CN115099229A

CN115099229A - Plan model generation method, plan model generation device, electronic device and storage medium

Info

Publication number: CN115099229A
Application number: CN202210739758.1A
Authority: CN
Inventors: 陈明洋
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2022-06-28
Filing date: 2022-06-28
Publication date: 2022-09-23

Abstract

The application relates to the field of system development, and provides a plan model generation method, a plan model generation device, electronic equipment and a computer-readable storage medium, wherein the method comprises the following steps: acquiring a historical service flow chart; extracting elements from the historical business flow chart to obtain a plurality of plan composition elements; arranging the plurality of plan composition elements based on a preset field-driven design rule to obtain a plan event map; carrying out first analysis processing on a plan event map to obtain a plurality of domain vocabularies; boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information; and carrying out modeling processing according to preset design rules of the damming ring, the field vocabularies and the limit context information to obtain a plan model. Through the technical scheme, the problem of repeated construction can be solved.

Description

Plan model generation method and device, electronic device and storage medium

Technical Field

The embodiment of the application relates to but is not limited to the field of system development, and in particular relates to a planning model generation method, a planning model generation device, an electronic device and a computer-readable storage medium.

Background

The planning is an essential link before various kinds of work and actions are carried out, a responsible person needs to plan a series of targets which need to be achieved by aiming at the current business, and meanwhile, related index data and achievement conditions are monitored in the plan execution process, so that risk early warning and plan adjustment can be made at any time. In actual business scenes, such as the development of additional member targets in an additional member core domain and the training plan of a training system, the underlying architectures of the systems are basically consistent, and the problem of repeated construction exists.

Disclosure of Invention

The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

In order to solve the problems mentioned in the background art, embodiments of the present application provide a plan model generation method, an apparatus, an electronic device, and a computer-readable storage medium, which can solve the problem of reconstruction.

In a first aspect, an embodiment of the present application provides a planning model generation method, where the method includes:

acquiring a historical service flow chart;

extracting elements from the historical business flow chart to obtain a plurality of plan composition elements;

arranging the plurality of plan composition elements based on a preset field-driven design rule to obtain a plan event map;

performing first analysis processing on the plan event map to obtain a plurality of domain vocabularies;

boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information;

and carrying out modeling processing according to a preset damming ring design rule, the field vocabulary and the limit context information to obtain a plan model.

According to the plan model generation method provided by the embodiment of the application, at least the following beneficial effects are achieved: firstly, acquiring a historical service flow chart; then, extracting elements from the historical business flow chart to obtain a plurality of plan composition elements; then, a plan event map can be obtained by arranging the plurality of plan composition elements based on a preset field-driven design rule; then, carrying out first analysis processing on the plan event map to obtain a plurality of domain vocabularies; boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information; finally, modeling is carried out according to preset design rules of the damming ring, field vocabularies and limit context information to obtain a plan model; by the technical scheme, different fields are fused, and the problem of cross-channel system multiplexing can be solved.

According to some embodiments of the present application, the extracting elements from the historical business process graph to obtain a plurality of planning component elements includes:

splitting the historical service flow chart to obtain a service composition text;

and performing second analysis processing on the service composition text to obtain a plurality of plan composition elements.

According to some embodiments of the present application, the organizing the plurality of plan components based on a preset domain-driven design rule to obtain a plan event map includes:

dividing the plurality of plan composition elements to obtain event information and command information;

arranging the event information and the command information according to a preset business process rule to obtain the planned event map.

According to some embodiments of the present application, the first analyzing the planned event map to obtain a plurality of domain vocabularies comprises:

performing vocabulary extraction processing on the event information and the command information in the plan event map to obtain a plurality of keywords;

and matching the plurality of keywords to obtain a plurality of domain vocabularies.

According to some embodiments of the present application, the boundary dividing processing on the plurality of domain vocabularies to obtain the bound context information includes:

creating a plurality of domain boundaries according to a preset business function rule;

performing semantic analysis on each field vocabulary to obtain corresponding semantic information;

and dividing each field vocabulary to the corresponding field boundary according to the semantic information to obtain the limit context information.

According to some embodiments of the present application, the modeling according to the preset damming ring design rule, the domain vocabulary and the bound context information to obtain a planning model comprises:

identifying the domain vocabulary and the bound context information to obtain aggregation information and an aggregation root;

creating an initial function module based on the aggregation information and the aggregation root;

dividing the initial function module according to the design rule of the damming ring to obtain a plan module, an implementation module, an inspection module and a correction module;

and mapping the domain vocabulary and the code objects in the code model to obtain the plan model based on the plan module, the implementation module, the inspection module and the correction module.

According to some embodiments of the present application, the creating an initial function module based on the aggregation information and the aggregation root includes:

performing third analysis processing on the aggregation information to obtain service associated information;

and according to the service association information, associating the domain vocabulary and the aggregation root to obtain the initial functional module.

In a second aspect, an embodiment of the present application further provides a planning model generation apparatus, where the apparatus includes:

the first processing module is used for acquiring a historical service flow chart;

the second processing module is used for extracting elements from the historical business flow chart to obtain a plurality of plan composition elements;

the third processing module is used for sorting the plurality of plan composition elements based on a preset field-driven design rule to obtain a plan event map;

the fourth processing module is used for carrying out first analysis processing on the plan event map to obtain a plurality of domain vocabularies;

the fifth processing module is used for carrying out boundary division processing on the plurality of domain vocabularies to obtain boundary context information;

and the sixth processing module is used for carrying out modeling processing according to a preset damming ring design rule, the field vocabulary and the limit context information to obtain a plan model.

In a third aspect, an embodiment of the present application further provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of generating a planning model according to the first aspect when executing the computer program.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium storing computer-executable instructions for performing the plan model generation method according to the first aspect.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

The accompanying drawings are included to provide a further understanding of the claimed subject matter and are incorporated in and constitute a part of this specification, illustrate embodiments of the subject matter and together with the description serve to explain the principles of the subject matter and not to limit the subject matter.

FIG. 1 is a flow chart of a planning model generation method provided by an embodiment of the present application;

FIG. 2 is a flowchart illustrating the generation of plan components in a plan model generation method according to an embodiment of the present application;

FIG. 3 is a flowchart of generating a planning event map in a planning model generation method according to an embodiment of the present application;

FIG. 4 is a flowchart illustrating domain vocabulary generation in a planning model generation method according to an embodiment of the present application;

FIG. 5 is a flow chart of generating bounding context information in a method for generating a planning model according to an embodiment of the present application;

FIG. 6 is a flowchart illustrating a method for generating a planning model according to an embodiment of the present application;

FIG. 7 is a flowchart illustrating the generation of an initial function module in a planning model generation method according to an embodiment of the present application;

FIG. 8 is a schematic diagram of a planning model generation apparatus provided in an embodiment of the present application;

fig. 9 is a schematic diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

It should be noted that although functional block divisions are performed in apparatus diagrams and logical orders are illustrated in flowcharts, in some cases, steps shown or described may be performed in orders different from block divisions in apparatus diagrams or flowcharts. The terms first, second and the like in the description and in the claims, as well as in the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

It is to be noted that, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.

The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.

AI is a new technical science to study and develop theories, methods, techniques and application systems for simulating, extending and expanding human intelligence; artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produces a new intelligent machine that can react in a manner similar to human intelligence, and research in this field includes robotics, language recognition, image recognition, natural language processing, and expert systems, among others. The artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is also a theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use the knowledge to obtain the best results.

The artificial intelligence base technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.

The artificial intelligence is AI, which is a theory, method, technique and application system that simulates, extends and expands human intelligence, senses the environment, acquires knowledge and uses the knowledge to obtain the best result by using a digital computer or a machine controlled by a digital computer.

The server related to the artificial intelligence technology can be an independent server, and can also be a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, Network service, cloud communication, middleware service, domain name service, security service, Content Delivery Network (CDN), big data and artificial intelligence platform and the like.

The application provides a plan model generation method, a plan model generation device, electronic equipment and a computer readable storage medium, and a historical business flow chart is obtained firstly; then, extracting elements from the historical business flow chart to obtain a plurality of plan composition elements; then, a plan event map can be obtained by arranging the plurality of plan composition elements based on a preset field-driven design rule; then, carrying out first analysis processing on the plan event map to obtain a plurality of domain vocabularies; boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information; finally, modeling is carried out according to preset damming ring design rules, domain vocabularies and limit context information to obtain a plan model; by the technical scheme, different fields are fused, and the problem of cross-channel system multiplexing can be solved.

The embodiment of the application provides a planning model generation method, and relates to the technical field of system development. The plan model generation method provided by the embodiment of the application can be applied to a terminal, a server side and software running in the terminal or the server side. In some embodiments, the terminal may be a smartphone, tablet, laptop, desktop computer, or the like; the server side can be configured into an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and cloud servers for providing basic cloud computing services such as cloud service, a cloud database, cloud computing, cloud functions, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN (content delivery network) and big data and artificial intelligence platforms; the software may be an application or the like that implements a planning model generation method, but is not limited to the above form.

The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In each embodiment of the present application, when data related to the user identity or characteristic, such as user information, user behavior data, user history data, and user location information, is processed, permission or consent of the user is obtained, and the data collection, use, and processing comply with relevant laws and regulations and standards of relevant countries and regions. In addition, when the embodiment of the present application needs to acquire sensitive personal information of a user, individual permission or individual consent of the user is obtained through a pop-up window or a jump to a confirmation page, and after the individual permission or individual consent of the user is definitely obtained, necessary user-related data for enabling the embodiment of the present application to operate normally is acquired.

The embodiments of the present application will be further explained with reference to the drawings.

As shown in fig. 1, fig. 1 is a flowchart of a planning model generation method provided in an embodiment of the present application, and the planning model generation method includes, but is not limited to, steps S100 to S600.

Step S100, acquiring a historical service flow chart;

step S200, extracting elements from the historical business process diagram to obtain a plurality of plan composition elements;

step S300, a plurality of plan composition elements are arranged based on a preset field-driven design rule to obtain a plan event map;

step S400, carrying out first analysis processing on a plan event map to obtain a plurality of domain vocabularies;

step S500, boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information;

and step S600, carrying out modeling processing according to preset design rules of the damming ring, the field vocabulary and the limit context information to obtain a plan model.

It should be noted that, a historical service flow chart is obtained first; then, extracting elements from the historical business flow chart to obtain a plurality of plan composition elements; then, a plan event map can be obtained by arranging a plurality of plan composition elements based on a preset field-driven design rule; then, carrying out first analysis processing on the plan event map to obtain a plurality of domain vocabularies; boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information; finally, modeling is carried out according to preset design rules of the damming ring, field vocabularies and limit context information to obtain a plan model; by the technical scheme, different fields are fused, and the problem of cross-channel system multiplexing can be solved.

It should be noted that the historical business flow chart is a previous business flow chart, and includes each planning component element constituting the historical business flow chart; because the historical business flow chart contains the planning component elements related in the past activity process, the planning component elements can be obtained by extracting the elements from the historical business flow chart, and the precondition preparation is made for the subsequent planning model creation. Illustratively, the plan component elements include creating a whole monthly added member amount draft, editing a whole monthly added member amount draft, issuing a whole monthly added member amount, creating a monthly incremental draft, creating a monthly added member amount draft, editing monthly added member amount, issuing monthly added member amount, automatically issuing monthly added member amount, and automatically issuing monthly added member amount.

Notably, the historical business process flow diagram is composed of a plurality of planning components; it is to be understood that elements of the historical business process flow diagram that appear may be identified as planning component elements.

Notably, Domain Drive Design (DDD) is a software development method that meets complex requirements by linking implementations to a model that continues to evolve. The premise of the field drive design is as follows: putting the main focus of the project on the core domain and the domain logic; placing a complex design on a bounded domain model; initiating a creative inter-collaboration technology and domain expert to iteratively perfect a conceptual mode to solve problems in a specific field; the domain-driven design is a concept that a system design is driven by a domain model, and the system design is not driven by storing a data dictionary. The domain model is an abstraction of the business model, and the DDD is a way to translate the business model into a system architecture design.

It is noted that DDD is a set of systems that deal with complex business systems with emphasis on the domain as the core. Or a domain logic design method for controlling design quality of a service system. The event storm is a good practice mode for exploring the business field, and the event storm produces the domain analysis in the unified language and strategic design of the corresponding DDD, and reaches the division limit context.

It is worth noting that the 'activity center' is built by using a domain-driven design methodology, the business domain is subdivided according to a certain rule, the problem to be solved is limited in a specific boundary, the 'activity' subdomain is analyzed in a fine granularity mode, the sharing capability in the 'activity' business process is identified and is precipitated into the general capability, the service reuse is realized through the precipitated general capability, and the purposes of cost reduction and efficiency improvement are achieved.

It should be noted that, the dacron is also called PDCA loop, P represents english word Plan, D represents english word Design, C represents english word Check, and a represents english word Act; through 'planning-designing-checking-acting', the result of the summarized checking is processed through continuous circulation, the successful experience is confirmed, and is standardized, or an operation instruction book is made, so that the operation instruction book can be conveniently followed in later work; the failed training is also summarized to avoid recurrence. For the problem not solved, it should be mentioned to be solved in the next PDCA cycle. PDCA is the first letter of the english words Plan, Do, Check and Act, PDCA cycles are the scientific procedures that proceed in this order and cycle through more than one. The operation of the overall quality management activities, without the need to manage the rotation of the cycles, i.e. improving and solving quality problems, and every job that is up to the advanced level, uses the scientific procedures of the PDCA cycle. No matter how high the product quality is, or how much the defective product is reduced, the goal is to be addressed, to what extent the quality is improved, how much the defective product rate is reduced? There is a plan; this plan includes not only the goal, but also the measures that need to be taken to achieve this goal; after the plan is made, checking according to the plan to see whether the expected effect is achieved or not; finding out problems and reasons through inspection; finally, the treatment is carried out, and the experience and the teaching are formulated into a standard and formed system.

In some embodiments, as shown in fig. 2, the step S200 may include, but is not limited to, steps S210 to S220.

Step S210, splitting the historical service flow chart to obtain a service composition text;

and step S220, carrying out second analysis processing on the service composition text to obtain a plurality of plan composition elements.

It should be noted that, in order to generate the plan composition elements, a historical business flowchart is split to obtain a business composition text; and then, performing second analysis processing on the service composition text to obtain a plurality of plan composition elements.

It can be understood that the historical business process diagram is split to obtain a business composition text forming the historical business process diagram, and then the business composition text is subjected to second analysis to obtain a plurality of plan composition elements; illustratively, a historical business process diagram is split to obtain a business composition text, the business composition text comprises judgment conditions of certain conditions and conventional names required by certain process diagrams, the obtained business composition text is subjected to second analysis processing, and then the nouns are removed, so that a plurality of plan composition elements can be obtained. Wherein, the process of performing the second analysis processing on the service composition text can utilize a keyword recognition technology; certain words can be identified by using keyword identification technology, and if the words are listed as non-essential words, the words are removed.

In some embodiments, as shown in fig. 3, the step S300 may include, but is not limited to, the steps S310 to S320.

Step S310, dividing a plurality of plan composition elements to obtain event information and command information;

step S320, sorting the event information and the command information according to a preset business process rule to obtain a planned event map.

It should be noted that, in the process of generating the planned event map, the event information and the command information can be obtained by dividing the plurality of planned component elements; and then sequencing the corresponding event information and the command information according to a preset business process rule to obtain a planned event map.

It is noted that event information and command information can be obtained by dividing a plurality of plan components; event information and command information are two important elements that make up a planned event map; illustratively, the event information in the monthly increment event map can comprise that an overall monthly increment draft is created, edited, issued, created, edited and automatically issued; the command information in the monthly increment event map can comprise the steps of creating a draft of the overall monthly increment amount, editing the draft of the overall monthly increment amount, issuing the draft of the overall monthly increment amount, creating the draft of the monthly increment amount, editing the monthly increment amount, issuing the monthly increment amount and automatically issuing the monthly increment amount.

It can be understood that the event information and the command information can be sequenced according to the business process rule to form a corresponding planned event map; illustratively, for the monthly increment event map, the overall monthly increment draft is created and is connected with the editing of the overall monthly increment draft, the overall monthly increment draft is edited and is connected with the issuing of the overall monthly increment, the overall monthly increment draft is issued and is connected with the creation of the monthly increment draft, the monthly increment draft is created and is connected with the editing of the monthly increment, and the monthly increment is edited and is respectively connected with the issuing of the monthly increment and the automatic issuing of the monthly increment.

In some embodiments, as shown in fig. 4, the step S400 may include, but is not limited to, the steps S410 to S420.

Step S410, carrying out vocabulary extraction processing on event information and command information in a plan event map to obtain a plurality of keywords;

step S420, performing matching processing on the plurality of keywords to obtain a plurality of domain vocabularies.

It should be noted that, in order to obtain the domain vocabulary, a plurality of keywords may be obtained by performing vocabulary extraction processing on the event information and the command information in the planned event map; and matching the keywords to obtain a plurality of domain vocabularies.

It can be understood that a plurality of keywords can be obtained by performing vocabulary extraction processing on the event information and the command information in the plan event map; illustratively, the event information in the monthly increment event map comprises that a draft of the overall monthly increment amount is created, the draft of the overall monthly increment amount is edited, the overall monthly increment amount is issued, the draft of the monthly increment amount is created, the monthly increment amount is edited, the monthly increment amount is issued and the monthly increment amount is automatically issued; the command information in the monthly increment event map comprises a draft for creating the whole monthly increment, a draft for editing the whole monthly increment, a draft for issuing the whole monthly increment, a draft for creating the monthly increment, a draft for editing the monthly increment, a monthly increment and an automatic monthly increment, wherein the vocabulary in the field of the target of the increment can be obtained by extracting the vocabulary of the plan components and matching the increment; and performing vocabulary extraction processing on the written and written increased member quantity actual value to obtain a keyword of the increased member quantity actual value, and performing matching processing on the increased member quantity actual value to obtain a domain vocabulary of the increased member quantity actual value.

In some embodiments, as shown in fig. 5, the step S500 may include, but is not limited to, the steps S510 to S530.

Step S510, a plurality of domain boundaries are established according to a preset business function rule;

step S520, semantic analysis is carried out on the vocabularies in each field to obtain corresponding semantic information;

step S530, dividing each domain vocabulary to the corresponding domain boundary according to the semantic information to obtain the bound context information.

It is to be noted that, a plurality of domain boundaries are created according to a preset business function rule; then, semantic analysis processing is carried out on the vocabularies in each field to obtain corresponding semantic information; and finally, dividing each field vocabulary into corresponding field boundaries according to the semantic information to obtain the boundary context information.

It is noted that a plurality of domain boundaries can be created according to the business function rules, and for example, for the planning model, a plan management boundary, an administrator plan management boundary, an interview management boundary, a participant management boundary, etc. can be created according to the business function rules. Then, semantic analysis processing is carried out on the vocabularies in each field to obtain corresponding semantic information; finally, dividing each field vocabulary according to semantic information corresponding to each field vocabulary, and dividing each field vocabulary into corresponding field boundaries to obtain boundary context information; illustratively, for the interview management clearance context information, the domain vocabulary such as personal input client list, locked client and interview two-dimensional code can be included.

In some embodiments, as shown in fig. 6, the step S600 may include, but is not limited to, steps S610 to S640.

Step S610, identifying and processing the domain vocabulary and the limit context information to obtain aggregation information and an aggregation root;

step S620, an initial function module is established based on the aggregation information and the aggregation root;

step S630, the initial function module is divided according to the design rule of the damming ring to obtain a plan module, an implementation module, a check module and a correction module;

and step S640, mapping the domain vocabulary and the code objects in the code model to obtain a plan model based on the plan module, the implementation module, the inspection module and the correction module.

It should be noted that, the aggregation information and the aggregation root can be obtained by performing recognition processing on the domain vocabulary and the bound context information; then, an initial function module can be created and obtained based on the aggregation information and the aggregation root; then, the initial function module is divided according to the design rule of the damming ring, so that a planning module, an implementation module, a checking module and a correction module can be obtained; and finally, mapping the domain vocabulary and the code objects in the code model based on the planning module, the implementation module, the inspection module and the correction module to obtain the planning model.

Illustratively, the plan issuing rules, the plan and the entity relationship all belong to a plan aggregation, and the target, the leaf target, the atom index, the derivative index and the like belong to a target aggregation.

It should be noted that, the aggregation belongs to a domain layer in a DDD layered architecture, the domain layer includes multiple aggregations, which together implement a core service logic, and entities in the aggregations implement individual service capabilities with a congestion model and high aggregation of service logics; business logic crossing multiple entities is realized by domain service, and business logic crossing multiple aggregations is realized by application service; the aggregation is formed by combining entity and value objects which are closely related to services and logics, the aggregation is a basic unit for modifying and persisting data, and one aggregation corresponds to the persistence of one data; the aggregations are related and quoted through the aggregation roots, if other aggregated entities need to be accessed, the aggregation roots are accessed, and then the entities in the aggregations are navigated; i.e., external objects cannot directly access entities within the aggregation. Polymeric radical: comparing the aggregation with an organization, wherein the aggregation root is a responsible person of the organization, is also called a root entity and is not only an entity but also a manager of the entity; responsibility: as an entity, the system has own service attribute, service behavior and service logic; as a manager of aggregation, the manager is responsible for coordinating the entity and the value object to cooperatively complete a common service logic according to a fixed service rule in the aggregation; between polymerizations: the method is characterized in that an external interface person is aggregated, an external request and a task are received in a manner of aggregating root IDs, and business cooperation among aggregations in a context is realized; the aggregations are related and quoted through the aggregation roots, if other aggregated entities need to be accessed, the aggregation roots are accessed, and then the entities in the aggregations are navigated; i.e., external objects cannot directly access entities within the aggregation.

Notably, the polymerization is characterized by: the high-cohesion low-coupling is the boundary of the bottommost layer in the domain model and can be used as the minimum unit for splitting the micro-service, but the single micro-service is not recommended to correspond to, unless the scene has extreme requirements on performance, one micro-service can comprise a plurality of aggregations, the boundary between the aggregations is the most logic natural boundary, and the logic boundary can be used as the basis for splitting and combining the micro-service when the micro-service is split. Characteristics of polymeric root: the aggregation root is an entity, has a unique identifier and an independent life cycle, only one aggregation root is provided for one aggregation, the aggregation root organizes and coordinates the entity and the value object in a reference-dependent mode in the aggregation, and the aggregation root are coordinated through the unique id.

It should be noted that, the dacron is also called PDCA loop, P represents english word Plan, D represents english word Design, C represents english word Check, and a represents english word Act; through 'planning-designing-checking-acting', the result of the summarized checking is processed through continuous circulation, the successful experience is confirmed, and is standardized, or an operation instruction book is made, so that the result is convenient to follow in the later working; the failed lessons were also summarized to avoid recurrence. For the problem not solved, it should be mentioned to be solved in the next PDCA cycle. PDCA is the first letter of the english words Plan, Do, Check and Act, PDCA cycles is a scientific procedure that performs quality management in this order and that cycles through more than one cycle. The operation of the overall quality management activities, without the need to manage the rotation of the cycles, i.e. improving and solving quality problems, and every job that is up to the advanced level, uses the scientific procedures of the PDCA cycle. No matter how high the quality of the product is, or how low the defective products are, the goal is to be put forward, i.e. how much the quality is raised and how much the defective rate is lowered? There is a plan; this plan includes not only the goal, but also the measures that need to be taken to achieve this goal; after the plan is made, checking according to the plan to see whether the expected effect is achieved or not and whether the expected target is achieved or not; finding out problems and reasons through inspection; finally, processing is carried out, and experience and teaching are formulated into a standard and formed system.

It is worth noting that the domain modeling usually adopts event storm, adopts methods such as use case analysis, scene analysis and user journey analysis, lists all possible business behaviors and events through the brain storm, then finds out domain objects generating the behaviors, combs the relationship between the domain objects, finds out a aggregation root, finds out an entity and a value object closely related to the aggregation root business, and then combines the aggregation root, the entity and the value object to construct an aggregation.

In some embodiments, as shown in fig. 7, the step S620 may include, but is not limited to, steps S621 to S622.

Step S621, performing third analysis processing on the aggregation information to obtain service associated information;

step S622, performing association processing on the domain vocabulary and the aggregation root according to the service association information to obtain an initial function module.

It should be noted that, first, the third analysis processing is performed on the aggregation information to obtain the service related information; and then, according to the business association information, associating the domain vocabulary and the aggregation root to obtain an initial functional module.

It is worth noting that the service associated information can be obtained by performing third analysis processing on the aggregation information, wherein the service associated information is used for representing the connection relation among all the domain vocabularies, a selected domain vocabulary is used as an aggregation root, and then different domain vocabularies can be connected to obtain corresponding initial function modules.

In addition, as shown in fig. 8, an embodiment of the present application further provides a plan model generation apparatus 10, including:

a first processing module 100, configured to obtain a historical business flowchart;

a second processing module 200, configured to perform element extraction on the historical business flowchart to obtain a plurality of plan constituent elements;

a third processing module 300, configured to sort the multiple plan components based on a preset domain-driven design rule to obtain a plan event map;

a fourth processing module 400, configured to perform a first analysis on the planned event map to obtain a plurality of domain vocabularies;

a fifth processing module 500, configured to perform boundary division processing on multiple domain vocabularies to obtain bound context information;

a sixth processing module 600, configured to perform modeling processing according to a preset damming ring design rule, the domain vocabulary, and the bound context information to obtain a plan model.

In one embodiment, a historical business flow chart is obtained first; then, extracting elements from the historical business flow chart to obtain a plurality of plan composition elements; then, a plan event map can be obtained by arranging the plurality of plan composition elements based on a preset field-driven design rule; then, carrying out first analysis processing on the plan event map to obtain a plurality of domain vocabularies; boundary division processing is carried out on a plurality of domain vocabularies to obtain boundary context information; finally, modeling is carried out according to preset design rules of the damming ring, field vocabularies and limit context information to obtain a plan model; by the technical scheme, different fields are fused, and the problem of cross-channel system multiplexing can be solved.

The specific implementation of the plan model generation apparatus is substantially the same as the specific implementation of the plan model generation method, and is not described herein again.

In addition, as shown in fig. 9, an embodiment of the present application also provides an electronic device 700, including: memory 710, processor 720, and computer programs stored on memory 710 and executable on processor 720.

The processor 720 and the memory 710 may be connected by a bus or other means.

Non-transitory software programs and instructions necessary to implement the planning model generation method of the above-described embodiments are stored in the memory 710, and when executed by the processor 720, the planning model generation method of the above-described embodiments is performed, for example, the method steps S100 to S600 in fig. 1, the method steps S210 to S220 in fig. 2, the method steps S310 to S320 in fig. 3, the method steps S410 to S420 in fig. 4, the method steps S510 to S530 in fig. 5, the method steps S610 to S640 in fig. 6, and the method steps S621 to S622 in fig. 7 described above are performed.

The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

Furthermore, an embodiment of the present application further provides a computer-readable storage medium, which stores computer-executable instructions, which are executed by a processor 720 or a controller, for example, by a processor 720 in the above-mentioned device embodiment, and can make the above-mentioned processor 720 execute the planning model generation method in the above-mentioned embodiment, for example, execute the above-mentioned method steps S100 to S600 in fig. 1, method steps S210 to S220 in fig. 2, method steps S310 to S320 in fig. 3, method steps S410 to S420 in fig. 4, method steps S510 to S530 in fig. 5, method steps S610 to S640 in fig. 6, and method steps S621 to S622 in fig. 7.

The above embodiments may be combined, and the modules with the same name may be the same or different between different embodiments.

While certain embodiments of the present application have been described above, other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily have to be in the particular order shown or in sequential order to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on differences from other embodiments. In particular, for the apparatus, device, and computer-readable storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and in relation to the description, reference may be made to some portions of the description of the method embodiments.

The apparatus, the device, the computer-readable storage medium, and the method provided in the embodiments of the present application correspond to each other, and therefore, the apparatus, the device, and the non-volatile computer storage medium also have similar advantageous technical effects to those of the corresponding method.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain a corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be regarded as a hardware component and the means for performing the various functions included therein may also be regarded as structures within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in multiple software and/or hardware when implementing the embodiments of the present application.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The present specification has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or Flash memory (Flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information and/or data which can be accessed by a computing device. As defined herein, computer readable Media does not include Transitory computer readable Media such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

In the embodiments of the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, and indicates that three relationships may exist, for example, a and/or B, and may indicate that a exists alone, a and B exist simultaneously, and B exists alone. Wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c may represent: a, b, c, a and b, a and c, b and c or a and b and c, wherein a, b and c can be single or multiple.

Embodiments of the application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Embodiments of the application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method of generating a planning model, the method comprising:

acquiring a historical service flow chart;

2. The method of generating a planning model according to claim 1, wherein the extracting elements from the historical business process graph to obtain a plurality of planning components comprises:

and carrying out second analysis processing on the service composition text to obtain a plurality of plan composition elements.

3. The method for generating a planning model according to claim 1, wherein the organizing the plurality of planning component elements based on a preset domain-driven design rule to obtain a planning event map comprises:

and arranging the event information and the command information according to a preset business process rule to obtain the planned event map.

4. The method of generating a planning model according to claim 1, wherein the first analyzing the planning event map to obtain a plurality of domain vocabularies comprises:

5. The method of generating a planning model according to claim 1, wherein the boundary dividing the plurality of domain vocabularies to obtain boundary context information includes:

6. The method for generating a planning model according to claim 1, wherein the modeling according to the preset delming ring design rule, the domain vocabulary and the bound context information to obtain the planning model comprises:

dividing the initial function module according to the design rule of the damming ring to obtain a planning module, an implementation module, a checking module and a correction module;

7. The method according to claim 6, wherein the creating an initial function module based on the aggregation information and the aggregation root comprises:

8. A planning model generation apparatus, the apparatus comprising:

9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of generating a planning model according to any of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing computer-executable instructions for performing the method of generating a planning model of any of claims 1-7.