Code keyword automatic retrieval method and device, equipment and medium

Abstract

The invention relates to the technical field of research and development management, can be applied to business scenes such as financial science and technology, medical health and the like, and discloses a code keyword automatic retrieval method which comprises the steps of deploying a tool platform and completing initial configuration, developing a user-defined plug-in for identifying code keywords, deploying and loading the user-defined plug-in, configuring the connection between the tool platform and the database, compiling an automatic script or a task scheduling tool, calling a user-defined plug-in to scan a target code library, identifying code snippets containing target keywords, extracting target keyword information from the code snippets, and uploading the target keyword information to the database and the tool platform. By scanning the target code library, automatic extraction and management of target keyword information in a large-scale code library are realized, and the problems of low efficiency and inaccuracy of manual retrieval are avoided; by uploading the target keyword information to the database and the tool platform, storage and real-time display of the retrieval result are realized, and the efficiency and accuracy of code retrieval are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of research and development management, and in particular to a method, device, equipment and storage medium for automatic retrieval of code keywords. Background Art

[0002] In the field of fintech business, as business scenarios become increasingly rich and complex, enterprise information systems usually cover multiple subsystems and project modules. For example, in the insurance business, it covers multiple subsystems such as underwriting, claims, and finance, and the claims subsystem includes multiple project modules such as reporting, investigation, loss assessment, settlement, and payment. Due to the diversity of business processes and the complexity of system architecture, the information system of fintech enterprises may consist of hundreds or thousands of engineering projects. The development and maintenance of these engineering projects put forward higher requirements for code quality management and content retrieval.

[0003] In the actual system development and maintenance process, it is often necessary to search large-scale code bases to confirm whether the comments in the project or the content returned to the user contain sensitive information, or whether certain key resources are used in multiple projects. If this information is not mastered in a timely manner, it may lead to data leakage, illegal use of resources or other risks in the system. However, the current keyword search mainly relies on developers to manually search the project code one by one through the IDE (Integrated Development Environment) tool. The specific operation is usually to send the search task to the project leader or maintenance personnel, who use the local search function to analyze and record each project one by one. This method is not only time-consuming and labor-intensive, but also because it relies on manual operation, the integrity and accuracy of the search results are difficult to guarantee. When faced with hundreds of engineering projects, this manual search method obviously has the problems of low efficiency and high risk of omission.

[0004] In the field of healthcare, information systems also present the characteristics of complexity and multi-modularity. For example, in hospital information systems, multiple functional modules are usually included, such as medical record management, drug management, financial settlement, and diagnosis and treatment process management. These systems need to process a large amount of patient information and diagnosis and treatment data, and must meet strict data security and privacy protection requirements. In the process of system development and maintenance, it is also necessary to perform keyword searches on a large number of code bases to check whether there are sensitive words or illegal data calls. However, the current retrieval method mainly relies on developers to manually retrieve project codes through local tools. System codes in the field of healthcare usually involve highly sensitive information, and manual retrieval methods cannot ensure that all sensitive information can be accurately identified, which may lead to patient privacy leaks or system security risks.

[0005] In summary, existing keyword search methods have obvious problems such as low efficiency, inaccurate results, lack of automation and data security when facing large-scale code bases. Especially in the fields of finance and healthcare, the complexity of information systems and the need to manage sensitive data make these problems particularly prominent. Therefore, a technical means is needed to automatically and efficiently perform keyword search and analysis on large-scale code bases to improve search efficiency, ensure the integrity and accuracy of search results, and strengthen data security and privacy protection. Summary of the invention

[0006] The main purpose of the present invention is to provide a method, device, equipment and storage medium for automatic retrieval of code keywords, aiming to solve the technical problems that the prior art relies on manual operation when retrieving target keyword information in a large-scale code library, resulting in low retrieval efficiency and lack of automated processing means.

[0007] To achieve the above object, the present invention provides a code keyword automatic retrieval method, comprising:

[0008] Deploy a tool platform for code analysis and processing, and complete initialization configuration of the tool platform;

[0009] Based on the interface provided by the tool platform, develop a custom plug-in for identifying code keywords;

[0010] Deploy the custom plug-in to the plug-in directory of the tool platform, and load the custom plug-in;

[0011] Configuring the connection between the tool platform and the database;

[0012] Build automation scripts or configure task scheduling tools;

[0013] By using the automated script or task scheduling tool, the custom plug-in is called to scan the target code library to identify code snippets containing target keywords;

[0014] Target keyword information is extracted from the code snippet, and the target keyword information is uploaded to the database and the tool platform.

[0015] Furthermore, in order to achieve the above-mentioned object, the present invention provides a code keyword automatic retrieval device, comprising:

[0016] A tool platform management module, used to deploy a tool platform for code analysis and processing, and complete the initialization configuration of the tool platform;

[0017] A plug-in development module, used to develop a custom plug-in for identifying code keywords based on an interface provided by the tool platform;

[0018] A plug-in deployment and loading module, used to deploy the custom plug-in to the plug-in directory of the tool platform and load the custom plug-in;

[0019] A database connection configuration module, used to configure the connection between the tool platform and the database;

[0020] Automated task management module, used to build automated scripts or configure task scheduling tools;

[0021] A code scanning and matching module, which is used to call the custom plug-in to scan the target code library through the automation script or task scheduling tool to identify the code fragments containing the target keyword;

[0022] The data extraction and uploading module is used to extract target keyword information from the code snippet and upload the target keyword information to the database and the tool platform.

[0023] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer device, which includes a memory, a processor, and a code keyword automatic retrieval program stored in the memory and executable on the processor, and the code keyword automatic retrieval program, when executed by the processor, implements the steps of the code keyword automatic retrieval method as described above.

[0024] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a code keyword automatic retrieval program is stored, and when the code keyword automatic retrieval program is executed by a processor, the steps of the code keyword automatic retrieval method described above are implemented.

[0025] Beneficial effects: The present invention relates to the field of R&D management technology, and can be applied to business scenarios such as financial technology and medical health. A method for automatic retrieval of code keywords is disclosed, including: deploying a tool platform and completing initialization configuration, developing a custom plug-in for identifying code keywords, deploying and loading the custom plug-in, configuring the connection between the tool platform and the database, writing an automated script or task scheduling tool, calling the custom plug-in to scan the target code library, identifying code snippets containing target keywords, extracting target keyword information from the code snippets, and uploading them to the database and tool platform. The present invention uses an automated script or task scheduling tool to call a custom plug-in to scan the target code library, thereby realizing the automatic extraction and management of target keyword information in a large-scale code library, and avoiding the inefficiency and inaccuracy of manual retrieval; by uploading the target keyword information to the database and tool platform, the persistent storage and real-time display of the retrieval results are realized, which effectively improves the efficiency and accuracy of code retrieval, reduces the risk of missing sensitive information, and facilitates subsequent query and analysis operations, thereby strengthening data management capabilities and information security. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0027] Figure 1 A schematic diagram of an application environment of a method for automatic code keyword retrieval in an embodiment of the present invention;

[0028] Figure 2 A schematic diagram of a flow chart of an embodiment of a method for automatically retrieving code keywords of the present invention;

[0029] Figure 3 A schematic diagram of functional modules of a preferred embodiment of the automatic code keyword retrieval device of the present invention;

[0030] Figure 4 A schematic diagram of the structure of a computer device in one embodiment of the present invention;

[0031] Figure 5 FIG. 4 is another schematic diagram of the structure of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0032] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0033] The code keyword automatic retrieval method provided by the embodiment of the present invention can be applied in the following aspects: Figure 1In the application environment, the user end communicates with the server end through the network. The server end can deploy the tool platform through the user end and complete the initialization configuration, develop a custom plug-in for identifying code keywords, deploy and load the custom plug-in, configure the connection between the tool platform and the database, write an automated script or task scheduling tool, call the custom plug-in to scan the target code library, identify the code fragment containing the target keyword, extract the target keyword information from the code fragment, and upload it to the database and tool platform. The present invention calls the custom plug-in to scan the target code library through an automated script or task scheduling tool, realizes the automated extraction and management of the target keyword information in a large-scale code library, and avoids the inefficiency and inaccuracy of manual retrieval; by uploading the target keyword information to the database and tool platform, the persistent storage and real-time display of the retrieval results are realized, the efficiency and accuracy of the code retrieval are effectively improved, the risk of omission of sensitive information is reduced, and the subsequent query and analysis operations are facilitated, and the data management capabilities and information security are strengthened. Among them, the user end can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server end can be implemented with an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0034] See also Figure 2 , Figure 2 This is a flow chart of an embodiment of the automatic code keyword retrieval method provided by the present invention. It should be noted that although the logical sequence is shown in the flow chart, in some cases, the steps shown or described may be performed in a different order than that here.

[0035] like Figure 2 As shown, the code keyword automatic retrieval method proposed by the present invention includes the following steps:

[0036] S10, deploying a tool platform for code analysis and processing, and completing initialization configuration of the tool platform;

[0037] In this embodiment, the selection of tool platforms is the basis for deployment. Common tool platforms may include commercial platforms. These platforms need to have functions such as code analysis, plug-in extension, database connection, and data display. Before deployment, it is necessary to select a suitable tool platform according to the actual needs of the enterprise, considering the platform's compatibility, expansion capabilities, and data processing capabilities.

[0038] First, prepare server resources in the deployment environment and determine the platform installation package and installation method. For cloud environments, you can choose to deploy the tool platform through image deployment or container deployment. In a local environment, you can install it by downloading the official installation package.

[0039] When installing the tool platform, you need to execute the installation file and follow the prompts to complete the installation process. The initial configuration of the platform usually includes setting up an administrative account, selecting a language environment, and determining the platform's basic path and port number. This process ensures that the tool platform can be started normally and has basic operating permissions.

[0040] Complete the installation by executing the platform installation package or running a script. In a cloud environment, you may complete the initial configuration of the platform by starting a container or virtual machine. In a local environment, you may complete the initial configuration by running the installation program, configuring environment variables, etc. After the initial configuration is completed, visit the management page of the tool platform to confirm that the platform can run normally.

[0041] After deployment, the tool platform needs to set up permission management to ensure that different users have appropriate access rights and operation permissions in the platform. Permission management includes creating administrator accounts, ordinary user accounts, and assigning permission ranges to different user roles. This step ensures the security of the platform and the confidentiality of data.

[0042] Create user roles and user accounts in the management interface of the tool platform. Assign permissions according to different user roles, such as code scanning permissions, data viewing permissions, configuration management permissions, etc. After the permission management configuration is completed, save the settings and exit the management interface to ensure that the permission configuration takes effect.

[0043] In order to support subsequent custom plug-in deployment, the tool platform needs to configure the plug-in directory path. The plug-in directory path is the key location for the tool platform to load plug-ins. It is usually located in the platform's configuration file and can be set by modifying the configuration file.

[0044] Find the configuration item of the plug-in directory path in the configuration file of the tool platform and modify the path setting according to the actual needs of the enterprise. After saving the configuration file, restart the tool platform to make the new plug-in directory path take effect. Check the plug-in management page in the management interface to confirm that the plug-in directory has been configured.

[0045] Example description: In the field of healthcare, the hospital's information system usually contains multiple subsystems and modules, such as medical record management, drug management, and financial settlement systems. These systems require regular security checks on the code base to ensure that there are no interfaces containing sensitive information or illegal calls in the system. When deploying the tool platform, the hospital's information technology department can choose a tool platform based on a cloud environment to quickly complete deployment and initialization configuration through containerization. For example, in order to analyze and detect whether there is unauthorized access to sensitive data in the code in the electronic medical record system, different user roles can be set in the tool platform to ensure that only authorized personnel can view and modify the code scanning results. Through the plug-in directory configuration, technicians can deploy customized code scanning plug-ins in the tool platform to detect sensitive data in the electronic medical record system, thereby effectively protecting patients' privacy information and improving the security and compliance of medical information systems.

[0046] In the financial field, the information systems of financial institutions such as banks and insurance companies usually cover multiple business modules, such as customer management, loan approval, insurance claims, financial settlement, etc. These systems involve a large amount of sensitive information and fund transaction records of customers, and the code base may contain sensitive fields, such as ID number, bank card number, account balance, etc. Once these sensitive information is maliciously accessed or leaked, it may lead to serious financial risks and legal liabilities. Therefore, when developing and maintaining information systems, financial institutions must strictly control the sensitive information in the code base. For example, in the insurance company's claims system, in order to ensure that there is no unauthorized customer information call in the code, the technical department can deploy a tool platform to regularly scan the code base through automated scripts and task scheduling tools. By developing custom plug-ins, sensitive information fields that may be contained in the code can be identified, such as customer identity information, claim amount, payment account, etc. Once the code snippet containing these fields is identified, the tool platform will upload the matching results to the database and display them to the security manager through a visual interface.

[0047] During this process, banks or insurance companies can also use the permission management function of the tool platform to ensure that only authorized developers or security personnel can view and process the scan results. In this way, not only can the risk of customer information leakage be effectively reduced, but also the regulatory compliance requirements of the financial industry can be met to ensure the security and stability of the system. For example, for a bank's loan approval system, after deploying the tool platform, an automated task can be set to scan the code base for sensitive information every week to identify whether there is unencrypted customer data transmission code. If a problem code is found, the system will automatically generate a report for developers to analyze and process, thereby improving the compliance and security of the system.

[0048] By deploying a tool platform for code analysis and processing and completing the initial configuration of the tool platform, the tool platform is automatically deployed and managed, allowing subsequent code analysis and keyword matching to be carried out efficiently. The tool platform's permission management configuration and plug-in directory configuration improve the system's security and expansion capabilities, reduce security risks caused by manual configuration errors, and ensure that the system can continue to operate efficiently.

[0049] S20, developing a custom plug-in for identifying code keywords based on an interface provided by the tool platform;

[0050] In this embodiment, the development of a custom plug-in first requires analysis and understanding of the interface methods and API documents provided by the tool platform. These interface methods contain the interaction rules between the plug-in and the tool platform, such as plug-in loading, calling, and return result format. The API document usually provides all the technical details required for plug-in development, including available interface methods, parameter descriptions, data formats, and return values.

[0051] Log in to the developer portal or management page of the tool platform, download the relevant API documentation, analyze the plug-in development interface provided in the interface documentation, confirm the calling method, parameter format, and data return structure required for plug-in development, and if the tool platform supports dynamic interface extension, you also need to confirm how to define a custom interface method.

[0052] Before developing a custom plug-in, you need to build a development environment that is compatible with the tool platform. This usually includes installing necessary development tools, configuring a code editor, downloading the tool platform's SDK (Software Development Kit) or plug-in templates, etc. The configuration of the development environment ensures that developers can efficiently write and debug plug-in code.

[0053] According to the technical requirements of the tool platform, select the appropriate development language (such as Java, Python, etc.), install relevant development tools, such as IDE (Integrated Development Environment) and code version management tools, download the SDK or plug-in template provided by the tool platform, and import it into the development environment. Configure the basic directory structure and dependent files of the plug-in in the development environment to ensure that the plug-in project can be compiled and run normally.

[0054] The core component is the part of the custom plug-in used to implement the main functions, including the plug-in's main class, scanning logic class, data processing class, etc. The plug-in's core component is responsible for receiving the code file delivered by the tool platform, scanning the code line by line, and identifying the code snippets containing the target keywords.

[0055] Create a main class (e.g., KeywordScannerPlugin) in the plug-in project and define the basic information of the plug-in, such as the plug-in name, version number, description, etc. Define the scanning logic class, write the function of reading the code file line by line, and use string matching or regular expression matching to identify the target keyword. Define the data processing class, which is responsible for formatting the identified target keyword information according to the requirements of the tool platform. If the tool platform provides an event-driven interface, you also need to implement methods such as plug-in startup, shutdown, and exception handling.

[0056] The target keyword identification module is the core functional module of the plug-in, which is responsible for identifying code snippets containing target keywords from code files and generating target keyword information including file path, line number and context content. This module usually includes functions such as string matching, character filtering, and keyword tagging.

[0057] Write a string matching algorithm that supports matching based on a fixed keyword list or regular expressions. Perform context extraction on the identified code snippet to obtain several lines of code before and after to form complete context information. Annotate and format the target keyword information, and encapsulate the file path, line number, and context content into a data structure according to the requirements of the tool platform. If the tool platform supports dynamic updating of the keyword list, you also need to implement an interface call to dynamically obtain the latest keyword list.

[0058] Example description: In the healthcare field, the code base in the hospital information system usually contains sensitive information such as patient privacy data and medical records. In order to ensure the compliance and security of the system, the hospital technology department can develop a custom plug-in to identify target keywords such as patient identity information and medical diagnosis results contained in the code base. For example, in the code base of the electronic medical record system, the plug-in can automatically identify code snippets containing information such as patient name, ID number, medical record number, etc., and generate target keyword information containing file path, line number and context content. The identified sensitive information can be uploaded to the tool platform for information security personnel to analyze and process to avoid the leakage of patient privacy data.

[0059] In the financial field, the business systems of financial institutions such as banks and insurance companies usually involve a large amount of customer information and transaction data, which may appear in plain text in the system code. In order to reduce the risk of information leakage, financial institutions can develop custom plug-ins to identify sensitive information fields in the code base, such as bank card numbers, account balances, transaction records, etc. For example, in the bank's loan approval system, a custom plug-in can identify code snippets containing customer identity information and loan amounts, generate target keyword information, and upload it to the tool platform for security managers to analyze. If sensitive information fields stored in plain text are identified, security managers can repair them in a timely manner, thereby improving the data security and compliance of the financial system.

[0060] By developing custom plug-ins, we have expanded the functionality of the tool platform, enabling it to automatically scan and analyze the code base based on specific target keywords. Through the target keyword recognition module, we can accurately extract target keyword information from code snippets and output the recognition results in a structured manner, improving the accuracy and efficiency of code retrieval. Compared with traditional manual retrieval methods, the automated keyword recognition plug-in significantly reduces labor costs and retrieval time, avoids the risk of missing information, and ensures the integrity and consistency of retrieval results.

[0061] S30, deploying the custom plug-in to the plug-in directory of the tool platform, and loading the custom plug-in;

[0062] In this embodiment, before deploying the custom plug-in to the tool platform, the plug-in project needs to be packaged to generate a plug-in file format that meets the requirements of the tool platform. Common plug-in file formats include JAR, ZIP, etc. The specific format depends on the technical requirements of the tool platform. The plug-in packaging process ensures the integrity of the plug-in and facilitates loading and management in the tool platform.

[0063] Use the compilation tool in the development environment to package the source code files, resource files, configuration files, etc. of the plug-in project into a plug-in file. According to the requirements of the tool platform, generate necessary metadata files during the packaging process, such as plug-in description files, version information files, etc. Confirm that the structure and format of the plug-in file conform to the specifications of the tool platform, such as file path, file name format, etc.

[0064] After the plug-in is packaged, you need to copy the plug-in file to the plug-in directory of the tool platform. The plug-in directory is the path used by the tool platform to manage and load plug-ins. By placing the plug-in file in this directory, the tool platform can automatically identify and load new plug-ins.

[0065] Confirm the path setting of the plug-in directory in the tool platform's configuration management page or file system. Use a file management tool or automated script to copy the packaged plug-in file to the plug-in directory. If the tool platform supports the remote upload plug-in function, you can also upload the plug-in file through the tool platform's management interface.

[0066] After placing the plug-in file in the plug-in directory, you need to trigger the plug-in loading operation through the management interface of the tool platform. The management interface of the tool platform usually provides plug-in management functions, which can perform operations such as loading, enabling, disabling, and uninstalling.

[0067] Log in to the management interface of the tool platform and enter the plug-in management page. On the plug-in management page, find the newly uploaded plug-in file and perform the "load" or "enable" operation. When loading a plug-in, the tool platform will verify the integrity and version information of the plug-in. If the verification passes, the plug-in is loaded successfully. For tool platforms that support API management, you can perform the loading operation by calling the plug-in management interface to avoid manual operation.

[0068] After the plug-in is loaded, you need to query the plug-in loading log of the tool platform to confirm whether the plug-in is loaded successfully. The loading log usually records the loading time, loading results, error information, etc. of the plug-in. If the plug-in fails to load, you can locate the problem by analyzing the loading log.

[0069] In the management interface of the tool platform, enter the system log or plug-in management page to query the plug-in loading log. According to the log information, confirm the loading status of the plug-in. If the log shows "Loaded successfully", the plug-in has been enabled normally; if an error message is displayed, you need to troubleshoot the problem. For tool platforms that support remote log query, you can query the loading log information through the API interface and return the loading status of the plug-in.

[0070] If an exception occurs during the plugin loading process, you can solve the problem by restarting the tool platform or reloading the plugin. The restart operation includes stopping the tool platform service, clearing the plugin cache, and then restarting the tool platform to ensure that the plugin can be loaded normally.

[0071] In the tool platform management interface, execute the "Stop" operation to shut down the tool platform service. Clean the tool platform plug-in cache directory to ensure that there are no remaining error plug-in files. Restart the tool platform service, enter the plug-in management page, and confirm that the plug-in has been loaded normally. If the plug-in still cannot be loaded, you can try to repackage the plug-in file and copy it back to the plug-in directory.

[0072] Example description: In the field of healthcare, hospital information systems often need to expand functions through plug-ins to meet personalized business needs. For example, a hospital may need to develop a plug-in to automatically identify sensitive information fields in the medical record system (such as patient name, ID number, diagnosis results, etc.) and generate a sensitive information matching report. After completing the development and packaging of the plug-in, you can upload the plug-in file to the plug-in directory of the hospital information system and execute the plug-in loading operation through the management interface. If the plug-in is loaded successfully, the system will automatically perform the sensitive information identification task, helping the hospital to promptly discover and deal with privacy data risks in the system and ensure the security and compliance of patient information.

[0073] In the financial sector, banks and insurance companies often need to scan the code base in the information system to identify sensitive fields that may lead to customer information leakage (such as bank card numbers, account balances, transaction records, etc.). Technicians can develop a custom plug-in to identify this sensitive information and generate a security scan report. After the plug-in is developed, upload the plug-in file to the bank's tool platform plug-in directory, and perform the plug-in loading operation through the tool platform's management interface. If the plug-in is loaded successfully, the system will automatically scan the code base and generate a matching report containing sensitive fields. This process reduces the workload of manual retrieval, improves the security and compliance of the system, and helps financial institutions effectively reduce the risk of information leakage.

[0074] By deploying custom plug-ins to the plug-in directory of the tool platform and executing the plug-in loading operation, the tool platform function is expanded, enabling the tool platform to identify and process target keyword information. Through the plug-in loading log query and exception handling mechanism, the loading status of the plug-in can be effectively ensured to avoid affecting the normal use of the tool platform due to plug-in loading failure. Compared with the traditional manual configuration method, the automated plug-in deployment and loading operation greatly improves the management efficiency and stability of the system.

[0075] S40, configuring the connection between the tool platform and the database;

[0076] In this embodiment, the tool platform needs to establish a reliable connection with the database to achieve storage and management of search results. Common database connection methods include local connection and remote connection. The choice of connection method depends on the deployment environment of the tool platform and the database. The tool platform can achieve compatibility with different types of databases (such as SQL Server, Oracle, PostgreSQL, etc.) through the driver.

[0077] The tool platform loads the database driver according to the configuration file and supports connections of different database types. The target database is specified by configuring the connection parameters (such as database access address, port number, database name, etc.). It supports secure transmission protocols such as SSL encryption to ensure the security of data transmission.

[0078] To ensure that the tool platform can successfully access the database, you must configure valid database access credentials, including username and password. The configuration of access credentials needs to meet the database's authentication mechanism to ensure that only authorized tool platforms can access the database.

[0079] The tool platform reads database access credentials from configuration files or environment variables. It supports multiple authentication methods, such as basic username and password authentication, OAuth authentication, or token authentication. When connecting to a database, the tool platform matches the credential information with the database user permissions to ensure that the tool platform has the corresponding data access permissions.

[0080] In order to improve the performance and stability of database connections, you can configure a connection pool in the tool platform. The connection pool is an optimization mechanism that reduces the overhead of frequent connections and disconnections to the database by pre-establishing a set of database connections.

[0081] When the tool platform starts, it creates one or more database connection pools according to the configuration parameters. Each connection pool contains a certain number of database connections. When the tool platform needs to access the database, it obtains idle connections from the connection pool and returns them to the connection pool after use. Set the connection pool parameters, such as the maximum number of connections, the minimum number of connections, the connection timeout, etc., to ensure efficient use of database connections.

[0082] The data transmission between the tool platform and the database needs to adopt a unified format and protocol. The tool platform usually supports multiple data formats (such as JSON, XML, CSV, etc.) and different data transmission protocols (such as JDBC, ODBC, etc.).

[0083] Specify the format type and encoding rules for data transmission in the tool platform to ensure that the transmitted data conforms to the storage format of the database. The tool platform transmits data to the database according to the specified protocol through the driver or API interface. If the database supports encrypted transmission protocols (such as TLS / SSL), the tool platform can configure encryption options to ensure the security of data transmission.

[0084] After the configuration is complete, the availability of the database connection needs to be tested to ensure that the tool platform can access the database normally. The test content usually includes connection establishment, identity authentication, data reading and writing, etc.

[0085] The tool platform verifies the connection status of the database by sending a test connection request. When testing the connection, the tool platform attempts to execute a simple SQL query (such as a SELECT statement) to verify the accessibility of the database. If the test connection fails, the tool platform returns an error message, indicating a configuration problem with the connection parameters or access credentials.

[0086] Example description: In the field of healthcare, hospital information systems usually store a large amount of patient data and medical records. In order to ensure the safe storage and management of this data, hospitals can establish a secure connection between the tool platform and the database. For example, the hospital can store the patient's medical record scan results in the database and manage this data through the tool platform. When configuring the connection between the tool platform and the database, you can choose to use the SSL encrypted transmission protocol to ensure that the patient's privacy data will not be leaked during transmission. In addition, the tool platform can also configure a connection pool mechanism to improve the system's database access efficiency in high-concurrency access scenarios, ensuring that doctors and managers can quickly access patient information.

[0087] In the financial field, the information systems of banks, insurance companies and other institutions usually need to manage a large amount of customer data and transaction records. In order to ensure the safe storage and compliance management of this data, financial institutions can establish a secure connection between the tool platform and the database. For example, in the loan approval system, the tool platform needs to store the customer's loan application records, credit assessment results and other data in the database. When configuring the connection between the tool platform and the database, you can set up a multi-authentication mechanism to ensure that only authorized tool platforms can access the database. In addition, by configuring the connection pool management mechanism, banks can effectively reduce frequent database connection operations, improve the system's response speed, and ensure timely processing of customer information. At the same time, by testing and verifying the connection status, banks can promptly discover and solve database connection problems to ensure system stability and data security.

[0088] By configuring the connection between the tool platform and the database, the tool platform can efficiently access and manage the database, so that the code retrieval results can be persistently stored in the database and can be used for subsequent queries and analysis. By setting up connection pool management and secure transmission protocols, the performance and security of database connections are improved, avoiding the problem of system performance degradation caused by frequent connections and disconnections to the database. At the same time, by testing the availability of the connection, it is ensured that the tool platform can stably access the database in different network environments, improving the reliability and availability of the system.

[0089] S50, build automation scripts or configure task scheduling tools;

[0090] In this embodiment, the first task of building an automation script or task scheduling tool is to determine its execution target, including the code base that the automation task needs to process, the calling process of the custom plug-in, and the data upload process. The execution target usually covers functions such as access to the target code base, line-by-line scanning, keyword matching, and result upload.

[0091] Confirm the triggering conditions of the automated task, such as scheduled execution, triggering when the code base changes, or manual execution. Clarify the name, parameters, and data processing logic of the custom plug-in to be called. Define the input and output content of the automated task, such as the target code base path, the storage location of the scan results, etc.

[0092] The choice of automation script or task scheduling tool depends on the deployment environment and technology stack. Common scripting languages ​​include Shell, Python, etc., and common task scheduling tools include Cron, Jenkins, etc. Choosing the right tool can improve the efficiency and reliability of task execution.

[0093] In Linux environments, you can use Shell scripts and Cron to schedule tasks. In Windows environments, you can use Batch scripts or PowerShell combined with Windows Task Scheduler. In complex project environments, you can use CI / CD tools such as Jenkins to achieve visual management of task scheduling.

[0094] The automated script needs to pull or update the target code repository to ensure that the latest version of the code file is used during scanning. Common code repository management tools include Git, SVN, etc.

[0095] Use Git commands such as git clone or git pull to pull or update the target code base. Set the access path, authentication information and other parameters of the code base in the script. You can set multiple code base paths to achieve batch scanning capabilities.

[0096] In the automation script, you need to configure the execution process of the task, including the call of custom plug-ins, the processing of scan results, and the data upload operation. The configuration of the execution process needs to consider the order of tasks and the exception handling mechanism.

[0097] Call custom plug-ins in automation scripts and pass necessary parameters, such as target code library path, keyword list, etc. Call plug-ins to scan code files one by one through loops or batch processing. Configure exception handling mechanisms to record error logs or trigger retry operations when task execution fails.

[0098] Task scheduling tools usually support execution strategies such as scheduled tasks, periodic tasks, and event-triggered tasks. By setting execution strategies, you can achieve on-demand execution of automated tasks and reduce manual intervention.

[0099] Configure the execution time and frequency of the task in the task scheduling tool, such as daily, weekly, or every time the code base is updated. Set the priority and concurrency of the task to ensure that the task can be executed as planned. If the task needs to be executed across multiple servers, you can configure a distributed task scheduling tool such as Kubernetes CronJob.

[0100] Example description: In the field of healthcare, the hospital's information system usually contains a large amount of patient information and medical data. In order to ensure that the system code does not contain sensitive data or illegal data calls, the hospital can build an automated script or configure a task scheduling tool to regularly scan and analyze the code base. For example, the hospital's technical department can write an automated script to pull the latest code file of the medical record management system and call a custom plug-in to scan for sensitive information such as patient names, ID numbers, and diagnosis results. Use the task scheduling tool to set it to execute once a day to ensure that sensitive data is automatically detected after each system update, effectively reducing the risk of patient privacy data leakage.

[0101] In the financial sector, banks and insurance companies need to perform sensitive information detection on the code base of information systems to identify whether the code contains sensitive fields such as customer bank card numbers, account balances, and transaction records. In order to achieve automated detection, financial institutions can build automated scripts and task scheduling tools to scan the code base regularly. For example, the technical department of a bank can use Jenkins to configure automated tasks, build automated scripts to access the code base of the loan approval system, and call custom plug-ins to scan for unencrypted customer information fields. By setting the execution strategy of the task scheduling tool, the scanning task is automatically executed after each system update to ensure the security of customer information and the compliance of the system.

[0102] By building automated scripts or configuring task scheduling tools, we can achieve automated access to the target code base and automated management of keyword search tasks. The construction of automated tasks reduces the need for manual intervention and improves the efficiency and accuracy of code retrieval. At the same time, by configuring the execution strategy of the task scheduling tool, we can ensure the regular execution and exception handling capabilities of keyword search tasks, reduce the risk of task execution failure, and improve the stability and reliability of the system.

[0103] S60, calling the custom plug-in to scan the target code library through the automation script or task scheduling tool to identify the code fragment containing the target keyword;

[0104] In this embodiment, the automated script or task scheduling tool is responsible for calling the custom plug-in to scan the target code library. During the calling process, the access configuration of the target code library and the calling parameters of the custom plug-in need to be loaded. These configurations and parameters ensure that the tool can access the target code library normally and perform the scanning task according to the preset keyword matching logic.

[0105] Load the target code repository's access path, authentication information, branch name, and other configurations in the automation script. Set the custom plug-in's calling parameters, including keyword lists, scan scopes, and scan policies. Confirm that the script or scheduling tool can successfully access the target code repository and correctly load the custom plug-in.

[0106] The automated script or task scheduling tool extracts code files from the target code library and preprocesses the extracted code files. The preprocessing includes removing comments, filtering blank lines, identifying file types, etc., to improve scanning efficiency and accuracy.

[0107] Call Git, SVN and other code management tools to pull the latest code files from the target code repository. Classify code files according to file types (such as .java, .py, .sql, etc.). Remove invalid content in code files, such as comments, blank lines, etc., to reduce the scanning scope and improve the accuracy of keyword matching.

[0108] The custom plug-in is called through an automated script or task scheduling tool to scan the extracted code files line by line. In each line of code, the plug-in will match the preset keyword list and identify the code snippets containing the target keywords.

[0109] Call the main class method of the custom plug-in to read the code file line by line. The plug-in matches keywords for each line of code according to the preset keyword matching strategy. If the target keyword is matched, the corresponding code snippet is marked as a snippet containing the target keyword.

[0110] When a code snippet containing a target keyword is matched, the automated script or task scheduling tool generates a target keyword data structure. The target keyword data structure usually includes information such as file path, line number, context content, etc., which is convenient for subsequent storage and display.

[0111] Define the format of the target keyword data structure in the automation script, such as JSON, XML, etc. When the plug-in matches the keyword, it fills the file path, line number, and context into the data structure. The generated target keyword data structure will be uploaded to the tool platform and database in subsequent steps.

[0112] Example description: In the field of healthcare, hospital information systems usually contain a large amount of patient data and medical records. To ensure that this data is not exposed in plain text in the code, the hospital technology department can call custom plug-ins through automated scripts to scan the code base line by line. For example, the hospital technology department can pull the code file of the electronic medical record system through an automated script and call a custom plug-in to scan for sensitive information fields such as patient name, ID number, diagnosis results, etc. When the plug-in matches sensitive information, it will generate a target keyword data structure containing the file path, line number, and context content, and upload it to the tool platform for security managers to analyze.

[0113] In the financial sector, banks and insurance companies need to perform sensitive information detection on the code base in the information system to identify whether the code contains sensitive fields such as customer bank card numbers, account balances, and transaction records. In order to achieve automated detection, financial institutions can call custom plug-ins through task scheduling tools to scan sensitive information in the code base. For example, the technical department of a bank configures automated tasks through Jenkins, and regularly calls custom plug-ins to scan the code base of the loan approval system to identify whether there are unencrypted customer information fields. When the plug-in matches the key fields, it generates the target keyword data structure and uploads it to the tool platform for analysis and processing by the risk management department, improving the security and compliance of the system.

[0114] By calling custom plug-ins through automated scripts or task scheduling tools, automated scanning and keyword matching operations on the target code base are realized. Compared with traditional manual retrieval methods, automated scanning reduces the workload of manual operations and improves the efficiency and accuracy of code keyword retrieval. At the same time, by scanning line by line, it can ensure full coverage of the code base and avoid the risk of missing key code fragments. The generated target keyword data structure provides a complete and accurate data foundation for subsequent storage, display and analysis, improving the system's management capabilities and information security.

[0115] S70, extracting target keyword information from the code snippet, and uploading the target keyword information to the database and the tool platform.

[0116] In this embodiment, the code snippet identified from the code scanning task generally contains the target keyword and its file path, line number and context information. The process of extracting the target keyword information includes structured parsing of the code snippet, extracting the code line containing the target keyword and its related metadata, and forming target keyword data for subsequent storage and display.

[0117] Call the parsing method of the custom plug-in to analyze the code snippet containing the target keyword. Extract key information such as file path, line number, context content of the target keyword, etc. Structuralize the extracted key information according to the preset data format (such as JSON, XML, etc.) to generate the target keyword data structure.

[0118] The extracted target keyword information needs to be formatted according to the storage and display requirements of the database and tool platform to ensure that the data can be correctly identified and stored. The formatting content includes data encoding method, field naming rules, adding timestamps, etc.

[0119] Confirm the format requirements of the database and tool platform for data, such as field name, data type, maximum length, etc. Encode and convert the target keyword information to ensure the compatibility of data between different systems. Add metadata such as timestamps and unique identifiers to facilitate subsequent data management and retrieval.

[0120] In order to upload the target keyword information to the database, the tool platform needs to establish a connection session with the database first. The establishment of a connection session usually includes steps such as identity authentication and connection pool management to ensure the stability and security of the data upload process.

[0121] Call the database driver in the tool platform to establish a connection with the database. Perform identity authentication to ensure that the tool platform has the authority to upload data. If the database supports the connection pool mechanism, you can configure the connection pool parameters to improve the efficiency of data upload.

[0122] The process of uploading the target keyword information to the database includes data insertion and update operations. When uploading, you need to select the appropriate database table and insert the corresponding field value according to the data structure. If the target keyword information already exists, perform the update operation.

[0123] Create a table structure in the database to store the target keyword information, including field names, data types, etc. Call the insert or update operation to upload the target keyword information to the database table. After the upload is completed, return the upload results, such as the number of successfully inserted records, failure reasons, etc.

[0124] In addition to uploading to the database, the target keyword information also needs to be uploaded to the tool platform through the tool platform interface to achieve data visualization and management. The tool platform usually provides a RESTful API or plug-in management interface for external system calls.

[0125] Call the tool platform's API interface to pass the formatted data of the target keyword information. If the tool platform supports batch upload, multiple target keyword information can be uploaded at once to reduce the number of interface calls. Confirm whether the uploaded target keyword information is displayed correctly in the tool platform's management interface.

[0126] Example: In the field of healthcare, the hospital's information system contains a large amount of patient data and medical records. In order to ensure the security of this data, the hospital's technical department can use automated tools to scan the code base, identify code snippets containing patient information, and extract target keyword information (such as patient name, ID number, medical record number, etc.). For example, the hospital's technical department can upload the extracted target keyword information to the database to generate a sensitive information retrieval report. At the same time, the target keyword information is displayed through the visual interface of the tool platform, which facilitates information security personnel to quickly analyze and process sensitive data, thereby avoiding the leakage of patient privacy information.

[0127] In the financial sector, banks and insurance companies need to scan code bases regularly to identify sensitive fields that may lead to customer information leakage (such as bank card numbers, account balances, transaction records, etc.). The technical department can extract target keyword information through automated tools and upload it to the database and tool platform. For example, the technical department of a bank can upload the identified code snippets containing sensitive information to the database for analysis by the risk management department. At the same time, the target keyword information, such as file path, line number, and context content, is displayed in the visual interface of the tool platform, which makes it easier for technicians to quickly locate the problem code and repair it, thereby improving the security and compliance of the system.

[0128] By extracting target keyword information from code snippets and uploading it to the database and tool platform, persistent storage and visual display of code retrieval results are achieved. The formatting of target keyword information ensures the compatibility of data between different systems and improves the stability and accuracy of data upload. The automated target keyword information upload process reduces the risk of manual operation and improves data management efficiency. At the same time, real-time data upload and display are achieved through the interface of the tool platform, making it easy for users to quickly view and analyze retrieval results.

[0129] The present invention relates to the field of R&D management technology, and can be applied to business scenarios such as financial technology and medical health. A method for automatic retrieval of code keywords is disclosed, including: deploying a tool platform and completing initialization configuration, developing a custom plug-in for identifying code keywords, deploying and loading the custom plug-in, configuring the connection between the tool platform and the database, writing an automated script or task scheduling tool, calling the custom plug-in to scan the target code library, identifying code snippets containing target keywords, extracting target keyword information from the code snippets, and uploading them to the database and tool platform. The present invention realizes the automatic extraction and management of target keyword information in a large-scale code library by scanning the target code library, avoiding the inefficiency and inaccuracy of manual retrieval; by uploading the target keyword information to the database and tool platform, the persistent storage and real-time display of the retrieval results are realized, effectively improving the efficiency and accuracy of code retrieval.

[0130] In one embodiment, the above S20 includes:

[0131] S201, based on the interface provided by the tool platform, obtaining the interface method and API document required for the development of the custom plug-in;

[0132] S202, creating a development environment for the custom plug-in based on the interface method and API document, and initializing core components of the custom plug-in;

[0133] S203, in the custom plug-in, based on the interface method and API document, developing a target keyword recognition module for line-by-line scanning and target keyword matching;

[0134] S204, in the custom plug-in, based on the interface method and API document, design an output structure for generating target keyword information including file path, line number and context content.

[0135] In this embodiment, the tool platform usually provides a developer interface and API documents for users to develop custom plug-ins. These interface methods and API documents contain detailed information such as the rules, data format, and calling methods for the interaction between the plug-in and the tool platform. By obtaining these documents and methods, it can be ensured that the development of custom plug-ins complies with the technical specifications of the tool platform.

[0136] Log in to the developer portal or management page of the tool platform and download the API documentation for plug-in development. Read and analyze the interface methods in the API documentation to clarify the rules and requirements for plug-in loading, calling, and data transmission. Record commonly used interface methods and their parameter descriptions, and create template codes for interface calls.

[0137] In order to develop custom plug-ins, you need to build a development environment that meets the technical requirements of the tool platform. The development environment usually includes a code editor, compilation tools, debugging tools, etc. The core component is the key part of the plug-in, responsible for handling line-by-line scanning and keyword matching tasks of the target code library.

[0138] Select the appropriate development language (such as Java, Python, etc.) and development tools (such as IDE). Download the SDK or plug-in template of the tool platform and import it into the development environment. Initialize the core components of the custom plug-in, including the main class of the plug-in, data processing class, logging class, etc. Configure the plug-in metadata file, including the name, version, description, and other information of the plug-in.

[0139] The target keyword recognition module is the core functional module of the custom plug-in, which is responsible for identifying the target keyword from the code lines of the target code library and generating keyword matching results. The recognition module usually includes string matching algorithms, regular expression matching, data filtering and other functions.

[0140] Define the interface methods of the target keyword recognition module, including line-by-line reading of code files and keyword matching logic. Write string matching algorithms or regular expression matching algorithms to support recognition of multiple keyword formats. Set keyword filtering rules in the recognition module to avoid misidentification of common code comments, blank lines and other invalid information. Use the logging function to track matching conditions and abnormal information during the recognition process.

[0141] The output structure of the target keyword information contains the meta information of the code snippet, such as file path, line number, context content, etc. This information needs to be output in a structured form to facilitate subsequent storage and display.

[0142] Define the output data structure of the target keyword information and select the appropriate format (such as JSON, XML). Design the field names of the data structure, including file path, line number, keyword content, and previous and next context information. Implement the serialization and deserialization functions of the data structure to ensure that the data remains consistent during transmission and storage. Add metadata to the output structure, such as timestamps, unique identifiers, etc., to facilitate data management and tracking.

[0143] This embodiment ensures the functional integrity of the custom plug-in and its compatibility with the tool platform by obtaining interface methods and API documents, creating a development environment, developing a target keyword recognition module, and designing an output structure. The target keyword recognition module can efficiently identify keyword information in the target code library and generate target keyword data containing file paths, line numbers, and context content, which is convenient for subsequent storage and display operations.

[0144] In one embodiment, the above S30 includes:

[0145] S301, packaging the custom plug-in into a plug-in file format that meets the requirements of the tool platform;

[0146] S302, copying the packaged custom plug-in to the plug-in directory of the tool platform;

[0147] S303, executing a loading operation of the custom plug-in through a management interface provided by the tool platform;

[0148] S304, querying the loading log information of the custom plug-in through the management interface provided by the tool platform to obtain the loading status of the custom plug-in;

[0149] S305: Perform a normal activation check or a restart operation in an abnormal situation according to the loading status of the custom plug-in.

[0150] In this embodiment, before deploying the custom plug-in, it needs to be packaged into a plug-in file format that meets the requirements of the tool platform. The tool platform usually requires the plug-in to be packaged in a specific format (such as JAR, ZIP, etc.) to ensure the integrity, compatibility and manageability of the plug-in.

[0151] In the development environment, use build tools (such as Maven, Gradle, etc.) to package the source code, configuration files, resource files, etc. of the plug-in into one file. The necessary metadata information, such as the plug-in name, version number, description, etc., must be included in the package so that the tool platform can identify and load the plug-in. Confirm that the packaged plug-in file conforms to the format specification of the tool platform to avoid loading failures due to incorrect format.

[0152] The tool platform usually provides a plug-in directory for storing all deployed plug-in files. Copying custom plug-in files to the plug-in directory is a key step in the deployment process. The tool platform automatically identifies the plug-in files in the directory and tries to load them.

[0153] Confirm the path of the plugin directory in the tool platform's configuration file. Use a file transfer tool (such as FTP, SCP, etc.) or an automated script to copy the packaged plugin files to the specified plugin directory. If the tool platform supports remote upload of plugin files, you can also upload plugins through the management interface.

[0154] After the plug-in file is copied to the plug-in directory, you need to load the plug-in through the management interface of the tool platform. The loading operation triggers the plug-in management function of the tool platform to verify the integrity, version number and dependencies of the plug-in.

[0155] Log in to the management interface of the tool platform, enter the plug-in management page, and perform the "load" or "enable" operation. If the tool platform provides an API interface, you can call the plug-in loading interface through an automated script to avoid manual operation. During the loading process, the tool platform will verify the metadata information of the plug-in, such as the plug-in description file, version number, etc.

[0156] After the plugin is loaded, you need to query the loading log information of the tool platform to confirm whether the plugin is loaded normally. The loading log usually records the loading time, loading results, error information, etc. of the plugin.

[0157] In the management interface of the tool platform, enter the system log or plug-in management page to query the plug-in loading log information. If the tool platform supports the API interface, you can query the plug-in loading status through the interface and return the loading result. According to the log information, confirm whether the plug-in loading status is "successful" and whether there is any error information.

[0158] Depending on the loading status of the plug-in, decide whether to enable or restart the plug-in. If the plug-in is loaded successfully, you need to perform a normal enablement check to ensure that the plug-in functions normally. If the plug-in fails to load or is abnormal, you need to restart it to try to fix the problem.

[0159] When the plugin is loaded successfully, perform functional testing to verify whether the main functions of the plugin are running normally. If loading fails, locate the problem and try to fix it by analyzing the error information in the loading log. When loading fails or is abnormal, you can restart the plugin through the management interface or API interface of the tool platform, clean the plugin cache and reload the plugin.

[0160] This embodiment expands the functionality of the tool platform by deploying a custom plug-in to the plug-in directory of the tool platform and executing the plug-in loading operation, enabling the tool platform to identify and process target keyword information. By querying the plug-in loading log and performing normal activation checks, the loading status of the plug-in is ensured to be normal, thereby improving the stability and availability of the system. For the restart operation under abnormal circumstances, an effective error repair mechanism is provided, which reduces the system failure time and ensures the normal operation of the system.

[0161] In one embodiment, the above S40 includes:

[0162] S401, selecting a database connection setting option through the configuration management page of the tool platform;

[0163] S402, in the database connection setting option, input the database access address, port number and database name, and configure the authentication information of the database;

[0164] S403, testing the connection status between the tool platform and the database, and judging whether the database is connected normally according to the test result;

[0165] S404: When the test result shows that the database is normally connected, save the database connection configuration of the tool platform.

[0166] In this embodiment, in order to effectively connect the tool platform to the database, it is first necessary to select the database connection setting option in the configuration management page of the tool platform. This step is used to start the database configuration process and guide the user to enter the necessary connection information.

[0167] Log in to the tool platform's management interface and find the "System Configuration" or "Database Settings" page. In the "Database Settings" page, select the "Add Connection" or "Configure Connection" option to start configuring a new database connection. If the tool platform supports multiple database types, select the target database type (such as PostgreSQL, SQL Server, Oracle, etc.).

[0168] In the database connection settings page, you need to enter the database access address (IP address or domain name), port number, database name and other connection parameters. At the same time, you also need to configure the database authentication information, including user name and password, to ensure that the tool platform can access the database through authentication.

[0169] Enter the database access address to ensure that the address can be accessed by the tool platform. Enter the database port number, which is usually the default port number of the database (such as 5432 for PostgreSQL and 1433 for SQL Server). Specify the name of the target database to ensure that the tool platform can access the correct database instance. Configure the database authentication information, including the user name and password, to ensure that the tool platform has sufficient permissions to access the database. For databases that support advanced authentication methods, you can also configure multi-factor authentication or token authentication.

[0170] After completing the configuration of the database connection parameters, you need to test the connection status between the tool platform and the database to verify whether the entered connection information is correct and whether the tool platform can successfully access the database.

[0171] Click the "Test Connection" button on the tool platform's configuration page to trigger the database connection test operation. The tool platform attempts to establish a connection with the target database through a network request and performs identity authentication. If the connection is successful, the tool platform returns a "Connection Successful" message; if the connection fails, the tool platform returns an error message (such as "Access Timeout" or "Authentication Failed"). Based on the test results, determine whether the connection is normal. If the connection fails, check whether the access address, port number, user name, password and other information are correct.

[0172] When the test results show that the database is connected normally, you need to save the configured database connection information to the configuration file of the tool platform so that the tool platform can use the connection in subsequent operations.

[0173] Click the "Save Configuration" button on the tool platform configuration page to save the database connection information to the tool platform configuration file or database. Make sure the saved connection information includes necessary parameters such as access address, port number, database name, user name and password. When the tool platform is restarted or executes related tasks, it can automatically load the saved database connection configuration to ensure the continued validity of the connection.

[0174] This embodiment realizes effective access to the database by configuring the connection between the tool platform and the database, providing a basis for the subsequent storage and analysis of code retrieval results. The connection test between the tool platform and the database ensures the correctness and reliability of the connection information and avoids database access failures caused by configuration errors. At the same time, by saving the database connection configuration, the tool platform can automatically load the configured database connection in subsequent operations, reducing the workload of repeated configuration and improving the stability and operation efficiency of the system.

[0175] In one embodiment, the above S60 includes:

[0176] S601, starting the automation script or task scheduling tool to load the access configuration of the target code library and the calling parameters of the custom plug-in;

[0177] S602, extracting the latest code files from the target code library according to the access configuration of the loaded target code library, and classifying and arranging the latest code files according to a preset scanning strategy;

[0178] S603, calling the custom plug-in according to the calling parameters of the loaded custom plug-in, parsing the codes in the classified and sorted code files, and matching the target keyword in each line of code;

[0179] S604: When a code snippet containing a target keyword is matched, target keyword information including a file path, a line number, and context information is generated.

[0180] In this embodiment, the start of the scanning task is the start of the automated script or task scheduling tool. Before the task is executed, the access configuration of the target code library (such as access address, branch information, authentication information, etc.) and the calling parameters of the custom plug-in (such as keyword list, matching rules, output format, etc.) need to be loaded to ensure that the tool can normally access the code library and call the plug-in for scanning.

[0181] Write automation scripts or configure the execution process of task scheduling tools, including the loading process of code repository access configuration. Configure the triggering conditions of automation tasks, such as execution at time intervals (Cron tasks), triggering when the code repository is updated (Webhook), or manual execution. The automation script passes the path of the target code repository, the calling parameters of the custom plug-in (such as keyword list, scanning range, etc.), and the output directory through parameters.

[0182] In order to ensure that the latest version of the code file is used during scanning, the code files need to be extracted from the target code library according to the access configuration and classified and organized according to the preset scanning strategy. The scanning strategy can include classification by file type, folder path, file size and other rules to improve scanning efficiency.

[0183] Call Git, SVN and other code management tools to pull the latest version of the code file from the target code repository. Classify the pulled code files according to the scanning strategy, for example, classify .java files as Java code, and classify .py files as Python code. The scanning strategy can include filtering rules, such as ignoring specific types of files (such as log files, temporary files) or excluding specific directories. The sorted code files are stored in the specified temporary directory by category for the custom plug-in to scan one by one.

[0184] The custom plug-in is responsible for parsing the code file line by line and performing the target keyword matching operation in each line of code. The calling parameters of the plug-in determine the matching keywords, matching methods (such as exact matching, fuzzy matching, regular expression matching, etc.) and the format of the output target keyword information.

[0185] The automated script or task scheduling tool calls the main method of the custom plug-in and passes the parameters of the scanning task. The custom plug-in reads the content of the code file line by line and parses the structure of each line of code (such as comments, function definitions, variable declarations, etc.). According to the keyword matching rules, the target keyword matching operation is performed in each line of code. The matching method can include regular expression matching, string inclusion matching, prefix and suffix matching, and other methods.

[0186] When the custom plug-in matches a code snippet containing a target keyword, a data structure of the target keyword information needs to be generated. This data structure contains the file path, line number, and surrounding context of the target keyword, which is convenient for subsequent storage, analysis, and display.

[0187] Define the data structure format (such as JSON, XML, etc.) of the target keyword information in the plug-in. When the target keyword is matched, extract the file path, line number, context content of the previous and next lines of the code snippet, and other information. Instantiate the data structure of the target keyword information and store it in memory or intermediate result files in a preset format. The target keyword information can contain metadata, such as timestamp, plug-in version number, matching rules, etc., to facilitate data management and traceability.

[0188] This embodiment calls a custom plug-in through an automated script or task scheduling tool to achieve automated scanning of the target code library and efficient matching of target keywords. The automated scanning process reduces the workload of manual operations and improves the efficiency and accuracy of code keyword recognition. Scanning code files line by line ensures that the scanning task fully covers the code library and avoids the risk of missing key code fragments. At the same time, the generated target keyword information data structure provides standardized basic data for subsequent storage, analysis, and display, improving the system's data management capabilities and security.

[0189] In one embodiment, the above S70 includes:

[0190] S701, parsing the identified code snippet, extracting the code content containing the target keyword, and generating the target keyword information according to a preset data structure;

[0191] S702, formatting the generated target keyword information to meet the storage and display requirements of the database and the tool platform;

[0192] S703, establishing a connection session with the database, and uploading the target keyword information to the database;

[0193] S704: Upload the target keyword information to the tool platform through the interface of the tool platform.

[0194] In this embodiment, parsing code snippets is the core step of extracting target keyword information. After scanning the code base line by line, the code snippets containing the target keyword are identified. During the parsing process, it is necessary to extract relevant code content, such as file path, line number, and context information, and generate target keyword information according to a preset data structure (such as JSON, XML, etc.) for subsequent storage and display.

[0195] Call the parsing method of the custom plug-in to decompose the identified code snippet. Extract the file path, line number, matched keywords and their context. Define the data structure of the target keyword information, including field name and data type, to ensure that the data format is unified and parsable. Fill the parsed target keyword information into the data structure to form a standardized data output format.

[0196] The generated target keyword information needs to be formatted according to the storage and display requirements of the database and tool platform. This includes steps such as encoding conversion, field mapping, and data validation to ensure the compatibility and consistency of data between different systems.

[0197] Confirm the specific requirements of the database and tool platform for data format, such as field length, data type, encoding method, etc. Convert the target keyword information into a format, such as converting text encoding to UTF-8 and date format to a standard timestamp. Verify the data integrity and legality of the target keyword information to ensure that the field value is within the expected range. Add necessary metadata, such as timestamp, plug-in version number, matching rule identifier, etc., to facilitate subsequent management and tracing.

[0198] Before uploading the target keyword information to the database, a stable connection session needs to be established. The connection session includes processes such as identity authentication, permission checking, and connection pool management to ensure that the tool platform can access the database efficiently and securely.

[0199] Call the database driver to initialize the database connection configuration, including parameters such as access address, port number, and database name. Perform identity authentication to ensure that the tool platform has the authority to upload data. Establish a database connection session to support batch data insertion or update operations. Execute insert or update statements to upload the formatted target keyword information to the specified database table. After the upload is completed, close the connection session to release database resources.

[0200] In addition to uploading to the database, the target keyword information also needs to be uploaded to the tool platform to achieve data visualization and management. The tool platform usually provides a RESTful API or plug-in management interface for external system calls.

[0201] Call the API interface of the tool platform to pass the formatted data of the target keyword information. Set the authentication information of the interface, such as API key or OAuth token, to ensure the security of the interface call. Support batch uploading of target keyword information, reduce the number of interface calls, and improve data upload efficiency. Check the response result returned by the interface to confirm whether the target keyword information is successfully uploaded to the tool platform. In the visualization page of the tool platform, verify whether the uploaded data is displayed correctly, and perform necessary debugging and optimization.

[0202] This embodiment realizes the standardized storage and visual display of code retrieval results by extracting target keyword information from code snippets and uploading it to the database and tool platform. The data formatting process ensures the compatibility between the database and the tool platform and reduces the risk of data transmission errors. By establishing a database connection session and calling the interface of the tool platform, the upload process of the target keyword information is automatically completed, which improves the data management efficiency and information security protection capabilities of the system. At the same time, the upload of target keyword information provides a data basis for subsequent data analysis, retrieval optimization and visual display.

[0203] In one embodiment, after the above S70, the method further includes:

[0204] S801, loading a display page of the target keyword information through a visual interface of the tool platform;

[0205] S802, in the display page, filtering the target keyword information according to the filtering condition to obtain filtered target keyword information;

[0206] S803, displaying the filtered target keyword information in the display page according to a preset display format, and performing data annotation processing on the displayed target keyword information;

[0207] S804, writing the target keyword information after the data annotation processing into the database.

[0208] In this embodiment, after the target keyword information is uploaded to the tool platform, a display page needs to be loaded through the visual interface of the tool platform. The display page is the main way for users to view and analyze the target keyword information, and can intuitively present the code search results.

[0209] Access the target keyword information display module in the management interface of the tool platform. Call the display page loading interface to import the uploaded target keyword information into the page. When loading the display page, you can preload basic filtering conditions, such as time range, keyword type, etc., to improve the user experience. Ensure that the display page supports dynamic loading and can display the latest target keyword information in real time.

[0210] The display page usually provides a filtering function, allowing users to filter the target keyword information according to different conditions. The filtering conditions can include file path, keyword type, matching line number, etc. The filtered results are used to accurately analyze and locate the target keyword.

[0211] An input box or drop-down menu for filtering conditions is provided on the display page, and the user can select or enter filtering conditions. According to the filtering conditions selected by the user, the filtering processing module is called to filter the target keyword information. The filtering conditions can support single condition or multi-condition combination filtering to improve the accuracy of the filtering results. The filtered target keyword information is displayed on the page in the form of a list or chart.

[0212] The filtered target keyword information needs to be displayed in a preset display format, and data annotation processing is supported. Data annotation processing refers to operations such as supplementing descriptions of target keyword information and marking risk levels on the display page.

[0213] On the display page, the target keyword information is displayed in the preset display format. The display format may include list view, card view, chart view, etc. A labeling option is provided next to the displayed target keyword information, and the user can label the information. The labeling content may include remarks, risk level, problem description, etc. Data labeling processing can support batch operations to improve labeling efficiency. The labeled target keyword information needs to be saved to a temporary cache in real time to ensure that the user's labeling operation is not lost.

[0214] The target keyword information after data annotation needs to be persistently stored in the database to ensure that the user's annotation operations are saved for subsequent query, analysis and management.

[0215] The function of saving data annotation processing results is implemented in the background logic of the tool platform. Call the database insert or update interface to write the target keyword information after data annotation processing into the specified database table. When writing data, the original content of the target keyword information and the user's annotation content must be included to ensure the integrity of the data. After the data is written, the writing result is returned to prompt the user that the annotation operation has been successfully saved.

[0216] This embodiment loads the display page of the target keyword information through the visual interface of the tool platform, and filters and annotates the target keyword information, thereby realizing accurate analysis and management of the code retrieval results. The filtering function of the display page can help users quickly locate key code snippets and improve the efficiency of information retrieval. The data annotation processing function provides support for further management of information, allowing users to perform supplementary operations such as risk assessment and problem description on the target keyword information. The target keyword information after data annotation processing is written into the database, realizing persistent storage of information, ensuring that the user's annotation operations are completely saved, and providing a data basis for subsequent data query and analysis.

[0217] In one embodiment, a code keyword automatic retrieval device is provided, and the code keyword automatic retrieval device corresponds one-to-one to the code keyword automatic retrieval method in the above embodiment. Figure 3 , Figure 3 This is a functional module diagram of a preferred embodiment of the automatic code keyword retrieval device of the present invention. Tool platform management module 10, plug-in development module 20, plug-in deployment and loading module 30, database connection configuration module 40, automatic task management module 50, code scanning and matching module 60 and data extraction and upload module 70. The functional modules are described in detail as follows:

[0218] The tool platform management module 10 is used to deploy a tool platform for code analysis and processing and complete the initialization configuration of the tool platform;

[0219] A plug-in development module 20, used to develop a custom plug-in for identifying code keywords based on an interface provided by the tool platform;

[0220] A plug-in deployment and loading module 30, used to deploy the custom plug-in to the plug-in directory of the tool platform and load the custom plug-in;

[0221] A database connection configuration module 40, used to configure the connection between the tool platform and the database;

[0222] The automated task management module 50 is used to build automated scripts or configure task scheduling tools;

[0223] A code scanning and matching module 60 is used to call the custom plug-in to scan the target code library through the automation script or task scheduling tool to identify the code fragment containing the target keyword;

[0224] The data extraction and uploading module 70 is used to extract target keyword information from the code snippet and upload the target keyword information to the database and the tool platform.

[0225] In one embodiment, the plug-in development module 20 is specifically used to:

[0226] Based on the interface provided by the tool platform, obtain the interface method and API document required for the development of custom plug-ins;

[0227] Based on the interface method and API document, create a development environment for the custom plug-in and initialize the core components of the custom plug-in;

[0228] In the custom plug-in, based on the interface method and API document, a target keyword recognition module for line-by-line scanning and target keyword matching is developed;

[0229] In the custom plug-in, based on the interface method and API document, an output structure is designed to generate target keyword information including file path, line number and context content.

[0230] In one embodiment, the plug-in deployment and loading module 30 is specifically used to:

[0231] Packaging the custom plug-in into a plug-in file format that meets the requirements of the tool platform;

[0232] Copy the packaged custom plug-in to the plug-in directory of the tool platform;

[0233] Execute the loading operation of the custom plug-in through the management interface provided by the tool platform;

[0234] Through the management interface provided by the tool platform, query the loading log information of the custom plug-in to obtain the loading status of the custom plug-in;

[0235] According to the loading status of the custom plug-in, a normal activation check or a restart operation in an abnormal situation is performed.

[0236] In one embodiment, the database connection configuration module 40 is specifically used to:

[0237] Select a database connection setting option through the configuration management page of the tool platform;

[0238] In the database connection setting option, enter the database access address, port number and database name, and configure the authentication information of the database;

[0239] Test the connection status between the tool platform and the database, and determine whether the database is connected normally according to the test result;

[0240] When the test result shows that the database is connected normally, the database connection configuration of the tool platform is saved.

[0241] In one embodiment, the code scanning and matching module 60 is specifically used to:

[0242] Starting the automation script or task scheduling tool to load the access configuration of the target code library and the calling parameters of the custom plug-in;

[0243] Extracting the latest code files from the target code library according to the access configuration of the loaded target code library, and classifying and arranging the latest code files according to the preset scanning strategy;

[0244] Calling the custom plug-in according to the calling parameters of the loaded custom plug-in, parsing the code in the classified and sorted code files, and matching the target keyword in each line of code;

[0245] When a code snippet containing a target keyword is matched, target keyword information including file path, line number, and context information is generated.

[0246] In one embodiment, the data extraction and uploading module 70 is specifically used to:

[0247] Parse the identified code snippets, extract the code content containing the target keyword, and generate the target keyword information according to a preset data structure;

[0248] Formatting the generated target keyword information to meet the storage and display requirements of the database and the tool platform;

[0249] Establishing a connection session with the database, and uploading the target keyword information to the database;

[0250] The target keyword information is uploaded to the tool platform through the interface of the tool platform.

[0251] In one embodiment, the data extraction and uploading module 70 is specifically used to:

[0252] Loading a display page of the target keyword information through a visual interface of the tool platform;

[0253] In the display page, the target keyword information is screened according to the screening conditions to obtain the screened target keyword information;

[0254] Displaying the filtered target keyword information in the display page according to a preset display format, and performing data annotation processing on the displayed target keyword information;

[0255] The target keyword information after data annotation processing is written into the database.

[0256] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external user terminal through a network connection. When the computer program is executed by the processor, the functions or steps on the server side of a code keyword automatic retrieval method are realized.

[0257] In one embodiment, a computer device is provided. The computer device may be a user terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of a user-side method for automatic retrieval of code keywords

[0258] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0259] Deploy a tool platform for code analysis and processing, and complete initialization configuration of the tool platform;

[0260] Based on the interface provided by the tool platform, develop a custom plug-in for identifying code keywords;

[0261] Deploy the custom plug-in to the plug-in directory of the tool platform, and load the custom plug-in;

[0262] Configuring the connection between the tool platform and the database;

[0263] Build automation scripts or configure task scheduling tools;

[0264] By using the automated script or task scheduling tool, the custom plug-in is called to scan the target code library to identify code snippets containing target keywords;

[0265] Target keyword information is extracted from the code snippet, and the target keyword information is uploaded to the database and the tool platform.

[0266] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0267] Deploy a tool platform for code analysis and processing, and complete initialization configuration of the tool platform;

[0268] Based on the interface provided by the tool platform, develop a custom plug-in for identifying code keywords;

[0269] Deploy the custom plug-in to the plug-in directory of the tool platform, and load the custom plug-in;

[0270] Configuring the connection between the tool platform and the database;

[0271] Build automation scripts or configure task scheduling tools;

[0272] By using the automated script or task scheduling tool, the custom plug-in is called to scan the target code library to identify code snippets containing target keywords;

[0273] Target keyword information is extracted from the code snippet, and the target keyword information is uploaded to the database and the tool platform.

[0274] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the user side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0275] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0276] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0277] It should be noted that if software tools or components other than those of the Company appear in the embodiments of the present application, they are only used for illustration and do not represent actual use. The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the above-mentioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the above-mentioned embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A code keyword automatic retrieval method, characterized in that: The following steps are involved: Deploy a tool platform for code analysis and processing, and complete initialization configuration of the tool platform; Based on the interface provided by the tool platform, develop a custom plug-in for identifying code keywords; Deploy the custom plug-in to the plug-in directory of the tool platform, and load the custom plug-in; Configuring the connection between the tool platform and the database; Build automation scripts or configure task scheduling tools; By using the automated script or task scheduling tool, the custom plug-in is called to scan the target code library to identify code snippets containing target keywords; Target keyword information is extracted from the code snippet, and the target keyword information is uploaded to the database and the tool platform.

2. The automatic code keyword retrieval method according to claim 1, characterized in that: Based on the interface provided by the tool platform, a custom plug-in for identifying code keywords is developed, including: Based on the interface provided by the tool platform, obtain the interface method and API document required for the development of the custom plug-in; Based on the interface method and API document, create a development environment for the custom plug-in and initialize the core components of the custom plug-in; In the custom plug-in, based on the interface method and API document, a target keyword recognition module for line-by-line scanning and target keyword matching is developed; In the custom plug-in, based on the interface method and API document, an output structure is designed to generate target keyword information including file path, line number and context content.

3. The automatic code keyword retrieval method according to claim 1, characterized in that: Deploying the custom plug-in to the plug-in directory of the tool platform and loading the custom plug-in includes: Packaging the custom plug-in into a plug-in file format that meets the requirements of the tool platform; Copy the packaged custom plug-in to the plug-in directory of the tool platform; Execute the loading operation of the custom plug-in through the management interface provided by the tool platform; Through the management interface provided by the tool platform, query the loading log information of the custom plug-in to obtain the loading status of the custom plug-in; According to the loading status of the custom plug-in, a normal activation check or a restart operation in an abnormal situation is performed.

4. The automatic code keyword retrieval method according to claim 1, characterized in that: Configuring the connection between the tool platform and the database includes: Select a database connection setting option through the configuration management page of the tool platform; In the database connection setting option, enter the database access address, port number and database name, and configure the authentication information of the database; Test the connection status between the tool platform and the database, and determine whether the database is connected normally according to the test result; When the test result shows that the database is connected normally, the database connection configuration of the tool platform is saved.

5. The automatic code keyword retrieval method according to claim 1, characterized in that: The custom plug-in is called through the automation script or task scheduling tool to scan the target code library and identify the code fragments containing the target keyword, including: Starting the automation script or task scheduling tool to load the access configuration of the target code library and the calling parameters of the custom plug-in; Extracting the latest code files from the target code library according to the access configuration of the loaded target code library, and classifying and arranging the latest code files according to the preset scanning strategy; Calling the custom plug-in according to the calling parameters of the loaded custom plug-in, parsing the code in the classified and sorted code files, and matching the target keyword in each line of code; When a code snippet containing a target keyword is matched, target keyword information including file path, line number, and context information is generated.

6. The automatic code keyword retrieval method according to claim 1, characterized in that: Extracting target keyword information from the code snippet and uploading the target keyword information to the database and the tool platform includes: Parse the identified code snippets, extract the code content containing the target keyword, and generate the target keyword information according to a preset data structure; Formatting the generated target keyword information to meet the storage and display requirements of the database and the tool platform; Establishing a connection session with the database, and uploading the target keyword information to the database; The target keyword information is uploaded to the tool platform through the interface of the tool platform.

7. The automatic code keyword retrieval method according to claim 1, characterized in that: After extracting target keyword information from the code snippet and uploading the target keyword information to the database and the tool platform, the method further includes: Loading a display page of the target keyword information through a visual interface of the tool platform; In the display page, the target keyword information is screened according to the screening conditions to obtain the screened target keyword information; Displaying the filtered target keyword information in the display page according to a preset display format, and performing data annotation processing on the displayed target keyword information; The target keyword information after data annotation processing is written into the database.

8. A code keyword automatic retrieval device, characterized in that: The code keyword automatic retrieval device comprises: A tool platform management module, used to deploy a tool platform for code analysis and processing, and complete the initialization configuration of the tool platform; A plug-in development module, used to develop a custom plug-in for identifying code keywords based on an interface provided by the tool platform; A plug-in deployment and loading module, used to deploy the custom plug-in to the plug-in directory of the tool platform and load the custom plug-in; A database connection configuration module, used to configure the connection between the tool platform and the database; Automated task management module, used to build automated scripts or configure task scheduling tools; A code scanning and matching module, which is used to call the custom plug-in to scan the target code library through the automation script or task scheduling tool to identify the code fragments containing the target keyword; The data extraction and uploading module is used to extract target keyword information from the code snippet and upload the target keyword information to the database and the tool platform.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a code keyword automatic retrieval program stored in the memory and executable on the processor. When the code keyword automatic retrieval program is executed by the processor, the steps of the code keyword automatic retrieval method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a code keyword automatic retrieval program, and when the code keyword automatic retrieval program is executed by the processor, the steps of the code keyword automatic retrieval method according to any one of claims 1 to 7 are implemented.

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