Adapting method, apparatus and computer readable storage medium

Abstract

The application provides an adaptation method and device and a computer readable storage medium, relates to the technical field of application software, and can provide functional support for automatic code replacement execution and scheme between source adaptation content and target adaptation content. The method comprises the following steps: when an adaptation application request is submitted, target parameters are configured, including an adaptation environment, basic data, a code library address and a function list; in the case of completed configuration, the adaptation application request is submitted to an automatic adaptation service through a form; the code library address information is transmitted to a machine learning service through the automatic adaptation service, and machine learning training is performed through the machine learning service; the function set in the code file information and adaptation requirements are used for rule matching on an adaptation rule library; in the case of successful matching, a code replacement operation is performed on user code; and based on the file name and file position information of the replaced user code, a code submission request is triggered. The application is applied to automatic code replacement execution.

Description

TECHNICAL FIELD

[0001] The present application relates to the application software technical field, and particularly relates to an adaptation method and device and a computer readable storage medium. BACKGROUND

[0002] At present, if the performance of the application system migrated to the target bottle body needs to be optimized, the migration predictability and migration workload of the application system under the target platform can be predicted according to the technology stack corresponding to the application system to be migrated, so as to obtain the application system migration prediction result; and the migration scheme of the application system and the required running environment of the application system are determined according to the application system migration prediction result; after the application system is migrated to the running environment created in the target platform, the performance of the migrated application system can be tested according to the performance index; and the performance of the application system migrated to the target platform is optimized according to the performance test result.

[0003] Although the prior art can meet the adaptation of the application system to the hardware and software information of the target platform, and the performance test and performance optimization of the required running environment of the system, but there is no effective learning and inheritance method for the adaptation service capability, and the adaptation service capability cannot be effectively improved through intelligent machine learning and diversified services. SUMMARY

[0004] The present application provides an adaptation method, device and computer readable storage medium, which can provide functional support for automatic code replacement execution and scheme between source adaptation content and target adaptation content through automatic adaptation capability. In order to achieve the above purpose, the present application adopts the following technical solutions:

[0005] In the first aspect, the present application provides an adaptation method, which comprises: when a user submits an adaptation application request, configuring target parameters, the target parameters comprising: adaptation environment, basic data, code library address and function list; in the case of completing the configuration, submitting the adaptation application request to the automatic adaptation service through the form; delivering the code library address information to the machine learning service through the automatic adaptation service, and performing machine learning training through the machine learning service; performing rule matching on the adaptation rule library based on the function set in the code file information and the adaptation demand; in the case of successful matching, performing code replacement operation on the user code; triggering the code submission request based on the file name and file location information of the replaced user code.

[0006] Based on the technical solution, the adaptation method provided by the embodiment of the application realizes intelligent adaptation service by performing "adaptation application, machine learning training, rule matching, code replacement, and code submission". Since the process of machine learning training is set, the adaptation code segment can be extracted and analyzed according to the adaptation requirement through the process, so as to complete the matching of the rule. After the rule matching succeeds, the code is replaced and submitted, and is saved to the user code library, thereby realizing more diversified automatic adaptation application functions, saving time cost, reducing human resources, effectively improving the efficiency of adaptation work, and ensuring the overall stability of the adaptation work. Since the machine learning training can be continuously trained and learned, more complex and variable services can be adapted.

[0007] In a first possible implementation manner of the first aspect, the adaptation application request further includes: adaptation rule standard formulation, framework knowledge base, and database knowledge base.

[0008] In a second possible implementation manner of the first aspect, the adaptation rule standard formulation is based on information of a development framework used in a traditional environment. The development framework is classified according to writing feature information and function feature information of the development framework, and a framework knowledge base is established to be used for identification requirements of user code framework information and configuration information during intelligent adaptation.

[0009] In a third possible implementation manner of the first aspect, the framework knowledge base is based on database information and version information used in a traditional environment and a signal creation environment. The database information of the traditional environment and the database information of the signal creation environment are structured in a method of providing information, and a database knowledge base is established to be used for code analysis requirements of a user in a database adaptation business scenario during intelligent adaptation.

[0010] In a fourth possible implementation manner of the first aspect, the database knowledge base is created by an automatic adaptation service based on application data in a case where the adaptation application request is submitted to the automatic adaptation service through a form.

[0011] In a fifth possible implementation manner of the first aspect, the machine learning training is performed through a machine learning service, including: pulling code file information based on code library address information through the machine learning service, and performing full-scan on the code file information.

[0012] In a sixth possible implementation manner of the first aspect, the machine learning training further includes: framework analysis, configuration analysis, code analysis, and code extraction, and the to-be-adapted code segment is analyzed according to syntax feature information of a development framework.

[0013] In a seventh possible implementation manner of the first aspect, the rule matching on the adaptation rule library based on the function set in the code file information and the adaptation requirement comprises: in a case where the code extraction by the machine learning service is completed, the rule matching on the adaptation rule library based on the function set in the extracted code file information and the adaptation requirement.

[0014] In an eighth possible implementation manner of the first aspect, the code replacement operation on the user code comprises: performing the code replacement operation on the user code based on the adaptation rule information and the code position information returned by the machine learning service, and performing type differentiation according to the adaptation rule information.

[0015] In a ninth possible implementation manner of the first aspect, the code replacement operation further comprises: a configuration replacement operation, a manual adaptation operation and a rule sedimentation operation; the configuration replacement operation is to obtain configuration information of an adaptation environment and perform replacement on source configuration information in a case where the configuration information position is determined according to the configuration replacement operation, and write the replaced configuration information back to a code configuration file; the manual adaptation operation is to perform the code replacement operation according to an adapted code segment in a case where the adaptation personnel adapt the code according to the adaptation requirement after the rule matching fails by the manual adaptation operation; and the rule sedimentation operation is to extract a general adaptation rule and output the general adaptation rule to the adaptation rule library.

[0016] In a tenth possible implementation manner of the first aspect, the code submission request is triggered based on the file name and the file position information of the replaced user code, comprising: triggering the code submission request based on the file name and the file position information, and submitting the changes to the code base service through a target request; and adding a code base submission point to submit the user code changes to the user code base.

[0017] In a second aspect, the application provides an adaptation device, comprising: a configuration unit, a submission unit, a processing unit, a matching unit and an execution unit; the configuration unit is configured to configure target parameters when a user submits an adaptation application request, the target parameters comprising: an adaptation environment, basic data, a code base address and a function list; the submission unit is configured to submit the adaptation application request to an automated adaptation service through a form in a case where the configuration is completed; the processing unit is configured to deliver the code base address information to a machine learning service through the automated adaptation service, and perform machine learning training through the machine learning service; the matching unit is configured to perform rule matching on an adaptation rule library based on a function set in code file information and an adaptation requirement; the execution unit is configured to perform a code replacement operation on user code in a case where the matching is successful; and a code submission request is triggered based on the file name and the file position information of the replaced user code.

[0018] In a first possible implementation manner of the second aspect, the adaptation application request further comprises: adaptation rule standardization, framework knowledge base and database knowledge base.

[0019] In a second possible implementation manner of the second aspect, the adaptation rule standardization is based on information of a development framework used by a traditional environment, and the information of the development framework is classified by writing feature information and function feature information of the development framework, and a framework knowledge base is established to meet the identification requirement of user code framework information and configuration information during intelligent adaptation.

[0020] In a third possible implementation manner of the second aspect, the framework knowledge base is based on database information and version information used by the traditional environment and the XG environment, and the database information of the traditional environment and the database information of the XG environment are structured to provide a device structure, and a database knowledge base is established to meet the code analysis requirement of the user in the database adaptation business scenario during intelligent adaptation.

[0021] In a fourth possible implementation manner of the second aspect, the database knowledge base is created by the automatic adaptation service based on the application data when the adaptation application request is submitted to the automatic adaptation service through a form.

[0022] In a fifth possible implementation manner of the second aspect, the processing unit is specifically configured to pull code file information based on code library address information through a machine learning service, and perform full-scan on the code file information.

[0023] In a sixth possible implementation manner of the second aspect, the machine learning training further comprises: framework analysis, configuration analysis, code analysis and code extraction, and the to-be-adapted code segment is analyzed according to syntax feature information of a development framework.

[0024] In a seventh possible implementation manner of the second aspect, the matching unit is specifically configured to perform rule matching on the adaptation rule library based on a function set in the extracted code file information and adaptation requirements when the code extraction through the machine learning service is completed.

[0025] In an eighth possible implementation manner of the second aspect, the execution unit is specifically configured to perform a code replacement operation on the user code based on adaptation rule information and code location information returned by the machine learning service, and perform type differentiation according to the adaptation rule information.

[0026] In a ninth possible implementation manner of the second aspect, the code replacement operation further includes: a configuration replacement operation, a manual adaptation operation, and a rule sedimentation operation; the configuration replacement operation is to obtain configuration information of the adaptation environment and perform replacement on the source configuration information in a case where the configuration information location is determined according to the configuration replacement operation, and write the replaced configuration information back to the code configuration file; the manual adaptation operation is to perform the code replacement operation according to the adapted code segment in a case where the adaptation personnel adapt the code according to the adaptation requirement and the rule matching fails; and the rule sedimentation operation is to extract a general adaptation rule and output the rule to an adaptation rule library.

[0027] In a tenth possible implementation manner of the second aspect, the execution unit is specifically configured to trigger a code submission request based on the file name and the file location information, and submit the change to the code library service through the target request; and a code library submission point is added, and the user code change is submitted to the user code library.

[0028] In a third aspect, the present application provides an adaptation device, which includes a processor and a communication interface; the communication interface is coupled with the processor, and the processor is configured to run a computer program or instruction to implement the adaptation method as described in the first aspect and any possible implementation manner of the first aspect.

[0029] In a fourth aspect, the present application provides a computer readable storage medium, which stores an instruction, and when the instruction is run on a terminal, the terminal executes the adaptation method as described in the first aspect and any possible implementation manner of the first aspect.

[0030] In a fifth aspect, the present application provides a computer program product including an instruction, and when the computer program product is run on an adaptation device, the adaptation device executes the adaptation method as described in the first aspect and any possible implementation manner of the first aspect.

[0031] In a sixth aspect, the present application provides a chip, which includes a processor and a communication interface; the communication interface is coupled with the processor, and the processor is configured to run a computer program or instruction to implement the adaptation method as described in the first aspect and any possible implementation manner of the first aspect.

[0032] Specifically, the chip provided in the present application further includes a memory for storing the computer program or instruction. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 A flowchart of an adaptation method provided in the present application;

[0034] Figure 2A language recognition and architecture recognition flowchart provided for an embodiment of the present application;

[0035] Figure 3 A language recognition and architecture recognition flowchart provided for an embodiment of the present application;

[0036] Figure 4 A rule matching flowchart provided for an embodiment of the present application;

[0037] Figure 5 A code replacement and code submission flowchart provided for an embodiment of the present application;

[0038] Figure 6 A jar framework analysis flowchart provided for an embodiment of the present application;

[0039] Figure 7 A JAVA framework internal structure knowledge example diagram provided for an embodiment of the present application;

[0040] Figure 8 A JAVA framework (commonsCSV) mapping example diagram provided for an embodiment of the present application;

[0041] Figure 9 A database query language differentiation knowledge graph schematic flowchart provided for an embodiment of the present application;

[0042] Figure 10 A code replacement knowledge graph flowchart provided for an embodiment of the present application;

[0043] Figure 11 A structure schematic diagram of an adaptation device provided for an embodiment of the present application;

[0044] Figure 12 A structure schematic diagram of an adaptation device provided for an embodiment of the present application;

[0045] Figure 13 A chip structure schematic diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0046] The adaptation method and device provided for an embodiment of the present application are described in detail below in combination with the accompanying drawings.

[0047] The term "and / or" in this document is merely a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone.

[0048] The terms "first" and "second" and the like in the description of the present application and in the accompanying drawings are used to distinguish different objects, or to distinguish different treatments of the same object, rather than to describe a specific order of the objects.

[0049] In addition, the terms "comprising" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[0050] It should be noted that in the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design presented as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Rather, the use of "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0051] In the description of the present application, unless otherwise specified, "a plurality of" means two or more.

[0052] It should be noted that in the embodiments of the present application, words with the same letter combination but different cases are the same word.

[0053] In the prior art, a migration adaptation method based on a domestic signal creation software and hardware platform is provided, which comprises: predicting the migratability and migration workload of an application system under a target platform according to the technical stack corresponding to the application system to be migrated, to obtain an application system migration prediction result; determining an application system migration scheme according to the application system migration prediction result; the application system migration scheme comprises software information and hardware information for adapting the application system to the target platform; in the target platform, installing the software corresponding to the software information and the hardware corresponding to the external hardware information to obtain the required running environment of the application system; migrating the application system to the running environment created in the target platform, and performing performance testing on the migrated application system according to the performance index; and performing performance optimization on the application system migrated to the target platform according to the performance testing result. Thus, the overall performance of the migrated application system can be improved.

[0054] However, the above method can meet the adaptation of the software and hardware information of the application system to the target platform, and the performance testing and performance optimization of the required running environment of the system, but there is no effective learning and inheritance method for the adaptation service capability, and the adaptation service capability cannot be effectively improved through intelligent machine learning and diversified services, so there is still a certain deficiency in this respect.

[0055] In order to solve the problems and deficiencies in the prior art, the application provides an adaptation method based on a domestic signal creation platform. The adaptation method is an application software intelligent control method. The purpose is to provide a domestic adaptation migration service with machine learning capability and automatic adaptation capability for enterprises through intelligent adaptation service. The machine learning capability is to identify the code location content and syntax information of Hibernate, SpringData and Mybits framework under JAVA language through AI machine learning, extract the adaptation code segment according to the adaptation requirement, and perform rule matching after semantic analysis of the extracted code segment. The automatic adaptation capability is to provide function support for the execution and scheme of automatic code replacement between source adaptation content and target adaptation content. The application function of the automatic adaptation capability includes "adaptation application, adaptation environment management, basic data management, data migration adaptation, adaptation rule library management, language recognition, architecture analysis, code segment extraction, rule reading, file scanning, rule matching, code replacement, code submission and achievement output".

[0056] The adaptation method provided by the application is an adaptation method from non-domestic to domestic. The method is an intelligent adaptation service technology. The innovation lies in the intelligent machine learning capability and more diversified automatic adaptation application function. The method focuses on solving the problem that enterprises cannot form machine learning capability of data and technology accumulation in domestic migration adaptation work, and provides more accurate and matched intelligent adaptation migration service for diversified software and hardware platforms in response to rapid changes and complex migration adaptation work, effectively improves the efficiency of adaptation work, and reduces the investment of personnel and time cost.

[0057] The adaptation method of the application is applied to an adaptation system, which can be applied in the automatic code replacement execution process.

[0058] As shown in Figure 1 The flowchart of the adaptation method provided by the embodiment of the application, the method comprises the following steps:

[0059] S101, when a user submits an adaptation application request, configure target parameters.

[0060] In the embodiment of the application, the target parameters include adaptation environment, basic data, code library address and function list.

[0061] S102, in the case of completed configuration, submit the adaptation application request to the automatic adaptation service through a form.

[0062] In the embodiments of the application, the user adaptation application is submitted to configure the adaptation environment, basic data, code library address and function list, so as to ensure the automatic adaptation service. The automatic adaptation service creates adaptation data based on the application data, deposits rules into the adaptation rule library table, improves the efficiency of adaptation work, and ensures the overall stability of the adaptation work.

[0063] In S103, the automatic adaptation service delivers the code library address information to the machine learning service, and performs machine learning training through the machine learning service.

[0064] In the embodiments of the application, through machine learning training, Hibernate, mybatis and SpringData framework under JAVA language can be learned, so as to improve the machine learning capability.

[0065] In S104, the function set in the code file information and the adaptation requirement are matched with the adaptation rule library.

[0066] In S105, the code replacement operation is performed on the user code when the matching is successful.

[0067] In the embodiments of the application, through the automatic adaptation capability, the function support is provided for the automatic code replacement execution and scheme between the source adaptation content and the target adaptation content, and the intelligent adaptation service method of "intelligent and diversified" is realized.

[0068] In S106, the code submission request is triggered based on the file name and file position information of the replaced user code.

[0069] Optionally, in the embodiments of the application, the adaptation application request further includes the adaptation rule standard formulation, the framework knowledge base and the database knowledge base.

[0070] Optionally, in the embodiments of the application, the adaptation rule standard formulation is based on the information of the development framework used in the traditional environment. The writing feature information and function feature information of the development framework are classified, and the framework knowledge base is established to meet the identification requirement of the user code framework information and configuration information during intelligent adaptation.

[0071] Optionally, in the embodiments of the application, the framework knowledge base is based on the database information and version information used in the traditional environment and the XG environment. The database information of the traditional environment and the database information of the XG environment are structured in the method of providing method, and the database knowledge base is established to meet the code analysis requirement of the user in the database adaptation business scenario during intelligent adaptation.

[0072] Optionally, in the embodiments of the present application, when the database knowledge base is submitted to the automatic adaptation service through the form of the adaptation application request, the automatic adaptation service creates adaptation data based on the application data.

[0073] In the embodiments of the present application, the code change can be submitted to the code base service through the HTTP request, the new code base submission point is added, and the code change is submitted to the user code base, thereby meeting the demand of the enterprise for the intelligent adaptation service.

[0074] The embodiments of the present application provide an adaptation method, which performs intelligent adaptation service by adapting the adaptation application, machine learning training, rule matching, code replacement, and code submission. Since the process of machine learning training is set, the adaptation code segment can be extracted and analyzed according to the adaptation demand through the process, so as to complete the matching of the rule, replace and submit the code after the rule matching is successful, and save it to the user code base, thereby realizing more diversified automatic adaptation application function, saving the time cost, reducing the human resources, effectively improving the efficiency of the adaptation work, and ensuring the overall stability of the adaptation work. Since the machine learning training can be continuously trained and learned, it can adapt to more complex and variable services.

[0075] Optionally, in the embodiments of the present application, the “machine learning training through the machine learning service” in the above S103 can be implemented through the following S103a.

[0076] S103a, pull the code file information based on the code base address information through the machine learning service, and perform full-scan on the code file information.

[0077] Optionally, in the embodiments of the present application, the machine learning training further includes framework analysis, configuration analysis, code analysis, and code extraction, and the to-be-adapted code segment is analyzed according to the syntax feature information of the development framework.

[0078] Optionally, in the embodiments of the present application, the above S104 can be implemented through the following S104a.

[0079] S104a, in the case where the code extraction through the machine learning service is completed, the rule matching is performed on the adaptation rule library based on the function set in the extracted code file information and the adaptation demand.

[0080] Optionally, in the embodiments of the present application, the “code replacement operation is performed on the user code” in the above S105 can be implemented through the following S105a.

[0081] S105a, based on the adaptation rule information and the code position information returned by the machine learning service, the code replacement operation is performed on the user code, and the type is distinguished according to the adaptation rule information.

[0082] Optionally, in the embodiments of the present application, the code replacement operation further includes: a configuration replacement operation, a manual adaptation operation and a rule sedimentation operation; the configuration replacement operation is to obtain the configuration information of the adaptation environment and perform replacement on the source configuration information in the case of determining the configuration information position according to the configuration replacement operation, and write the replaced configuration information back to the code configuration file; the manual adaptation operation is to perform the code replacement operation according to the adapted code segment after the code is adapted by the adaptation personnel according to the adaptation requirement in the case of rule matching failure through the manual adaptation operation; the rule sedimentation operation is to extract the general adaptation rule and output to the adaptation rule library.

[0083] Optionally, in the embodiments of the present application, S106 can be implemented through S106a1 and S106a2 as follows.

[0084] S106a1, based on the file name and the file position information, triggering a code submission request, and submitting changes to the code library service through the target request.

[0085] S106a2, adding a code library submission point, and submitting user code changes to the user code library.

[0086] Optionally, in the embodiments of the present application, S101 to S106 can be further explained and described through S1 to S5 as follows.

[0087] It should be noted that the adaptation method provided by the embodiments of the present application is based on the domestic signal creation platform, and the method can be an intelligent adaptation method for application software based on the domestic signal creation platform, and the method includes the following steps:

[0088] S1, adaptation application;

[0089] When the user submits the adaptation application, the adaptation environment, the basic data, the code library address and the function list configuration are configured, and after the configuration is completed, the request is submitted to the automatic adaptation service through the form submission, and the automatic adaptation service creates adaptation data based on the application data.

[0090] Optionally, in the embodiments of the present application, the adaptation application of S1 further includes adaptation rule standard formulation, framework knowledge base and database knowledge base.

[0091] It should be noted that the adaptation rule standard is based on the development framework information commonly used in the traditional environment, and the function characteristics are classified, and the framework knowledge base is established for intelligent adaptation, and the recognition demand of the user code framework information and the configuration information; the framework knowledge base is based on the commonly used database and version of the traditional environment and the XG environment, and the database of the traditional environment and the database of the XG environment are structured, and the database knowledge base is established for the code analysis demand of the user in the database adaptation business scenario; the database knowledge base refers to the adaptation environment, the basic data, the code library address and the function list configuration when the user submits the adaptation application, and after the configuration is completed, the request is submitted to the automatic adaptation service through the form submission; the automatic adaptation service creates adaptation data based on the application data;

[0092] In the above manner, the efficiency of the adaptation work can be effectively improved, and the personnel and time cost investment is reduced.

[0093] As shown in Figure 2 , it is an adaptation application process flowchart language recognition and architecture recognition flowchart provided by the embodiment of the present application, which can be applied in the process of adaptation business process.

[0094] S2, machine learning training;

[0095] The automatic adaptation service delivers the code library address information to the machine learning service, and the machine learning service pulls the code file information based on the code library address, and performs full-scan on the code file information;

[0096] In the above manner, the execution and scheme of the automatic code replacement between the source adaptation content and the target adaptation content can be provided with functional support.

[0097] As shown in Figure 3 , it is a language recognition and architecture recognition flowchart provided by the embodiment of the present application, which can be applied in the process of adaptation business process.

[0098] S3, rule matching;

[0099] According to the function set in the code segment information and the adaptation demand, the adaptation rule library is searched, if the matching is successful, the corresponding code position information and function set replacement rule are returned to the automatic adaptation service; if the matching is unsuccessful, the function matching is degraded, the function information is matched with the adaptation rule one by one according to the use, if the adaptation rule in the function set cannot be matched, the whole code is output to the automatic adaptation service, and the manual adaptation task is initiated by the automatic adaptation service.

[0100] In the above manner, the code segment position information and the adaptation rule set can be returned to the automatic adaptation service in the case of full matching success.

[0101] As Figure 4 shown, the rule matching flowchart provided by the embodiment of the present application can be applied to the process of code analysis and rule matching in the adaptation business process.

[0102] S4, code replacement;

[0103] After the rule matching succeeds, the code replacement operation is performed on the user code based on the adaptation rule information and the code position information returned by the machine learning service, the configuration information of the adaptation environment is obtained according to the returned adaptation rule type and the configuration information position analyzed according to the configuration, and the source configuration information is replaced and written back to the code configuration file.

[0104] In the above manner, the intelligent adaptation service of "intelligence and diversification" can be realized.

[0105] S5, code submission;

[0106] The code submission request is triggered according to the file name and the file position information, the changes are submitted to the code library service through the HTTP request, and the code library submission point is added.

[0107] In the above manner, the code changes can be submitted to the user code library, thereby meeting the needs of enterprises for intelligent adaptation services.

[0108] As Figure 5 shown, the code replacement and code submission flowchart provided by the embodiment of the present application can be applied to the process of adapting the business.

[0109] Optionally, in the embodiment of the present application, on the basis of S1 to S5, the adaptation method provided by the embodiment of the present application can also be applied to the scene of intelligent adaptation of code segments, which includes the following steps in the scene:

[0110] S11, jar framework analysis;

[0111] Scan the code to identify all database framework class code segments.

[0112] Optionally, in the embodiment of the present application, for jar framework analysis, for the JAVA language framework, the original data is a compiled and packaged file, and the content needs to be parsed to be effectively utilized. The Clazz method is identified through the class path level to identify the class structure of the classes code, and the main architecture information such as the class name, function, constructor, parameter and static variable of the JAVA framework is automatically extracted to form a code framework knowledge base to support the business application,

[0113] As Figure 6 shown, the jar framework analysis flowchart provided by the embodiment of the present application is shown.

[0114] The framework analysis process includes:

[0115] Reading the analysis jar package, reading the analysis to obtain the compiled file (its compiled file format, specifically the compiled file.class, Figure 6 The class name, function, etc. are identified, and the class name, function, etc. are content structured to obtain the code function association graph.

[0116] It should be noted that the architecture analysis and recognition effect of the JAVA function package is as follows:

[0117] Framework 1: {function class 1, function class 2, function class 3, function class...}, {function function 1, function function 2,...};

[0118] Framework 2: {function class 1, function class 2, function class 3, function class...}, {function function 1, function function 2,...};

[0119] Framework 3: {function class 1, function class 2, function class 3, function class...}, {function function 1, function function 2,...}.

[0120] S12, data structuring;

[0121] Identify the SQL call code segment and the framework type (SQL, HQL, JDBCTemplate, JPA, ORM, Criteria, etc.).

[0122] Optionally, in the embodiments of the present application, the framework structure (classes, functions, etc.) identified from S11 is scattered and has no associated information.

[0123] As Figure 7 shown, the JAVA framework internal structure knowledge provided by the embodiments of the present application is illustrated, which can parse the JAVA framework into different function classes, such as function class 1, function class 2, function class 3, etc. by the method of hasClass, and for each function class, the function class can be parsed into different function functions by the method of hasfunc; for example, function class 2 is parsed into function function 1, function function 2, function function 3, function function 4 and function function 5.

[0124] It needs to record which function belongs to which class, the relationship between the subclass and the parent class, etc. to save the JAVA framework in the form of identifiable, traceable, describable and retrievable data. The scheme is to structure the data in the form of knowledge graph, and the graph database is used to save these associated information, to form a framework theme rule knowledge base as basic data, and to provide all business support related thereto.

[0125] It should be noted that the mapping of the JAVA framework obtains more specific data, such as Figure 8 As shown in the JAVA framework (commons CSV) mapping example provided by the embodiment of the application, the JAVA framework can be parsed into different functional classes, such as the CVSFormat class, the CSVParser class, the CSVPrinter class, and the CSVPecord class, by the method of hasClass. For each functional class, the functional class can be parsed into different functional functions by the method of hasfunc. For example, the CSVParser class is parsed into the parse function, the add Record Value function, the Interat or function, the close function, and the getRecords function.

[0126] It can be used to identify keywords of code blocks for rapid retrieval (for example, the identification of the following function code block can be completed within 1 second), and the specific JAVA framework used is obtained.

[0127] S13, code location identification;

[0128] According to each type of framework, key information is identified.

[0129] Optionally, in the embodiment of the application, the above S13 can include the following steps:

[0130] S13a, input code block (text format);

[0131] S13b, NLP word segmentation (identify keywords);

[0132] Optionally, in the embodiment of the application, when S13b is executed, only the class name (capitalized at the beginning) of each line needs to be obtained, so that the data amount can be reduced, and the results Connection, Statement, String, ResultSet, and the like are obtained.

[0133] S13c, obtain the code segment that needs to be adjusted, and execute the code segment through the jshell of java11, so that the parameters of the spliced string, the dialect, and the driver parameters, and the like are obtained.

[0134] That is:

[0135] Database connection class: com.mysql.jdbc.Driver;

[0136] url: jdbc:mysql: / / / cgb2109?characterEncoding=utf8;

[0137] Username: root;

[0138] Password: root;

[0139] sql: select*from user where name='jack'and pwd='123;

[0140] It should be noted that for SQL, further NLP word segmentation or SQL parsing methods are needed to extract the syntactic and semantic information.

[0141] S14, Replacement of framework element information;

[0142] Key information (driving function, dialect, URL, username, password), where string concatenation involves executing code in Java and retrieving the variables that are ultimately sent to the database connection function, is the key information; for file reading, the file is retrieved and identified in the project.

[0143] Optionally, in this embodiment of the application, the replacement of framework element information includes: constructing a database query language differential knowledge graph.

[0144] like Figure 9 The diagram shown is a schematic flowchart of the database query language differential knowledge graph provided in an embodiment of this application, wherein mysql (or MySQL) is used. Figure 9 The user database can connect to the `com.mysql.jdbc.Driver` class via a database connection class, while the DM database connects to the `dm.jdbc.driver.DmDriver` class via the same database connection class. The `com.mysql.jdbc.Driver` and `dm.jdbc.driver.DmDriver` classes are mutually mapped. The user database framework can be parsed into different functions using the `hasfunc` method, such as `Gro UP_CONCAT`, `DATE_FORMAT`, `from_unixtime`, and `subst ring_index`. Similarly, the DM database framework can be parsed into different functions using the `hasfunc` method, such as `wm_concat`, `Datepart`, `round`, and `substr`. The `Gro UP_CONCAT` function maps to the `wm_concat` function, the `DATE_FORMAT` function maps to the `Datepart` function, the `from_unixtime` function maps to the `round` function, and the `subst ring_index` function maps to the `substr` function.

[0145] The advantages of data graphing are clear management and quick retrieval. In addition, knowledge-based data is more useful for AI tasks as training corpus.

[0146] In addition, the "dialect", "driver" and SQL corresponding to SQL can be replaced in subsequent steps.

[0147] Exemplarily, the above method is further illustrated by the following scenarios.

[0148] Scenario 1: Business requirements

[0149] In the case of business requirements, the personnel set under a certain department can be returned in the form of a string.

[0150] Original mysql query method, using group_concat() function

[0151] select

[0152] d.dept_name, GROUP_CONCAT(u.name)

[0153] From

[0154] user u

[0155] LEFT JOIN dept d on

[0156] dept_id = d.id

[0157] where

[0158] U.dept_id = #{dept_id} and u.status = 0.

[0159] Scenario 2: Knowledge graph solution - code replacement

[0160] In the case of knowledge graph solution - code replacement, it can be implemented based on code replacement knowledge graph, as shown in Figure 10 The code replacement knowledge graph process provided by the embodiments of the present application is disclosed in Figure 9 In the case where the classes and functions in the user database are mapped to the classes and functions in the dream database, the replacement classes or replacement functions of MySQL and dream database can be obtained according to the mapping relationship, and the classes can be replaced, or the functions can be replaced, for example, the com.mysql.jdbc.Driver class and the dm.jdbc.driver.DmDriver class are replaced.

[0161] The specific performance is as follows:

[0162] S14a, SQL statement word segmentation

[0163] Optionally, in the embodiments of the present application, the above S14a can be obtained by using syntax analysis, thereby obtaining: d.dept_name, GROUP_CONCAT(u.name).

[0164] S14b, atlas retrieval keyword

[0165] Optionally, in the embodiments of the present application, through knowledge retrieval (d.dept_name, GROUP_CONCAT), d.dept_name is ignored if no result is obtained, and after the entity is found by GROUP_CONCAT, the replacement function of MySQL and Dameng database is obtained through mapping, so that code replacement can be performed in the next step.

[0166] S14c, replace SQL syntax

[0167] Optionally, in the embodiments of the present application, the Dameng database syntax is implemented using the wm_concat() function, and the group_concat() syntax is not used

[0168] select

[0169] d.dept_name,wm_concat(u.name)

[0170] From

[0171] user u

[0172] LEFT JOIN dept d on

[0173] dept_id=d.id

[0174] where

[0175] U.dept_id=#{dept_id}and u.status=0

[0176] It should be noted that the requirement is directly replaced by the associated results of knowledge retrieval.

[0177] S15, AI model training;

[0178] Key information replacement, including Structured Query Language (SQL) query language differentiation replacement.

[0179] It should be noted that the above S15 can be accomplished using graph database mapping relationships: that is, identifying the code location content and syntax information of frameworks such as Hibenate, SpringData, and Mybits under the JAVA language, and implementing a fully automated solution.

[0180] Optionally, in this embodiment of the application, for AI model training, corpus can be automatically labeled, and an intelligent labeling system can be constructed through a knowledge graph; by using word2Vec and node2Vec algorithms, the knowledge structure embedding of each JAVA framework can be vectorized to obtain several automatically labeled AI training datasets, which are used for algorithm model training. Thus, training data can be continuously added by updating and traversing the knowledge graph, and the AI ​​classification model required by the business can be trained according to business needs. The target code segment is adapted and identified by a dual approach of graph neural network algorithm and knowledge graph retrieval.

[0181] This application embodiment can divide the adapter device into functional modules or functional units according to the above method examples. For example, each function can be divided into a separate functional module or functional unit, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or in software functional modules or functional units. The module or unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0182] like Figure 11 The diagram shown is a structural schematic of an adapter device provided in an embodiment of this application. The device includes: a configuration unit 21, a submission unit 22, a processing unit 23, a matching unit 24, and an execution unit 25.

[0183] The system includes: a configuration unit 21, which configures target parameters when a user submits an adaptation request, including the adaptation environment, basic data, code repository address, and function list; a submission unit 22, which submits the adaptation request to the automated adaptation service via a form after configuration; a processing unit 23, which transmits the code repository address information to the machine learning service through the automated adaptation service and performs machine learning training through the machine learning service; a matching unit 24, which performs rule matching on the adaptation rule base based on the function set in the code file information and the adaptation requirements; and an execution unit 25, which performs a code replacement operation on the user's code when the match is successful and triggers a code submission request based on the file name and file location information of the replaced user code.

[0184] In one possible implementation, the adaptation request also includes: adaptation rule standardization, framework knowledge base, and database knowledge base.

[0185] In a possible implementation, the adaptation rule standard formulation is based on information of a development framework used in a traditional environment, the information of the development framework is classified by writing feature information and function feature information, and a framework knowledge base is established to meet the identification requirements of user code framework information and configuration information during intelligent adaptation.

[0186] In a possible implementation, the framework knowledge base is based on database information and version information used in a traditional environment and a China-specific environment, the database information of the traditional environment and the database information of the China-specific environment are structured, and a database knowledge base is established to meet the code analysis requirements of a user in a database adaptation business scenario during intelligent adaptation.

[0187] In a possible implementation, the database knowledge base is created by the automated adaptation service based on application data when the adaptation application request is submitted to the automated adaptation service through a form.

[0188] In a possible implementation, the processing unit 23 is specifically configured to pull code file information based on code library address information through a machine learning service, and perform full-scan on the code file information.

[0189] In a possible implementation, the machine learning training further includes framework analysis, configuration analysis, code analysis, and code extraction, and the to-be-adapted code segment is analyzed according to syntax feature information of a development framework.

[0190] In a possible implementation, the matching unit 24 is specifically configured to perform rule matching on the adaptation rule library based on a function set in the extracted code file information and adaptation requirements when the code extraction through the machine learning service is completed.

[0191] In a possible implementation, the execution unit 25 is specifically configured to perform a code replacement operation on user code based on adaptation rule information and code location information returned by the machine learning service, and perform type differentiation according to the adaptation rule information.

[0192] In a possible implementation, the code replacement operation further includes a configuration replacement operation, a manual adaptation operation, and a rule sedimentation operation; the configuration replacement operation is to obtain configuration information of an adaptation environment and perform replacement on source configuration information when the configuration information location is determined according to the configuration replacement operation, and write the replaced configuration information back to a code configuration file; the manual adaptation operation is to perform a code replacement operation according to an adapted code segment when the code adaptation is performed by an adaptation personnel according to adaptation requirements in a case where rule matching fails through the manual adaptation operation; and the rule sedimentation operation is to extract a general adaptation rule and output the rule to an adaptation rule library.

[0193] In a possible implementation, the execution unit 25 is specifically configured to trigger a code submission request based on the file name and the file location information, and submit the change to the code repository service through a target request; and add a code repository submission point to submit the user code change to the user code repository.

[0194] When implemented by hardware, the configuration unit 21, the submission unit 22, the processing unit 23, the matching unit 24 and the execution unit 25 in the embodiments of the present application can be integrated on a processor. The specific implementation manner is shown in Figure 12 .

[0195] Figure 12 Another possible structural schematic diagram of the adaptation device involved in the above embodiments is shown. The adaptation device includes a processor 302 and a communication interface 303. The processor 302 is configured to control and manage the actions of the adaptation device, for example, to execute the steps performed by the configuration unit 21, the submission unit 22, the processing unit 23, the matching unit 24 and the execution unit 25, and / or to execute other processes of the technology described herein. The communication interface 303 is configured to support the communication of the adaptation device with other network entities. The adaptation device can also include a memory 301 and a bus 304, and the memory 301 is configured to store the program code and data of the adaptation device.

[0196] The memory 301 can be a memory in the adaptation device, which can include a volatile memory such as a random access memory, and can also include a non-volatile memory such as a read-only memory, a flash memory, a hard disk or a solid state disk, and can also include a combination of the above kinds of memories.

[0197] The processor 302 described above can be various exemplary logical blocks, modules and circuits described in combination with the disclosure of the present application. The processor can be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure of the present application. The processor can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0198] The bus 304 can be an extended industry standard architecture (EISA) bus or the like. The bus 304 can be divided into an address bus, a data bus, a control bus and the like. For the sake of representation, Figure 12Only one bus or bus type is used in some of the drawings, but it is understood that the connection to the other buses or bus types may be used as well.

[0199] Figure 13 is a structural schematic diagram of the chip 170 provided in an embodiment of the present application. The chip 170 includes one or more than two (including two) processors 1710 and a communication interface 1730.

[0200] Optionally, the chip 170 further includes a memory 1740, which can include a read-only memory and a random access memory, and provides operation instructions and data to the processor 1710. A part of the memory 1740 can further include a non-volatile random access memory (NVRAM).

[0201] In some embodiments, the memory 1740 stores the following elements, execution modules or data structures, or a subset thereof, or an extended set thereof.

[0202] In an embodiment of the present application, corresponding operations are performed by invoking operation instructions stored in the memory 1740 (which can be stored in an operating system).

[0203] The processor 1710 can implement or execute the various exemplary logical blocks, units and circuits described in connection with the disclosure of the present application. The processor can be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute the various exemplary logical blocks, units and circuits described in connection with the disclosure of the present application. The processor can also be a combination of components that implement computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0204] The memory 1740 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid state disk; the memory can also include a combination of the above kinds of memories.

[0205] The bus 1720 can be an extended industry standard architecture (EISA) bus or the like. The bus 1720 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 13 Only one bus or bus type is used in some of the drawings, but it is understood that the connection to the other buses or bus types may be used as well.

[0206] Those skilled in the art can clearly understand the above-mentioned technical solutions from the description of the above-embodiment, for the convenience and brevity of description, only the above-mentioned division of functional modules is exemplified, in actual application, the above-mentioned functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiment, and will not be repeated here.

[0207] The embodiment of the present application provides a computer program product containing instructions, when the computer program product runs on a computer, so that the computer executes the adaptation method in the method embodiment.

[0208] The embodiment of the present application also provides a computer readable storage medium, and the computer readable storage medium stores instructions, when the instructions run on a computer, so that the computer executes the adaptation method in the method process shown in the method embodiment.

[0209] The computer readable storage medium may, for example, be but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to the processor, so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). In the embodiment of the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus.

[0210] Embodiments of the present application provide a computer program product comprising instructions which, when executed on a computer, cause the computer to carry out the adaptation method as described above.

[0211] Since the adaptation apparatus, the computer readable storage medium, the computer program product in the embodiments of the present application can be applied to the above-mentioned method, the technical effects that can be obtained thereby can be referred to the above-mentioned method embodiments, and the embodiments of the present application will not be repeated here.

[0212] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented by other manners. For example, the above-mentioned device embodiments are only illustrative, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0213] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. can be located in one place or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0214] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.

[0215] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any change or replacement within the technical scope disclosed in the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An adaptation method, characterized by, The method comprises: When a user submits an adaptation application request, configure target parameters, including: adaptation environment, basic data, code library address, and function list; In the case of completed configuration, submit the adaptation application request to the automated adaptation service through a form; Deliver the code library address information to the machine learning service through the automated adaptation service, and perform machine learning training through the machine learning service; The machine learning training through the machine learning service comprises: pulling code file information based on the code library address information through the machine learning service, and performing full-scan on the code file information; The machine learning training further comprises: framework analysis, configuration analysis, code analysis, and code extraction, and analyzing the code segment to be adapted according to the syntax feature information of the development framework; In the case of completing code extraction through the machine learning service, perform rule matching on the adaptation rule library based on the function set in the extracted code file information and adaptation requirements; if the matching is successful, return the corresponding code location information and function set replacement rule to the automated adaptation service; if the matching is unsuccessful, perform function matching in a degraded manner, and match the adaptation rules one by one according to the used function information; if there is an adaptation rule that cannot be matched in the function set, output the entire code segment to the automated adaptation service, and initiate a manual adaptation task by the automated adaptation service; the manual adaptation task is performed by an adaptation personnel according to the adaptation requirements, and the code replacement operation is performed according to the adapted code segment; In the case of all matching being successful, perform code replacement operation on the user code based on the adaptation rule information and code location information returned by the machine learning service, and perform type differentiation according to the adaptation rule information; The code replacement operation further comprises: configuration replacement operation and rule sedimentation operation; the configuration replacement operation is to obtain the configuration information of the adaptation environment and perform replacement on the source configuration information in the case of determining the configuration information position according to the configuration replacement operation, and write the replaced configuration information back to the code configuration file; the rule sedimentation operation is to extract the general adaptation rule and output it to the adaptation rule library. Trigger a code submission request based on the file name and file location information of the replaced user code.

2. The method of claim 1, wherein, The adaptation application request further comprises: adaptation rule standard formulation, framework knowledge base, and database knowledge base.

3. The method of claim 2, wherein, The adaptation rule standard formulation is based on the information of the development framework used in the traditional environment, classifies the writing feature information and function feature information of the development framework, and establishes the framework knowledge base for the identification requirements of the user code framework information and configuration information in intelligent adaptation.

4. The method of claim 2, wherein The framework knowledge base is based on database information and version information used in traditional environments and Xingcheng environments, and the database information of the traditional environment and the database information of the Xingcheng environment are structured to provide a method structure, and the database knowledge base is established for code analysis requirements of users in database adaptation business scenarios during intelligent adaptation.

5. The method of claim 2, wherein, In the case that the database knowledge base is submitted to the automatic adaptation service through the form, the automatic adaptation service creates adaptation data based on application data.

6. The method of claim 1, wherein, The file name and file location information of the replaced user code trigger a code submission request, including: Based on the file name and file location information, trigger a code submission request, and submit changes to the code library service through a target request; Add a code library submission point to submit the user code changes to the user code library.

7. An adapting device, characterized in that The device comprises a configuration unit, a submission unit, a processing unit, a matching unit and an execution unit. The configuration unit is configured to configure target parameters when a user submits an adaptation application request, the target parameters including: adaptation environment, basic data, code library address and function list; The submission unit is configured to submit the adaptation application request to the automatic adaptation service through a form after configuration is completed; The processing unit is configured to deliver code library address information to a machine learning service through the automatic adaptation service, and perform machine learning training through the machine learning service; The processing unit is specifically configured to pull code file information based on the code library address information through the machine learning service, and perform full-scan on the code file information; The machine learning training further includes framework analysis, configuration analysis, code analysis and code extraction, and analyzes the code segment to be adapted according to the syntax feature information of the development framework; The matching unit is configured to perform rule matching on the adaptation rule base based on the function set in the extracted code file information and adaptation requirements when code extraction through the machine learning service is completed; if the matching is successful, the corresponding code location information and function set replacement rule are returned to the automatic adaptation service; if the matching is unsuccessful, function matching is performed in a degraded manner, and the adaptation rules are matched one by one according to the used function information; if there is an adaptation rule that cannot be matched in the function set, the whole code segment is output to the automatic adaptation service, and a manual adaptation task is initiated by the automatic adaptation service; the manual adaptation task is performed by an adaptation personnel according to the code adaptation requirement, and the code replacement operation is performed according to the adapted code segment; The execution unit is configured to, in the case of successful matching, perform a code replacement operation on the user code based on the adaptation rule information and the code location information returned by the machine learning service, and perform type differentiation according to the adaptation rule information; the code replacement operation further includes a configuration replacement operation and a rule sedimentation operation; the configuration replacement operation is to obtain configuration information of the adaptation environment and perform replacement on source configuration information, and write the replaced configuration information back to a code configuration file, in the case of determining a configuration information location according to the configuration replacement operation; the rule sedimentation operation is to extract a general adaptation rule and output it to the adaptation rule library. The execution unit is further configured to trigger a code submission request based on the file name and the file location information of the replaced user code.

8. The apparatus of claim 7, wherein, The adaptation application request further includes adaptation rule standard formulation, a framework knowledge base, and a database knowledge base.

9. The apparatus of claim 8, wherein, The adaptation rule standard formulation is based on information of a development framework used in a traditional environment, classifies the writing characteristics information and the function characteristics information of the development framework, and establishes the framework knowledge base to meet the identification needs of user code framework information and configuration information during intelligent adaptation.

10. The apparatus of claim 8, wherein The framework knowledge base is based on database information and version information used in a traditional environment and a credit environment, provides a device structure for the database information of the traditional environment and the database information of the credit environment, establishes the database knowledge base to meet the code analysis needs of a user in a database adaptation business scenario during intelligent adaptation.

11. The apparatus of claim 8, wherein, The database knowledge base is created by the automatic adaptation service based on application data in the case of submitting the adaptation application request to the automatic adaptation service through the form.

12. The apparatus of claim 7, wherein The execution unit is specifically configured to trigger a code submission request based on the file name and the file location information, submit changes to a code library service through a target request, and add a code library submission point to submit the user code changes to a user code library.

13. An adapting device, characterized in that including: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is configured to run computer programs or instructions to implement the adaptation method in any one of claims 1 to 6.

14. A computer-readable storage medium having stored therein instructions, the computer-readable storage medium comprising: When a computer executes the instructions, the computer executes the adaptation method in any one of claims 1 to 6.

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