Service triggering system, method and equipment based on artificial intelligence

Abstract

The invention relates to the technical field of software development and maintenance, and provides a service triggering system, method and equipment based on artificial intelligence, and the system comprises an analysis module which is used for analyzing a design drawing in a software engineering process, and extracting design drawing elements; the similarity calculation module is used for performing similarity calculation on design drawing elements and development requirements and performing similarity calculation on the development requirements and codes; the incidence relation calculation module is used for calculating the incidence relation between the design drawing and the code according to the similarity between the design drawing element and the development demand and the similarity between the development demand and the code; the change influence analysis triggering module is used for sending corresponding change information to a change initiator for confirmation when the software is changed; and the fault positioning trigger module is used for sending corresponding fault information to a maintainer for troubleshooting when the software has a fault. According to the method, the incidence relation and the intelligent service triggering mechanism can be quickly established in the software engineering life cycle, the change influence analysis accuracy is improved, and fault corresponding positioning is accelerated.

Description

Technical Field

[0001] The present application relates to the field of software development and maintenance technology, and in particular to an artificial intelligence-based business triggering system, method and device. Background Art

[0002] In today's software industry, the complexity of software programs is increasing, especially for medium and large software and those that have been developed or operated for a long time. These software bring many challenges to maintenance and development iteration due to the complexity of their inherent functions and the continuous changes in the time dimension.

[0003] The traditional maintenance and development iteration process mainly relies on two methods: one is to record the functions and time changes of the software through a large amount of documents; the other is to hire fixed personnel to maintain these systems for a long time. In this model, it is necessary to rely on fixed manpower and detailed data documentation to ensure the smooth maintenance of the software and the development iteration of simple new functions.

[0004] However, this traditional approach has many drawbacks. In the process of medium and large software development, development and maintenance work is usually not completed by a single person. Although the development iteration standards may strive to be unified, in actual operation, the changed materials, code comment documents, etc. are often difficult to be perfect. In addition, the technical levels of developers vary. This leads to the situation that when facing the same requirement, different developers may step on the "pitfalls" of past codes due to their judgments based on their own experience. The "pitfalls" mentioned here are not simply code anomalies, but some conventions that exist in past programs. New developers may not understand these conventions, or even if they know them, they may not pay enough attention to them in the actual implementation process. When the changes are small and relatively simple, the problem is not obvious, but once the number of changes increases and becomes complicated, it is very easy to cause various accidents.

[0005] Moreover, human experience is limited after all. Even with a checklist to assist, it takes a lot of time to check these tedious items one by one. For those who are not familiar with the software, it is even more difficult to figure out the details of the entire software. This traditional maintenance and development iteration method that relies on manpower and documents can no longer meet the needs of efficient and accurate maintenance and iteration of modern medium and large complex software. A new technical solution is urgently needed to solve the problems existing in the existing technology. Summary of the invention

[0006] In view of this, in order to overcome the deficiencies of the prior art, the present application aims to provide a business triggering system, method and device based on artificial intelligence.

[0007] According to a first aspect of the present application, there is provided an artificial intelligence-based service triggering system, the system comprising a service triggering server, the service triggering server comprising: The parsing module is used to parse the design drawings in the software engineering process and extract the design drawing elements; A similarity calculation module is used to calculate the similarity between design elements and development requirements, and between development requirements and codes; The association relationship calculation module is used to calculate the association relationship between the design drawing and the code according to the similarity between the design drawing elements and the development requirements, and the development requirements and the code; The change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation when the software is changed; The fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting when a software fault occurs.

[0008] Optionally, in the artificial intelligence-based business triggering system of the present application, the parsing module identifies the design drawing through a graph parsing algorithm and extracts design drawing elements, wherein the design drawing elements include functional modules and their mutual associations, hierarchical relationships, and sequential relationships.

[0009] Optionally, in the artificial intelligence-based business trigger system of the present application, the similarity calculation module is used to calculate the similarity between the design drawing elements and the development requirements, and to calculate the similarity between the development requirements and the code by comparing the functional descriptions incorporated into the log of the development requirements and the code.

[0010] Optionally, in the artificial intelligence-based business triggering system of the present application, an association calculation module is used to dynamically update and display the association between the design drawing and the code according to the iteration and change status of the software engineering.

[0011] Optionally, in the artificial intelligence-based business trigger system of the present application, the change impact analysis trigger module is used to trigger the artificial intelligence component to search for the development requirement changes corresponding to the corresponding changes when the software or software code changes, and send the corresponding change information and change impact assessment report to the change initiator for confirmation.

[0012] Optionally, in the artificial intelligence-based business trigger system of the present application, the fault location trigger module is used to trigger the artificial intelligence component to search for the development requirement fault corresponding to the corresponding code when a software fault occurs, and send the corresponding fault information and troubleshooting suggestions to the maintenance locator for troubleshooting.

[0013] Optionally, in the artificial intelligence-based business triggering system of the present application, the artificial intelligence component can use a deep learning algorithm to learn and train software engineering data to improve the accuracy of analysis and prediction.

[0014] Optionally, the artificial intelligence-based service triggering system of the present application further includes: The authority management module is used to control the access and operation of the system; The data storage module is used to store design drawings, requirement documents, and code integration log data in the software engineering process.

[0015] According to a second aspect of the present application, a service triggering method based on artificial intelligence is provided, the method comprising: The parsing module is used to parse the design drawings in the software engineering process and extract the design drawing elements; Use the similarity calculation module to calculate the similarity between design elements and development requirements, and between development requirements and codes; The association relationship calculation module is used to calculate the association relationship between the design drawing and the code according to the similarity between the design drawing elements and the development requirements, and the development requirements and the code; When software is changed, the change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation; When a software failure occurs, the fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting.

[0016] According to a third aspect of the present application, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the second aspect of the present application is implemented.

[0017] The artificial intelligence-based service triggering method and system of the embodiment of the present application has the following beneficial technical effects in the software engineering life cycle, especially in the fields of change impact analysis and rapid fault location, by means of the application of artificial intelligence (AI) technology: 1. Quickly establish association relationships With the support of AI technology, it is possible to quickly establish various complex relationships between iterative requirements, design drawings, key nodes, and related personnel at various stages of software engineering, such as requirements analysis, design, development, testing, and operation and maintenance. The establishment of such relationships no longer relies on traditional manual combing and document recording, but uses AI algorithms to analyze and mine massive amounts of software engineering data, thereby efficiently identifying the inherent connections between different elements. For example, when requirements change, AI can quickly identify the scope of impact and related personnel of the change on various links such as design drawings, code implementation, and test cases, providing clear guidance for subsequent processing.

[0018] 2. Intelligent Service Triggering Mechanism Based on the quickly established association relationship, this application implements an intelligent business trigger mechanism. Once an action occurs in any associated link in the software engineering life cycle, such as a change in requirements, code submission, or a problem found in testing, the system will automatically generate a response event and trigger the corresponding intelligent business process. This mechanism greatly improves the response speed and processing efficiency of software engineering. For example, when a developer submits a code change, the AI ​​system will immediately analyze the impact of the change on other modules, automatically trigger related testing tasks, and notify affected developers and testers. At the same time, it will also evaluate the risk level of the change according to preset rules to provide a basis for subsequent decision-making. This intelligent triggering mechanism avoids the tediousness and inefficiency of manually notifying and manually starting related processes one by one in the traditional mode, ensuring close connection and efficient collaboration between various links in software engineering.

[0019] 3. Improving the accuracy of change impact analysis In terms of change impact analysis, this application uses AI technology to more accurately assess the impact of changes on the software as a whole. Through comprehensive analysis of multi-dimensional information such as software architecture, code dependencies, historical change data, etc., the AI ​​system can predict the problems and risks that may be caused by changes, and formulate corresponding response strategies in advance. Compared with traditional methods that rely on manual experience and document analysis, the AI-driven change impact analysis of this application is not only faster, but also more accurate. It can discover some potential problems hidden in complex codes and architectures, reduce software failures and defects caused by changes, and thus reduce software maintenance costs and risks.

[0020] 4. Accelerate fault location In the field of rapid fault location, this application also shows great advantages. When the software fails, the AI ​​system can quickly locate the root cause of the fault based on the fault phenomenon and related log information, combined with the established association relationship. It can filter out the most likely cause from many possible fault points and provide a detailed analysis of the fault path and impact range. This enables developers and maintenance personnel to find the problem more quickly and take repair measures in time, greatly shortening the fault recovery time and improving the availability and stability of the software. Compared with traditional troubleshooting methods, the rapid fault location function of this application can save a lot of time and labor costs, and improve the overall operation and maintenance efficiency of software engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is an example diagram of the architecture of an artificial intelligence-based service triggering system according to an embodiment of the present application; Figure 2 This is an example diagram of the architecture of a service triggering server of an artificial intelligence-based service triggering system according to an embodiment of the present application; Figure 3 This is a flowchart of a method for triggering a service based on artificial intelligence according to an embodiment of the present application; Figure 4 This is an example diagram of triggering a change impact analysis according to an artificial intelligence-based business triggering method according to an embodiment of the present application; Figure 5 This is an example diagram of basic granularity in software engineering; Figure 6 This is an example diagram of fault location triggering based on an artificial intelligence-based service triggering method according to an embodiment of the present application; Figure 7 A schematic diagram of the structure of the device provided in this application. DETAILED DESCRIPTION

[0023] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0024] It should be noted that the following embodiments and features in the embodiments may be combined with each other in the absence of conflict; and, based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making any creative work are within the scope of protection of the present disclosure.

[0025] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0026] Figure 1 FIG. 1 is an example diagram of the architecture of an artificial intelligence-based service triggering system according to an embodiment of the present application, such as Figure 1 As shown, the system may include a service triggering server 101, a communication network 102 and / or one or more service triggering clients 103. Figure 1The example in FIG. 1 is a plurality of service triggering clients 103 .

[0027] The business trigger server 101 can be any appropriate server for storing information, data, programs and / or any other suitable type of content. In some embodiments, the business trigger server 101 can perform appropriate functions. For example, in some embodiments, the business trigger server 101 can be used to trigger a business based on artificial intelligence. As an optional example, in some embodiments, the business trigger server 101 can be used to: use a parsing module to parse the design drawings in the software engineering process and extract the design drawing elements; use a similarity calculation module to calculate the similarity between the design drawing elements and the development requirements, and the development requirements and the code; use an association calculation module to calculate the association between the design drawing and the code based on the similarity between the design drawing elements and the development requirements, and the development requirements and the code; when the software is changed, the change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation; when the software fails, the fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting.

[0028] Figure 2 FIG. 1 is an example diagram of the architecture of a service triggering server of an artificial intelligence-based service triggering system according to an embodiment of the present application, such as Figure 2 As shown, in this embodiment, the business trigger service end includes a parsing module, a similarity calculation module, an association calculation module, a change impact analysis trigger module and a fault location trigger module.

[0029] In this embodiment, the parsing module is used to parse the design drawing in the software engineering process and extract the design drawing elements. As an optional example, in this embodiment, the parsing module identifies the design drawing through a graph parsing algorithm and extracts the design drawing elements, wherein the design drawing elements include functional modules and their mutual association, hierarchical relationship, and sequential relationship.

[0030] In this embodiment, the similarity calculation module is used to calculate the similarity between the design drawing elements and the development requirements, and between the development requirements and the code. As an optional example, in this embodiment, the similarity calculation module is used to calculate the similarity between the design drawing elements and the development requirements, and to calculate the similarity between the development requirements and the code by comparing the functional descriptions of the development requirements and the code in the log.

[0031] In this embodiment, the association relationship calculation module is used to calculate the association relationship between the design drawing and the code based on the similarity between the design drawing elements and the development requirements, and the development requirements and the code. As an optional example, in this embodiment, the association relationship calculation module is used to dynamically update and display the association relationship between the design drawing and the code according to the iteration and change status of the software engineering.

[0032] In this embodiment, the change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation when the software is changed. As an optional example, in this embodiment, the change impact analysis trigger module is used to trigger the artificial intelligence component to search for the development requirement change corresponding to the corresponding change when the software or the software code is changed, and send the corresponding change information and the change impact assessment report to the change initiator for confirmation.

[0033] In this embodiment, the fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting when the software fails. As an optional example, in this embodiment, the fault location trigger module is used to trigger the artificial intelligence component to search for the development requirement fault corresponding to the corresponding code when the software fails, and send the corresponding fault information and troubleshooting suggestions to the maintenance locator for troubleshooting.

[0034] It should be noted that the artificial intelligence component in this embodiment can use deep learning algorithms to learn and train software engineering data to improve the accuracy of analysis and prediction.

[0035] In practical applications, the artificial intelligence-based business triggering system of this embodiment also includes a rights management module and a data storage module. In practical applications, the rights management module is used to control the access and operation of the system. The data storage module is used to store design drawings, requirement documents, and code integration log data in the software engineering process.

[0036] As another example, in some embodiments, the business triggering server 101 may send an artificial intelligence-based business triggering method to the business triggering client 103 for user use based on a request of the business triggering client 103 .

[0037] As an optional example, in some embodiments, the business trigger client 103 is used to provide a visual business trigger interface, which is used to receive a user's selection input operation for business triggering based on artificial intelligence, and, in response to the selection input operation, obtain a business trigger interface corresponding to the option selected by the selection input operation from the business trigger server 101 and display the business trigger interface, wherein the business trigger interface at least displays information on business triggering based on artificial intelligence and operation options for the information on business triggering based on artificial intelligence.

[0038] In some embodiments, the communication network 102 can be any suitable combination of one or more wired and / or wireless networks. For example, the communication network 102 can include any one or more of the following: the Internet, an intranet, a wide area network (WAN), a local area network (LAN), a wireless network, a digital subscriber line (DSL) network, a frame relay network, an asynchronous transfer mode (ATM) network, a virtual private network (VPN), and / or any other suitable communication network. The service trigger client 103 can be connected to the communication network 102 via one or more communication links (e.g., communication link 104), and the communication network 102 can be linked to the service trigger service end 101 via one or more communication links (e.g., communication link 105). The communication link can be any communication link suitable for transmitting data between the service trigger client 103 and the service trigger service end 101, such as a network link, a dial-up link, a wireless link, a hard-wired link, any other suitable communication link, or any suitable combination of such links.

[0039] The service trigger client 103 may include any one or more clients that present an interface related to service triggering based on artificial intelligence in an appropriate form for use and operation by a user. In some embodiments, the service trigger client 103 may include any suitable type of device. For example, in some embodiments, the service trigger client 103 may include a mobile device, a tablet computer, a laptop computer, a desktop computer, and / or any other suitable type of client device.

[0040] Although the business trigger server 101 is illustrated as one device, in some embodiments, any appropriate number of devices may be used to perform the functions performed by the business trigger server 101. For example, in some embodiments, multiple devices may be used to implement the functions performed by the business trigger server 101. Alternatively, a cloud service may be used to implement the functions of the business trigger server 101.

[0041] Based on the above system, an embodiment of the present application provides a service triggering method based on artificial intelligence, which is described below through the following embodiments.

[0042] Figure 3 The following is a flowchart of a method for triggering a service based on artificial intelligence according to an embodiment of the present application. The method for triggering a service based on artificial intelligence in this embodiment can be executed on a service triggering server, and the method for triggering a service based on artificial intelligence includes the following steps: Step S201: using a parsing module to parse the design drawing in the software engineering process and extract the design drawing elements.

[0043] As an optional example, in this embodiment, a parsing module is used to identify the design drawing through a graph parsing algorithm to extract design drawing elements, wherein the design drawing elements include functional modules and their mutual associations, hierarchical relationships, and sequential relationships.

[0044] Step S202: using a similarity calculation module to calculate similarities between design drawing elements and development requirements, and between development requirements and codes.

[0045] As an optional example, in this embodiment, a similarity calculation module is used to calculate the similarity between design drawing elements and development requirements, and the similarity between development requirements and code is calculated by comparing the development requirements with the functional descriptions incorporated into the log.

[0046] Step S203: using the association relationship calculation module to calculate the association relationship between the design drawing and the code according to the similarity between the design drawing elements and the development requirements, and between the development requirements and the code.

[0047] As an optional example, in this embodiment, an association relationship calculation module is used to dynamically update and display the association relationship between the design diagram and the code according to the iteration and change status of the software engineering.

[0048] Step S204: When the software is changed, the change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation.

[0049] As an optional example, in this embodiment, when the software or the software code changes, the change impact analysis trigger module is used to trigger the artificial intelligence component to search for the development requirement change corresponding to the corresponding change, and send the corresponding change information and change impact assessment report to the change initiator for confirmation. In this embodiment, the artificial intelligence component can use deep learning algorithms to learn and train software engineering data to improve the accuracy of analysis and prediction.

[0050] Figure 4 This is an example diagram of triggering a change impact analysis according to an artificial intelligence-based business triggering method according to an embodiment of the present application, such as Figure 4 As shown, when the software or code changes, the artificial intelligence (AI) component is triggered to perform analysis, and the AI ​​component calls the AI ​​service to search for the required functional changes corresponding to the corresponding code. Figure 5 This is an example diagram of basic granularity in software engineering, such as Figure 5 As shown, the requirement function is related to the iterative version, and the iterative version is related to the basic elements "requirements", "design drawings", "codes" and "personnel". The AI ​​agent sends the basic information involved in the change to the changer for confirmation one by one.

[0051] Step S205: When a software failure occurs, a fault location trigger module is used to send corresponding fault information to a maintenance locator for troubleshooting.

[0052] As an optional example, in this embodiment, when a software failure occurs, a fault location trigger module is used to trigger an artificial intelligence component to search for the development requirement failure corresponding to the corresponding code, and the corresponding fault information and troubleshooting suggestions are sent to the maintenance locator for troubleshooting.

[0053] Figure 6 FIG. 1 is an example diagram of a fault location triggering method based on artificial intelligence according to an embodiment of the present application, such as Figure 6 As shown, when a software failure occurs, the AI ​​component is triggered for analysis, and the AI ​​service searches for the required functional failure corresponding to the corresponding code. The function is related to the iterative version, and the iterative version is related to the basic elements "requirements", "design drawings", "codes" and "personnel". The AI ​​agent sends the basic information related to the failure to the software maintenance locator for one-by-one investigation.

[0054] The artificial intelligence-based service triggering method and system of the embodiment of the present application has the following beneficial technical effects in the software engineering life cycle, especially in the fields of change impact analysis and rapid fault location, by means of the application of artificial intelligence (AI) technology: 1. Quickly establish association relationships With the support of AI technology, it is possible to quickly establish various complex relationships between iterative requirements, design drawings, key nodes, and related personnel at various stages of software engineering, such as requirements analysis, design, development, testing, and operation and maintenance. The establishment of such relationships no longer relies on traditional manual combing and document recording, but uses AI algorithms to analyze and mine massive amounts of software engineering data, thereby efficiently identifying the inherent connections between different elements. For example, when requirements change, AI can quickly identify the scope of impact and related personnel of the change on various links such as design drawings, code implementation, and test cases, providing clear guidance for subsequent processing.

[0055] 2. Intelligent Service Triggering Mechanism Based on the quickly established association relationship, this application implements an intelligent business trigger mechanism. Once an action occurs in any associated link in the software engineering life cycle, such as a change in requirements, code submission, or a problem found in testing, the system will automatically generate a response event and trigger the corresponding intelligent business process. This mechanism greatly improves the response speed and processing efficiency of software engineering. For example, when a developer submits a code change, the AI ​​system will immediately analyze the impact of the change on other modules, automatically trigger related testing tasks, and notify affected developers and testers. At the same time, it will also evaluate the risk level of the change according to preset rules to provide a basis for subsequent decision-making. This intelligent triggering mechanism avoids the tediousness and inefficiency of manually notifying and manually starting related processes one by one in the traditional mode, ensuring close connection and efficient collaboration between various links in software engineering.

[0056] 3. Improving the accuracy of change impact analysis In terms of change impact analysis, this application uses AI technology to more accurately assess the impact of changes on the software as a whole. Through comprehensive analysis of multi-dimensional information such as software architecture, code dependencies, historical change data, etc., the AI ​​system can predict the problems and risks that may be caused by changes, and formulate corresponding response strategies in advance. Compared with traditional methods that rely on manual experience and document analysis, the AI-driven change impact analysis of this application is not only faster, but also more accurate. It can discover some potential problems hidden in complex codes and architectures, reduce software failures and defects caused by changes, and thus reduce software maintenance costs and risks.

[0057] 4. Accelerate fault location In the field of rapid fault location, this application also shows great advantages. When the software fails, the AI ​​system can quickly locate the root cause of the fault based on the fault phenomenon and related log information, combined with the established association relationship. It can filter out the most likely cause from many possible fault points and provide a detailed analysis of the fault path and impact range. This enables developers and maintenance personnel to find the problem more quickly and take repair measures in time, greatly shortening the fault recovery time and improving the availability and stability of the software. Compared with traditional troubleshooting methods, the rapid fault location function of this application can save a lot of time and labor costs, and improve the overall operation and maintenance efficiency of software engineering.

[0058] like Figure 7As shown, the present application also provides a device, including a processor 310, a communication interface 320, a memory 330 for storing a processor executable computer program, and a communication bus 340. The processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 implements the above-mentioned artificial intelligence-based service triggering method by running an executable computer program.

[0059] Among them, the computer program in the memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0060] The system embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected based on actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0061] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0062] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A business triggering system based on artificial intelligence, characterized in that: The system includes a service triggering service end, and the service triggering service end includes: The parsing module is used to parse the design drawings in the software engineering process and extract the design drawing elements; A similarity calculation module is used to calculate the similarity between design elements and development requirements, and between development requirements and codes; The association relationship calculation module is used to calculate the association relationship between the design drawing and the code according to the similarity between the design drawing elements and the development requirements, and the development requirements and the code; The change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation when the software is changed; The fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting when a software fault occurs.

2. The artificial intelligence-based service triggering system according to claim 1, characterized in that: The parsing module recognizes the design drawing through a graph parsing algorithm and extracts the design drawing elements, which include functional modules and their mutual association, hierarchical relationship and sequential relationship.

3. The service triggering system based on artificial intelligence according to claim 1 is characterized in that: The similarity calculation module is used to calculate the similarity between the design drawing elements and the development requirements, and to calculate the similarity between the development requirements and the code by comparing the functional descriptions in the logs in which the development requirements and the code are merged.

4. The artificial intelligence-based service triggering system according to claim 1, characterized in that: The association relationship calculation module is used to dynamically update and display the association relationship between the design diagram and the code according to the iteration and change status of the software engineering.

5. The service triggering system based on artificial intelligence according to claim 1 is characterized in that: The change impact analysis trigger module is used to trigger the artificial intelligence component to search for the development requirement changes corresponding to the corresponding changes when the software or the software code changes, and send the corresponding change information and change impact assessment report to the change initiator for confirmation.

6. The artificial intelligence-based service triggering system according to claim 1, characterized in that: The fault location trigger module is used to trigger the artificial intelligence component to search for the development requirement fault corresponding to the corresponding code when a software fault occurs, and send the corresponding fault information and troubleshooting suggestions to the maintenance locator for troubleshooting.

7. The artificial intelligence-based service triggering system according to claim 1, characterized in that: The artificial intelligence component can use deep learning algorithms to learn and train software engineering data to improve the accuracy of analysis and prediction.

8. The artificial intelligence-based service triggering system according to claim 1, characterized in that: The system further comprises: The authority management module is used to control the access and operation of the system; The data storage module is used to store design drawings, requirement documents, and code integration log data in the software engineering process.

9. A service triggering method based on artificial intelligence, characterized in that: The method comprises: The parsing module is used to parse the design drawings in the software engineering process and extract the design drawing elements; Use the similarity calculation module to calculate the similarity between design elements and development requirements, and between development requirements and codes; The association relationship calculation module is used to calculate the association relationship between the design drawing and the code according to the similarity between the design drawing elements and the development requirements, and the development requirements and the code; When software is changed, the change impact analysis trigger module is used to send the corresponding change information to the change initiator for confirmation; When a software failure occurs, the fault location trigger module is used to send the corresponding fault information to the maintenance locator for troubleshooting.

10. A computer device, characterized in that: The computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the steps of the method according to claim 9 are implemented when the processor executes the program.

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