called by the application system and call relationships between the components;

[0059] In the method provided by the embodiment of the present invention, the component identification tool can perform component call analysis on the application monitoring data through data mining technology. On the one hand, it can identify the various components called in the business processing flow based on the component call operations recorded in the application monitoring data. On the other hand, the call time of each component can be determined based on the timestamp information in the application monitoring data. Based on the call time and call operation of each component, the call relationship between each component can be analyzed, including the direct call relationship between components and the indirect call relationship between components. Based on the call relationship between each component, a corresponding call link graph can be constructed, and the call link graph can be used as the application call link corresponding to the corresponding business processing flow. It can be understood that the application call link refers to the path of mutual calls between each component in a certain order, which can describe the execution order and dependency relationship between each component during the program running process. For example, with respect to the business processing flow of order processing of an e-commerce application system, the application call link (i.e., the e-commerce call link) corresponding to the process can be as follows Figure 3 As shown in the figure, in this business processing flow, data flows from the front-end order submission component to the back-end order processing logic component, and then to the inventory query component and payment interface component. By analyzing the flow and format changes of data between various components, we can understand the function of each component in the order processing business.

[0060] S103: Determine behavior data corresponding to each component based on the application monitoring data and the application call link;

[0061] In the method provided by the embodiments of the present invention, the component identification tool can analyze the behavior of each component in the business process based on application monitoring data and application call links, such as information about being called, information about calls to other components, and information about interactions with other components. Data related to the operation of each component in the application monitoring data is used as the corresponding behavior data of the component.

[0062] It should be noted that in actual implementation scenarios, if this is not the first time that type identification is performed on components in the application system, that is, some components in the application system have already been identified, then there may be components in the current application call link that have completed type identification. Components that have completed the identification process do not need to be processed repeatedly.

[0063] S104: For each component, obtain component metadata and code data corresponding to the component, and combine the behavior data, component metadata, and code data corresponding to the component to form an original data set of the component;

[0064] In the method provided by an embodiment of the present invention, the component identification tool can obtain the component metadata and code data corresponding to each component from the corresponding data storage location. Component metadata is data describing the basic details of the component, and may include, for example, the component name, version number, developer information, etc. For each component, the component metadata, code data, and behavior data corresponding to the component are combined to form an original dataset for the component. That is, the original dataset contains the component metadata, code data, and behavior data of the component.

[0065] S105: For each component, based on the original data set of the component, perform feature analysis on the component from multiple preset feature dimensions to obtain a feature data set corresponding to the component, where the feature data set includes feature data of each feature dimension;

[0066] In the method provided by the embodiment of the present invention, multiple feature dimensions can be set in advance according to actual needs. For example, multiple feature dimensions such as metadata feature dimensions, behavioral feature dimensions, code structure feature dimensions, and compatibility feature dimensions can be configured, and other feature dimensions can also be configured. The component identification tool can perform multi-dimensional feature analysis on each component based on the pre-set multi-dimensional feature analysis method. Specifically, for each component, according to the analysis requirements corresponding to each feature dimension, the original data required for each feature dimension can be obtained from the original data set of the component. According to the feature analysis method of each feature dimension, feature extraction is performed on the original data corresponding to each feature dimension to obtain feature data of each feature dimension. The feature data of each feature dimension are combined into a feature data set corresponding to the component, thereby performing multi-dimensional feature analysis on the component.

[0067] S106: For each of the components, determine whether the component is a non-domestic component based on a preset feature rule library and a feature data set corresponding to the component.

[0068] In the method provided by the embodiment of the present invention, a feature rule library can be pre-built based on actual needs. The feature rule library contains feature rules for multiple feature dimensions. The feature rules in the feature rule library can be continuously updated according to actual needs to ensure the accuracy and timeliness of component identification. For example, when a new domestically produced component based on artificial intelligence emerges, corresponding feature rules can be configured based on the unique characteristics of the component and incorporated into the feature rule library to facilitate the identification of that type of component.

[0069] In the method provided by an embodiment of the present invention, the component identification tool can judge whether the characteristics of each component comply with the corresponding rules based on a preset feature rule library and a feature data set corresponding to each component, so as to identify whether the characteristics of each component comply with the characteristics of a domestic component or a non-domestic component, thereby determining the component type of each component involved in the current business processing flow, that is, a domestic component or a non-domestic component.

[0070] As the application system runs, the application system can process different business processing flows. Based on the method shown in steps S101 to S106, the components involved in different business processing flows can be identified, and then the types of all components in the application system can be identified.

[0071] Based on the method provided by the embodiment of the present invention, the application monitoring data corresponding to the business processing flow of the application system can be determined; the application monitoring data is data collected by various probes preset in the application system; component call analysis is performed on the application monitoring data to obtain the application call link corresponding to the business processing flow; the application call link includes the various components called by the application system and the call relationship between the various components; based on the application monitoring data and the application call link, the behavior data corresponding to each component is determined; for each component, the component metadata and code data corresponding to the component are obtained, and the behavior data, component metadata and code data corresponding to the component are combined to form the original data set of the component; for each component, based on the original data set of the component, the component is analyzed from multiple preset feature dimensions to obtain the feature data set corresponding to the component, and the feature data set includes feature data of each feature dimension; for each component, based on the preset feature rule library and the feature data set corresponding to the component, it is determined whether the component is a non-domestic component. Applying the method provided by the embodiment of the present invention, the operation data in the business processing process of the application system can be monitored by implanting probes, application monitoring data can be obtained, and components called during the system operation can be identified based on the application monitoring data. Based on the behavioral data, code data, and metadata of the identified components, a multi-dimensional feature analysis is performed on the components, and feature rule judgment is used to determine whether the components are non-domestic components. Based on the calls to each component during system operation, it is possible to automatically identify whether each component in the system is a non-domestic component, eliminating the need for manual component inspection to identify components, which helps reduce manpower consumption and improve the efficiency of component type identification. Secondly, during the component type identification process, the component type is identified through a feature rule library, which can be adaptively adjusted according to needs, which helps improve the accuracy of component type identification. Moreover, during the identification process, the component code and component behavior, which reflect the characteristics of the component operation, are combined for identification. Components can be identified based on their actual operating characteristics. Even components with disguised component information can be effectively identified, which helps further improve the accuracy of component type identification.

[0072] exist Figure 1 Based on the method shown above, in the method provided by the embodiment of the present invention, the multiple preset feature dimensions mentioned in step S105 include metadata feature dimensions. That is, the process of performing feature analysis on the component based on the multiple preset feature dimensions includes performing feature analysis on the component based on the metadata feature dimension. In the method provided by the embodiment of the present invention, the process of performing feature analysis on the component based on the metadata feature dimension specifically includes:

[0073] Perform metadata feature analysis on the component metadata corresponding to the component to obtain metadata feature analysis results;

[0074] The metadata feature analysis result is used as feature data of the metadata feature dimension.

[0075] In the method provided by an embodiment of the present invention, each preset feature dimension includes a metadata feature dimension. When performing feature analysis on a component from the metadata feature dimension, the component metadata corresponding to the component can be obtained from the original data set of the component. According to a predetermined feature analysis method for metadata, metadata feature analysis is performed on the component metadata of the component, for example, analyzing whether the component name is the name of a domestic component, whether the developer of the component is a domestic entity, etc., to obtain the metadata feature analysis results. The metadata feature analysis results are used as the feature data of the component in the metadata feature dimension. It can be understood that the feature data of the metadata feature dimension is the feature data corresponding to the metadata feature dimension in the feature data set corresponding to the component.

[0076] exist Figure 1 Based on the method shown, in the method provided by the embodiment of the present invention, the multiple preset feature dimensions mentioned in step S105 include a behavioral feature dimension, that is, the process of performing feature analysis on the component from the multiple preset feature dimensions includes performing feature analysis on the component from the behavioral feature dimension. In the method provided by the embodiment of the present invention, the process of performing feature analysis on the component from the behavioral feature dimension specifically includes:

[0077] Performing a behavioral feature analysis on the component based on the behavioral data corresponding to the component to obtain a behavioral feature analysis result; the behavioral feature analysis result reflects the behavioral pattern of the component in the application call link;

[0078] The behavior feature analysis result is used as feature data of the behavior feature dimension.

[0079] In the method provided by the embodiment of the present invention, the preset characteristic dimensions include a behavioral characteristic dimension. When a component is subjected to characteristic analysis from the behavioral characteristic dimension, the behavioral data corresponding to the component can be obtained from the original data set of the component. According to a predetermined behavioral analysis method, the behavioral characteristics of the component are analyzed based on the behavioral data of the component. For example, the behavioral pattern of the component in the application call link, such as the calling frequency, response time, interaction logic with other components, etc., is analyzed to obtain the behavioral characteristic analysis results. The behavioral characteristic analysis results are used as the characteristic data of the component in the behavioral characteristic dimension. The characteristic data of the behavioral characteristic dimension is the characteristic data of the characteristic dimension corresponding to the behavioral characteristic dimension in the characteristic data set corresponding to the component.

[0080] exist Figure 1Based on the method shown, in the method provided by the embodiment of the present invention, the multiple preset feature dimensions mentioned in step S105 include the code structure feature dimension, that is, the process of performing feature analysis on the component based on the multiple preset feature dimensions includes performing feature analysis on the component based on the code structure feature dimension. In the method provided by the embodiment of the present invention, the process of performing feature analysis on the component based on the code structure feature dimension specifically includes:

[0081] Perform code structure feature analysis on the code data corresponding to the component to obtain a code structure feature analysis result;

[0082] The code structure feature analysis result is used as feature data of the code structure feature dimension.

[0083] In the method provided by the embodiment of the present invention, the preset feature dimensions include a code structure feature dimension. When a feature analysis is performed on a component from the code structure feature dimension, the code data corresponding to the component can be obtained from the original data set of the component. According to a predetermined feature analysis method for the code structure, a code structure feature analysis is performed on the code data corresponding to the component, for example, features such as function call relationships and variable usage patterns in the code are extracted to obtain a code structure feature analysis result. The code structure feature analysis result is used as the feature data of the component in the code structure feature dimension. The feature data of the code structure feature dimension is the feature data corresponding to the code structure feature dimension in the feature data set corresponding to the component.

[0084] exist Figure 1 Based on the method shown, in the method provided by the embodiment of the present invention, the multiple preset feature dimensions mentioned in step S105 include a compatibility feature dimension, that is, the process of performing feature analysis on the component based on the multiple preset feature dimensions includes performing feature analysis on the component based on the compatibility feature dimension. In the method provided by the embodiment of the present invention, the process of performing feature analysis on the component based on the compatibility feature dimension specifically includes:

[0085] Performing a compatibility analysis on the component based on code data corresponding to the component to obtain a compatibility analysis result corresponding to the component, wherein the compatibility analysis result reflects the compatibility of the component with a domestic chip or a domestic operating system;

[0086] The compatibility analysis result is used as feature data of the compatibility feature dimension.

[0087] In the method provided by the embodiment of the present invention, each preset feature dimension includes a compatibility feature dimension. When performing feature analysis on a component from the compatibility feature dimension, the code data corresponding to the component can be obtained from the original data set of the component. According to a predetermined compatibility analysis method, a compatibility analysis is performed on the component based on the code data corresponding to the component. Compatibility analysis refers to analyzing the compatibility of the component with domestic chips or domestic operating systems, such as analyzing the features of the component in terms of system resource calls, underlying driver interactions, etc., to obtain a compatibility analysis result. The compatibility analysis result of the component is used as the feature data of the component in the compatibility feature dimension. The feature data of the compatibility feature dimension is the feature data corresponding to the compatibility feature dimension in the feature data set corresponding to the component.

[0088] It should be noted that the specific descriptions of feature dimensions and feature analysis in the above embodiments are only for the purpose of better illustrating the specific implementation methods provided by the method provided by the present invention. In the specific implementation process, each feature dimension can be configured according to actual needs. Each feature dimension can include the above-mentioned metadata feature dimension, behavior feature dimension, code structure feature dimension, and compatibility feature dimension at the same time. It can include only any of the above-mentioned feature dimensions, or other feature dimensions can be configured as needed. In the feature analysis process of each feature dimension, the corresponding analysis operation can be configured according to actual needs, which will not affect the function of the method provided by the embodiment of the present invention.

[0089] exist Figure 1 On the basis of the method shown in FIG. 1 , in the method provided by the embodiment of the present invention, the process of determining whether the component is a non-domestic component based on the preset feature rule library and the feature data set corresponding to the component mentioned in step S106 includes:

[0090] Obtaining, from the feature rule library, feature rules corresponding to each feature dimension;

[0091] In the method provided by the embodiment of the present invention, the feature rule library is pre-configured with feature rules corresponding to each feature dimension. For example, each feature dimension includes a metadata feature dimension, a behavioral feature dimension, a code structure feature dimension, and a compatibility feature dimension. The feature rule library is correspondingly configured with metadata feature rules corresponding to the metadata feature dimension, behavioral feature rules corresponding to the behavioral feature dimension, code structure feature rules corresponding to the code structure feature dimension, and compatibility feature rules corresponding to the compatibility feature dimension. Each feature rule in the feature rule library describes the feature requirements that domestic components need to meet. For example, corresponding compatibility feature rules can be formulated based on different combinations of domestic chips and operating systems. The compatibility feature rules can set specifications and features for components that adapt to corresponding domestic chips and domestic operating systems in terms of system resource calls, underlying driver interactions, etc.

[0092] In the method provided by the embodiment of the present invention, the component identification tool can obtain the feature rules corresponding to each feature dimension from the feature rule library.

[0093] For each feature dimension of the feature data in the feature data set corresponding to the component, determine whether the feature data matches the feature rule corresponding to the feature dimension, and use the determination result as the feature matching result corresponding to the feature dimension;

[0094] In the method provided by an embodiment of the present invention, when identifying the component type of each component, a rule judgment is performed on the feature data of each feature dimension in the feature database corresponding to the current component, and the feature data of the current feature dimension is matched with the feature rule corresponding to the current feature dimension to obtain a feature matching result corresponding to the feature dimension. The feature matching result indicates whether the feature data of the feature dimension matches the feature rule corresponding to the feature dimension. Determining whether the feature data of a feature dimension matches the feature rule corresponding to the feature dimension refers to determining whether the feature data meets the feature requirements set in the feature rule. For example, the behavior feature rules set the calling frequency range and response time range of the domestically produced components. When judging whether the feature data of the behavior feature dimension matches the behavior feature rules, the calling frequency of the component in the feature data is compared with the calling frequency range in the behavior feature rules, and the response time of the component in the feature data is compared with the response time range in the behavior feature rules. If the calling frequency of the component is within the predetermined calling frequency range, and the response time of the component is within the predetermined response time range, then the feature data of the behavior feature dimension of the component is considered to match the feature rules of the behavior feature dimension. If the calling frequency and / or response time of the component are not within the corresponding range, then the feature data of the behavior feature dimension of the component is considered to not match the feature rules of the behavior feature dimension. In this way, the feature matching results of the current component in each feature dimension can be obtained.

[0095] If the feature matching results corresponding to each of the feature dimensions indicate that the feature data of the feature dimension matches the feature rule corresponding to the feature dimension, then the component is determined to be a domestically produced component.

[0096] In the method provided by an embodiment of the present invention, the component type can be determined based on the feature matching results for each feature dimension of the current component. Specifically, if the feature matching results for each feature dimension of the current component indicate that the feature data for that feature dimension matches the corresponding feature rule, the current component is determined to be a domestically produced component.

[0097] On the basis of the method provided in the above embodiment, the method provided in the embodiment of the present invention further includes:

[0098] If there is a feature matching result corresponding to at least one feature dimension, and the feature data representing the feature dimension does not match the feature rule corresponding to the feature dimension, then the component is determined to be a non-domestic component.

[0099] In the method provided by an embodiment of the present invention, if the feature matching results of each feature dimension of the current component do not all represent that the feature data of the feature dimension matches the corresponding feature rules, that is, there are one or more feature matching results representing that the feature data does not match the corresponding feature rules, then the current component is determined to be a non-domestic component.

[0100] In order to better illustrate the method provided by the embodiment of the present invention, on the basis of the methods provided by the various embodiments above, the embodiment of the present invention provides another method for identifying non-domestic components of an application system. The method provided by the embodiment of the present invention pre-implants probes in various key nodes of the application system, and monitors various data in the process of business processing by the application system through the probes. Component call analysis is performed based on the application monitoring data in the business processing flow, an application call link is constructed, and the components involved in the application call link are used as components to be identified. In the method provided by the embodiment of the present invention, the preset feature dimensions include metadata feature dimensions, behavioral feature dimensions, code structure feature dimensions, and compatibility feature dimensions. Feature rules corresponding to each feature dimension are preset in the feature rule library, specifically including: metadata feature rules corresponding to the metadata feature dimension, behavioral feature rules corresponding to the behavioral feature dimension, code structure feature rules corresponding to the code structure feature dimension, and compatibility feature rules corresponding to the compatibility feature dimension, etc.

[0101] In the method provided by the embodiment of the present invention, the process of performing component identification on the component to be identified can be as follows: Figure 4 As shown. First, for the component to be identified, its feature data needs to be updated. Specifically, the component metadata, behavior data and code data corresponding to the component to be identified need to be obtained as the original feature data. Feature extraction is performed on the original feature data of the component from each feature dimension to obtain the feature data of each feature dimension. For the feature data of each feature dimension, it is determined whether the feature data matches the feature rules corresponding to the feature dimension. If the feature data of each feature dimension matches the corresponding feature rules, the current component is determined to be a domestically produced component. If there is feature data that does not match the corresponding feature rules, the current component is determined to be a non-domesticated component.

[0102] Based on the method provided in the embodiment of the present invention, it is possible to efficiently, accurately and comprehensively identify whether the components in the application system are domestically produced components, overcoming the shortcomings of the existing technology in component detection efficiency, accuracy and versatility.

[0103] and Figure 1Corresponding to the method for identifying non-domestic components of an application system shown in FIG, an embodiment of the present invention further provides an apparatus for identifying non-domestic components of an application system, for identifying Figure 1 The specific implementation of the method shown in is shown in the structural diagram. Figure 5 Shown, including:

[0104] The first determining unit 201 is configured to determine application monitoring data corresponding to a business process flow of an application system; the application monitoring data is data collected by various probes preset in the application system;

[0105] The call analysis unit 202 is configured to perform component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component;

[0106] A second determining unit 203 is configured to determine behavior data corresponding to each component based on the application monitoring data and the application call link;

[0107] The data acquisition unit 204 is configured to acquire, for each component, component metadata and code data corresponding to the component, and combine the behavior data, component metadata and code data corresponding to the component into an original data set of the component;

[0108] A feature analysis unit 205 is configured to perform feature analysis on each component based on an original data set of the component from a plurality of preset feature dimensions to obtain a feature data set corresponding to the component, the feature data set including feature data of each feature dimension;

[0109] The third determining unit 206 is configured to determine, for each component, whether the component is a non-domestic component based on a preset feature rule library and a feature data set corresponding to the component.

[0110] By using the device provided by the embodiments of the present invention, operational data during application system business processing can be monitored by implanting probes, obtaining application monitoring data. Based on the application monitoring data, components called during system operation can be identified. Based on the behavioral data, code data, and metadata of the identified components, multi-dimensional feature analysis is performed on the components, and feature rule judgment is used to determine whether the components are non-domestic components. Based on the calls made to each component during system operation, it is possible to automatically determine whether each component in the system is non-domestic, eliminating the need for manual component inspection. This helps reduce manpower consumption and improves the efficiency of component type identification. Furthermore, during component type identification, component types are identified using a feature rule library that can be adaptively adjusted based on demand, which helps improve the accuracy of component type identification. Furthermore, during the identification process, component code and component behavior, which reflect component operation, are combined for identification. Components can be identified based on their actual operational characteristics. This allows for effective identification even of components with disguised component information, further improving the accuracy of component type identification.

[0111] exist Figure 5 Based on the device shown, the device provided by the embodiment of the present invention can be further expanded into multiple units. The functions of each unit can be found in the descriptions of the various embodiments provided in the previous text on the method for identifying non-domestic components of the application system, and no further examples will be given here.

[0112] An embodiment of the present invention also provides a storage medium, which includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the above-mentioned method for identifying non-domestic components of the application system.

[0113] The embodiment of the present invention further provides an electronic device, the structural diagram of which is shown in FIG. Figure 6 As shown, the system specifically includes a memory 301 and one or more instructions 302, wherein the one or more instructions 302 are stored in the memory 301 and are configured to be executed by one or more processors 303 to perform the following operations:

[0114] Determine application monitoring data corresponding to the business process flow of the application system; the application monitoring data is data collected by various probes preset in the application system;

[0115] Performing component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component;

[0116] Determining behavior data corresponding to each component based on the application monitoring data and the application call link;

[0117] For each of the components, obtain component metadata and code data corresponding to the component, and combine the behavior data, component metadata, and code data corresponding to the component to form an original data set of the component;

[0118] For each of the components, based on the original data set of the component, feature analysis is performed on the component from multiple preset feature dimensions to obtain a feature data set corresponding to the component, where the feature data set includes feature data of each of the feature dimensions;

[0119] For each of the components, whether the component is a non-domestic component is determined based on a preset feature rule library and a feature data set corresponding to the component.

[0120] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple. For relevant parts, refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0121] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0122] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying non-domestic components of an application system, characterized in that: include: Determine the application monitoring data corresponding to the business processing flow of the application system; The application monitoring data is data collected by various probes preset in the application system; Performing component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component; Determining behavior data corresponding to each component based on the application monitoring data and the application call link; For each of the components, obtain component metadata and code data corresponding to the component, and combine the behavior data, component metadata, and code data corresponding to the component to form an original data set of the component; For each of the components, based on the original data set of the component, feature analysis is performed on the component from multiple preset feature dimensions to obtain a feature data set corresponding to the component, where the feature data set includes feature data of each of the feature dimensions; For each of the components, whether the component is a non-domestic component is determined based on a preset feature rule library and a feature data set corresponding to the component.

2. The method for identifying non-domestic components of an application system according to claim 1, characterized in that: The preset multiple feature dimensions include a metadata feature dimension, and performing feature analysis on the component based on the metadata feature dimension includes: Perform metadata feature analysis on the component metadata corresponding to the component to obtain metadata feature analysis results; The metadata feature analysis result is used as feature data of the metadata feature dimension.

3. The method for identifying non-domestic components of an application system according to claim 1, characterized in that: The preset multiple feature dimensions include a behavioral feature dimension, and feature analysis of the component based on the behavioral feature dimension includes: Performing a behavioral feature analysis on the component based on the behavioral data corresponding to the component to obtain a behavioral feature analysis result; the behavioral feature analysis result reflects the behavioral pattern of the component in the application call link; The behavior feature analysis result is used as feature data of the behavior feature dimension.

4. The method for identifying non-domestic components of an application system according to claim 1, characterized in that: The preset multiple feature dimensions include a code structure feature dimension, and feature analysis of the component is performed based on the code structure feature dimension, including: Perform code structure feature analysis on the code data corresponding to the component to obtain a code structure feature analysis result; The code structure feature analysis result is used as feature data of the code structure feature dimension.

5. The method for identifying non-domestic components of an application system according to claim 1, characterized in that: The preset multiple feature dimensions include a compatibility feature dimension, and feature analysis of the component is performed based on the compatibility feature dimension, including: Performing a compatibility analysis on the component based on code data corresponding to the component to obtain a compatibility analysis result corresponding to the component, wherein the compatibility analysis result reflects the compatibility of the component with a domestic chip or a domestic operating system; The compatibility analysis result is used as feature data of the compatibility feature dimension.

6. The method for identifying non-domestic components of an application system according to claim 1, characterized in that: The determining whether the component is a non-local component based on a preset feature rule library and a feature data set corresponding to the component includes: Obtaining, from the feature rule library, feature rules corresponding to each feature dimension; For each feature dimension of the feature data in the feature data set corresponding to the component, determine whether the feature data matches the feature rule corresponding to the feature dimension, and use the determination result as the feature matching result corresponding to the feature dimension; If the feature matching results corresponding to each of the feature dimensions indicate that the feature data of the feature dimension matches the feature rule corresponding to the feature dimension, then the component is determined to be a domestically produced component.

7. The method for identifying non-domestic components of an application system according to claim 6, characterized in that: Also includes: If there is a feature matching result corresponding to at least one feature dimension, and the feature data representing the feature dimension does not match the feature rule corresponding to the feature dimension, then the component is determined to be a non-domestic component.

8. A device for identifying non-domestic components of an application system, characterized in that: include: A first determining unit, configured to determine application monitoring data corresponding to a business processing flow of an application system; The application monitoring data is data collected by various probes preset in the application system; A call analysis unit, configured to perform component call analysis on the application monitoring data to obtain an application call link corresponding to the business processing flow; the application call link includes each component called by the application system and the call relationship between each component; A second determining unit is configured to determine behavior data corresponding to each of the components based on the application monitoring data and the application call link; A data acquisition unit, configured to acquire, for each component, component metadata and code data corresponding to the component, and combine the behavior data, component metadata and code data corresponding to the component into an original data set of the component; a feature analysis unit configured to perform feature analysis on each component based on an original data set of the component from a plurality of preset feature dimensions to obtain a feature data set corresponding to the component, the feature data set including feature data of each of the feature dimensions; The third determining unit is used to determine, for each of the components, whether the component is a non-domestic component based on a preset feature rule library and a feature data set corresponding to the component.

9. A storage medium, characterized in that: The storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the method for identifying non-domestic components of an application system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the method for identifying non-domestic components of an application system as described in any one of claims 1 to 7.

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