Public component optimization method and system based on application market

Abstract

The invention discloses a public component optimization method and system based on an application market, and relates to the technical field of public component optimization, and the method comprises the steps: collecting the information of a plurality of public components in a target enterprise through registration; calling operation records of the multiple pieces of public component information, carrying out calling analysis on the multiple pieces of public component information according to the operation records, and generating a calling analysis result; establishing an examination mechanism, examining the information of the plurality of public components, and obtaining an examination result of the public components; establishing a feedback channel, synchronizing a common component review result to the feedback channel, and outputting repair feedback data; and screening the multiple pieces of public component information based on the repair feedback data, and performing quality optimization on the multiple pieces of public component information according to a screening result. The technical problems of unstable component performance, poor compatibility and the like caused by lack of deep understanding and flexible adaptation to the application market in the prior art are solved, and the technical effect of improving the component performance and the compatibility is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of public component optimization, and in particular to a public component optimization method and system based on an application market. Background Art

[0002] With the popularization of mobile Internet and the rapid iteration of smart terminal devices, the scale of the application market is expanding, providing users with a rich selection of applications and a convenient download experience. However, with the rapid development of the application market, the performance, stability and security of public components, as an important infrastructure supporting the operation of applications, are becoming increasingly prominent.

[0003] Traditional public component design and optimization methods often lack in-depth understanding of the application market and flexible adaptation, leading to problems such as unstable component performance and poor compatibility. Summary of the invention

[0004] The present application provides a method and system for optimizing common components based on an application market, which is used to solve the technical problems that the prior art lacks in-depth understanding and flexible adaptation of the application market, resulting in unstable component performance and poor compatibility.

[0005] In view of the above problems, the present application provides a method and system for optimizing common components based on an application market.

[0006] In a first aspect of the present application, a method for optimizing common components based on an application market is provided, the method comprising:

[0007] Collect multiple public component information within the target enterprise through registration; retrieve the operation records of the multiple public component information, perform call analysis on the multiple public component information according to the operation records, and generate call analysis results; establish a review mechanism based on the call analysis results, review the multiple public component information, and obtain public component review results; establish a feedback channel based on the management model of the application market, synchronize the public component review results to the feedback channel, and output repair feedback data; screen the multiple public component information based on the repair feedback data, and optimize the quality of the multiple public component information according to the screening results.

[0008] A second aspect of the present application provides a common component optimization system based on an application market, the system comprising:

[0009] A public component information collection module, wherein the public component information collection module collects multiple public component information within the target enterprise through registration; a call analysis result generation module, wherein the call analysis result generation module retrieves the operation records of the multiple public component information, performs call analysis on the multiple public component information according to the operation records, and generates call analysis results; a public component review result acquisition module, wherein the public component review result acquisition module establishes a review mechanism based on the call analysis results, reviews the multiple public component information, and obtains public component review results; a repair feedback data output module, wherein the repair feedback data output module establishes a feedback channel based on the management mode of the application market, synchronizes the public component review results to the feedback channel, and outputs repair feedback data; a quality optimization module, wherein the quality optimization module screens the multiple public component information based on the repair feedback data, and optimizes the quality of the multiple public component information according to the screening results.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] This application collects multiple public component information within the target enterprise through registration; retrieves the operation records of multiple public component information, performs call analysis on multiple public component information based on the operation records, and generates call analysis results; establishes a review mechanism based on the call analysis results, reviews multiple public component information, and obtains public component review results; establishes a feedback channel based on the management model of the application market, synchronizes the public component review results to the feedback channel, and outputs repair feedback data; screens multiple public component information based on the repair feedback data, and optimizes the quality of multiple public component information based on the screening results. The present invention solves the technical problems that the prior art lacks in-depth understanding and flexible adaptation of the application market, resulting in unstable component performance and poor compatibility. Through automated testing and continuous integration, data-driven performance analysis and optimization, the technical effect of improving component performance and compatibility is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 A schematic diagram of a common component optimization method based on an application market provided in an embodiment of the present application;

[0014] Figure 2A schematic diagram of the structure of a common component optimization system based on an application market provided in an embodiment of the present application.

[0015] Explanation of the accompanying drawings: common component information collection module 11, call analysis result generation module 12, common component review result acquisition module 13, repair feedback data output module 14, quality optimization module 15. DETAILED DESCRIPTION

[0016] This application provides a public component optimization method and system based on the application market, aiming to solve the technical problem that the existing technology lacks in-depth understanding and flexible adaptation of the application market, resulting in unstable component performance and poor compatibility. Through automated testing and continuous integration, data-driven performance analysis and optimization, the application achieves the technical effect of improving component performance and compatibility.

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0019] Embodiment 1

[0020] like Figure 1 As shown, the present application provides a common component optimization method based on an application market, the method comprising:

[0021] Step S100: Collecting multiple public component information within the target enterprise through registration;

[0022] In the embodiment of the present application, registration is first performed to ensure that the public component information within the target enterprise can be systematically collected and managed. When performing registration, the definition and scope of public components are clarified, and which components belong to the collection objects are determined. At the same time, a corresponding registration mechanism is established to determine the registration process, standards, and responsible persons.

[0023] Next, we will start collecting public component information and conduct a comprehensive review and scan of various systems, platforms, and applications within the enterprise. During the collection process, we will focus on multiple aspects of public component information, including but not limited to the component name, version, function description, dependency, and usage frequency. During the collection process, we will use automated scanning tools to quickly identify and extract public component information to reduce the tediousness and errors of manual operations. At the same time, we will establish a public component information library or database to uniformly store and manage the collected information. Through this process, we will complete the collection of public component information.

[0024] Step S200: Retrieving the operation records of the plurality of common component information, performing call analysis on the plurality of common component information according to the operation records, and generating a call analysis result;

[0025] In the embodiment of the present application, a connection is first established with a log system or monitoring system for calling a common component. These systems record various information of the common component during operation, such as the number of calls, call time, response time, error log, etc. The operation records of the common component are then extracted from these systems.

[0026] After obtaining the operation record data, call analysis is performed. The operation record data is counted, analyzed, and visualized to reveal the call status and usage patterns of public components. When performing call analysis, the obtained operation record data is cleaned and preprocessed to remove duplicate, invalid, or abnormal data to ensure the accuracy and consistency of the data. Then, the cleaned data is statistically analyzed to calculate indicators such as the number of calls, call frequency, and average response time of each public component. These indicators reflect the usage and performance of public components. Then, by comparing the call data of different time periods, the call trend of public components is analyzed. Determine the peak and trough periods of component use, as well as possible periodic changes. Then analyze the call relationship between different public components, determine the dependencies and associations between public components, and identify key components and potential bottlenecks. Finally, analyze the errors and abnormal information in the operation records to find out the causes of the problems and possible solutions, and locate and repair defects and vulnerabilities in public components.

[0027] Through the above steps, the call analysis results are generated.

[0028] Step S300: establishing a review mechanism based on the call analysis result, reviewing the plurality of common component information, and obtaining a common component review result;

[0029] In the embodiment of the present application, a complete review rule base is pre-built based on the performance indicators, security standards and historical call analysis data of common components. The rules in the review rule base cover multiple aspects such as code quality, functional integrity, performance bottlenecks, and security vulnerabilities.

[0030] After that, we integrate automated review tools to automatically analyze, test, and scan common components according to the requirements in the rule base. Automated review tools include but are not limited to static code analysis tools, performance testing tools, security scanning tools, etc.

[0031] When reviewing multiple public component information, obtain the public component information that needs to be reviewed, including code, documents, and configuration files, from the public component library. According to the requirements in the rule library, automatically call the corresponding review tool to perform static code analysis, functional testing, performance testing, and security scanning on the public components. Then analyze the data generated by the review tool, which includes test results, performance indicators, security vulnerabilities, etc. Through data analysis and mining, identify potential problems and risks in public components.

[0032] The public component review results are automatically generated based on the review results. The report contains information such as the evaluation of the public components, a list of problems found, problem details, and repair suggestions.

[0033] Step S400: establishing a feedback channel based on the management mode of the application market, synchronizing the public component review result to the feedback channel, and outputting repair feedback data;

[0034] In the embodiment of the present application, a feedback channel is first established, which is an open, convenient, and easy-to-use platform that allows developers, users, and their stakeholders to submit feedback on public components. The public component review results are then synchronized to the feedback channel. When synchronizing the review results, the accuracy and completeness of the review results are ensured to avoid omissions or erroneous information.

[0035] Once the feedback channel is established and the review results are synchronized, the app market can begin to receive and process feedback submitted by users. Feedback includes issues and suggestions on the performance, functionality, security, etc. of public components.

[0036] After repairing the common components according to the feedback, the repair feedback data is output, which includes key information such as the repair completion time, repair effect, and problem reproduction.

[0037] Step S500: screening the plurality of common component information based on the repair feedback data, and optimizing the quality of the plurality of common component information according to the screening result.

[0038] In an embodiment of the present application, the collected repair feedback data is analyzed to count indicators such as the number of repairs, repair success rate, and repair time of each common component, and to analyze the main problem types and causes encountered during the repair process.

[0039] Based on the analysis results of the repair feedback data, multiple public component information is screened to identify components with unstable performance, frequent security issues, or poor user experience. During the screening process, a series of indicators and thresholds are set, such as components that have been repaired more than a certain number of times, have a repair success rate below a certain level, or have serious security vulnerabilities as objects that need special attention.

[0040] Develop targeted quality optimization strategies for the selected public components. For example, refactor and optimize the component code to improve performance and stability; fix known security vulnerabilities and strengthen component security protection measures. Add new features or improve existing features based on user feedback and market demand.

[0041] Finally, quality optimization is carried out according to the formulated optimization strategy.

[0042] Furthermore, step S100 in the method provided in the application embodiment also includes:

[0043] Based on SpringBoot, it provides a unified interface through RESTAPI;

[0044] Determine multiple access methods based on the unified interface, and determine query entry information in combination with the adaptability plug-in;

[0045] The plurality of common component information is extracted according to the query entry.

[0046] In the embodiment of this application, a Spring Boot project is set up to define the basic structure and dependencies of the project. Including Spring Web dependencies, creating RESTful Web services. Define the service layer and data access layer to handle the logic and data operations of common components. For example, use Spring Data JPA to simplify database access.

[0047] Design the endpoints of the RESTful API to receive and process requests from clients. Ensure that the interface design complies with RESTful principles and use HTTP verbs to represent different operations. Implement these API endpoints in Spring Boot controllers. The controller handles the request, calls the service layer method, and returns the result to the client.

[0048] Determine multiple ways to access public component information based on actual needs. Ways to access public component information include different authentication methods, different request formats, different request headers or parameters, etc. Implement these different access methods in the Spring Boot controller. For example, use Spring Security to handle authentication and authorization; use Jackson or JAXB to handle different data formats.

[0049] To support different clients or integration scenarios, use adaptability plug-ins to determine query entry information. Integrate these adaptability plug-ins in the Spring Boot application to determine which query entry to use based on different request features, such as request headers, request parameters, and client type.

[0050] Once the query entry is determined, the common component information is extracted according to the query entry.

[0051] Furthermore, step S200 in the method provided in the application embodiment also includes:

[0052] Determine the version release management record of the plurality of common component information using Jenkins;

[0053] According to the version release management record, in combination with the multi-language analysis tool record, the operation record of the plurality of common component information is obtained.

[0054] In an embodiment of the present application, one or more Pipeline projects are created for common components in Jenkins. The Pipeline project defines a series of automated build, test, and release tasks to ensure that the version release process of the component is standardized and automated. In the Pipeline, the complete process of version release is defined, including steps such as code pulling, building, testing, packaging, and publishing. Use Jenkinsfile to describe the process to ensure that each step has clear outputs and records. In each step of the Pipeline, use Jenkins's plug-in or API to record key information, such as build time, builder, build status, version number, released package or image information, etc. When the code of a common component changes, Jenkins automatically triggers the Pipeline to execute the version release process. Through the above process, the version release management records of multiple common component information are determined.

[0055] According to the programming language and technology stack used by the common components, select appropriate multi-language analysis tools, such as VisualVM. These tools monitor the behavior of components at runtime, collect performance data, record exceptions and errors, and other key information. Integrate the selected multi-language analysis tools into the runtime environment of the common components to ensure that they can collect the running records of the components in real time or periodically. During the integration process, insert monitoring code into the component code, configure agents or plug-ins, or interact with the running environment in other ways. Once the multi-language analysis tool starts collecting running records, ensure that these records are associated with the version release management records by including identifiers related to the version release, such as version numbers or build IDs in the running records. Finally, use the multi-language analysis tool to obtain various information about the common components at runtime.

[0056] Furthermore, step S200 in the method provided in the application embodiment also includes:

[0057] Counting the number of calls and the frequency of calls of each common component based on the operation records;

[0058] Analyze the operation efficiency of the plurality of common components according to the number of calls and the calling frequency, and obtain a plurality of operation times of the plurality of common components;

[0059] Extracting the number of error occurrences and the error types within the multiple running time periods;

[0060] The target common component is located based on the number of error occurrences and the type of error occurrences, and a call trend analysis is performed on the multiple common components according to the location result to generate the call analysis result.

[0061] In an embodiment of the present application, the call information of each public component is extracted from the collected operation records, including the timestamp of the component being called, the caller, etc. For each public component, the total number of calls in a specific time period is counted by counting the extracted call information. The call frequency is calculated by dividing the total number of calls by the length of the specific time period.

[0062] According to the timestamp information in the running record, calculate the running time of each public component each time it is called. For each public component, collect multiple running time data within a period of time. By analyzing these running time data, evaluate the running efficiency of the public component. For example, calculate statistical indicators such as average running time, maximum running time, minimum running time, and the distribution of running time.

[0063] Filter out the records containing error information from the operation records. These records contain information such as error type, error description, and occurrence time. For each common component, count the number of errors that occurred in a specific time period. Classify and analyze the error types to determine which types of errors are the most common, as well as their possible causes and impacts.

[0064] Combine the number of errors and the types of errors to locate common components that frequently make errors or have a greater impact as target components. Perform time series analysis on the number of calls, call frequency, and runtime of the target common components to determine their call trends in different time periods.

[0065] Finally, the call analysis results are generated based on the call trends.

[0066] Furthermore, step S300 in the method provided in the application embodiment also includes:

[0067] Performing correlation analysis on the plurality of common components based on the call analysis result to generate a correlation factor;

[0068] Determining the review scope of the public components to be reviewed based on the relevance factors;

[0069] The business scenarios of the multiple common components are extracted, and the review mechanism is established according to the review scope based on the component types of the multiple common components.

[0070] In the embodiment of the present application, firstly, according to the call analysis results, key indicators for correlation analysis are determined. These indicators include the call frequency between components, the call chain length, the data sharing situation, the error propagation path, etc. Based on the above indicators, the correlation between each common component is calculated based on the correlation calculation method based on graph theory, the correlation analysis based on statistics, etc. According to the correlation calculation results, a correlation factor is generated for each common component.

[0071] Set the threshold of the correlation factor according to actual needs. Based on the correlation factor and the set threshold, filter out the public components to be reviewed. These components are performance bottlenecks, key nodes for error propagation, or components closely related to key business logic.

[0072] For the selected components to be reviewed, extract the business scenarios and component types to which they belong. According to the business scenarios and component types, formulate a specific review process. The review process includes multiple links such as code review, performance testing, and security scanning to ensure the quality and stability of the components.

[0073] According to the scope of review, determine the specific review content of each component to be reviewed. The review content includes interface call relationships, data processing logic, exception handling mechanism, etc.

[0074] According to the above steps, the establishment of the review mechanism is completed.

[0075] Furthermore, step S300 in the method provided in the application embodiment also includes:

[0076] The review mechanism includes multiple review layers, and each review layer is connected by communication;

[0077] Review the code data of the plurality of common components line by line based on the first review layer to generate a first review result;

[0078] Reviewing the performance data of the plurality of common components based on the second review layer to generate a second review result;

[0079] Reviewing the security data of the plurality of common components based on the third review layer to generate a third review result;

[0080] Reviewing the document data of the plurality of common components based on the fourth review layer to generate a fourth review result;

[0081] The first review result, the second review result, the third review result, and the fourth review result are integrated to obtain the common component review result.

[0082] In the embodiment of the present application, the review mechanism includes four review layers, the first review layer is responsible for the review of code data, the second review layer is responsible for the review of performance data, the third review layer is responsible for the review of security data, and the fourth review layer is responsible for the review of document data. Each review layer is an independent module that can execute review tasks in parallel and exchange data and share results with other review layers through communication connections, such as API interfaces, message queues, etc.

[0083] The first review layer reviews the code data of multiple public components line by line to check the logical correctness of the code, compliance with programming standards, potential defects and vulnerabilities, etc. The review process uses static code analysis tools to automatically scan and evaluate the code to generate the first review results.

[0084] The second review layer reviews the performance data of multiple common components, analyzes key performance indicators such as component response time, throughput, resource utilization, and finds performance bottlenecks and optimization points. The review process generates the second review results based on the data from the performance testing tool or monitoring system.

[0085] The third review layer reviews the security data of multiple public components to check whether the components have security vulnerabilities, whether they comply with security coding specifications, whether necessary security protection measures have been taken, etc. The review process uses security scanning tools, vulnerability detection systems and other means to generate the third review results.

[0086] The fourth review layer reviews the document data of multiple public components to check whether the component interface documents, instructions, change records, etc. are complete, accurate, and easy to understand. The review process is carried out through automated tools to generate the fourth review results.

[0087] After completing the review of each review layer, the first review results, the second review results, the third review results, and the fourth review results are integrated. The integration process weights, sorts, or classifies each review result according to specific review requirements and standards. After the integration is completed, the public component review results are obtained.

[0088] Furthermore, step S500 in the method provided in the application embodiment also includes:

[0089] Calculating the problem repair rate of the plurality of common component information based on the repair feedback data;

[0090] Analyze and obtain the repair efficiency of the plurality of common component information;

[0091] Filter the plurality of common component information based on the problem repair rate and the repair efficiency to obtain a filtering result;

[0092] A component optimization strategy is formulated according to the screening result, and the component optimization strategy is executed to optimize the quality of the plurality of common component information.

[0093] In an embodiment of the present application, successfully repaired problems are screened out from the feedback data, and then the number of repaired problems is compared with the total number of problems to obtain the problem repair rate.

[0094] Analyze the repair time of each fixed issue to determine the time from the discovery of the issue to the completion of the repair. Collect statistics on the repair time of all fixed issues and calculate the average repair time. Analyze the changing trend of repair efficiency by comparing the repair efficiency in different time periods or different versions.

[0095] According to business needs and quality management goals, set the screening criteria for problem repair rate and repair efficiency. For example, set the problem repair rate to be above 80%, and the average repair time to be below a certain threshold. According to the set screening criteria, filter multiple public component information. Components that meet or exceed the standards are considered to be high-quality components, and components that fail to meet the standards are considered to be components that need to be optimized.

[0096] According to the screening results, formulate specific optimization strategies for the public components that need to be optimized. The optimization strategies include improving code structure, optimizing algorithms, enhancing security, improving documentation, etc. Finally, the quality of public components is optimized according to the formulated optimization strategies.

[0097] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0098] This application collects multiple public component information within the target enterprise through registration; retrieves the operation records of multiple public component information, performs call analysis on multiple public component information based on the operation records, and generates call analysis results; establishes a review mechanism based on the call analysis results, reviews multiple public component information, and obtains public component review results; establishes a feedback channel based on the management model of the application market, synchronizes the public component review results to the feedback channel, and outputs repair feedback data; screens multiple public component information based on the repair feedback data, and optimizes the quality of multiple public component information based on the screening results. The present invention solves the technical problems that the prior art lacks in-depth understanding and flexible adaptation of the application market, resulting in unstable component performance and poor compatibility. Through automated testing and continuous integration, data-driven performance analysis and optimization, the technical effect of improving component performance and compatibility is achieved.

[0099] Embodiment 2

[0100] Based on the same inventive concept as the common component optimization method based on the application market in the aforementioned embodiment, Figure 2 As shown, the present application provides a common component optimization system based on the application market, and the system and method embodiments in the present application embodiments are based on the same inventive concept. The system includes:

[0101] A public component information collection module 11, wherein the public component information collection module 11 collects information of multiple public components in a target enterprise through registration;

[0102] A call analysis result generating module 12, wherein the call analysis result generating module 12 retrieves the operation records of the plurality of common component information, performs call analysis on the plurality of common component information according to the operation records, and generates a call analysis result;

[0103] A common component review result acquisition module 13, wherein the common component review result acquisition module 13 establishes a review mechanism based on the call analysis result, reviews the plurality of common component information, and acquires a common component review result;

[0104] A repair feedback data output module 14, wherein the repair feedback data output module 14 establishes a feedback channel based on the management mode of the application market, synchronizes the public component review result to the feedback channel, and outputs the repair feedback data;

[0105] The quality optimization module 15 filters the plurality of common component information based on the repair feedback data, and optimizes the quality of the plurality of common component information according to the filtering result.

[0106] Furthermore, the system also includes:

[0107] Based on SpringBoot, it provides a unified interface through RESTAPI;

[0108] Determine multiple access methods based on the unified interface, and determine query entry information in combination with the adaptability plug-in;

[0109] The plurality of common component information is extracted according to the query entry.

[0110] Furthermore, the system also includes:

[0111] Determine the version release management record of the plurality of common component information using Jenkins;

[0112] According to the version release management record, in combination with the multi-language analysis tool record, the operation record of the plurality of common component information is obtained.

[0113] Furthermore, the system also includes:

[0114] Counting the number of calls and the frequency of calls of each common component based on the operation records;

[0115] Analyze the operation efficiency of the plurality of common components according to the number of calls and the calling frequency, and obtain a plurality of operation times of the plurality of common components;

[0116] Extracting the number of error occurrences and the error types within the multiple running time periods;

[0117] The target common component is located based on the number of error occurrences and the type of error occurrences, and a call trend analysis is performed on the multiple common components according to the location result to generate the call analysis result.

[0118] Furthermore, the system also includes:

[0119] Performing correlation analysis on the plurality of common components based on the call analysis result to generate a correlation factor;

[0120] Determining the review scope of the public components to be reviewed based on the relevance factors;

[0121] The business scenarios of the multiple common components are extracted, and the review mechanism is established according to the review scope based on the component types of the multiple common components.

[0122] Furthermore, the system also includes:

[0123] The review mechanism includes multiple review layers, and each review layer is connected by communication;

[0124] Review the code data of the plurality of common components line by line based on the first review layer to generate a first review result;

[0125] Reviewing the performance data of the plurality of common components based on the second review layer to generate a second review result;

[0126] Reviewing the security data of the plurality of common components based on the third review layer to generate a third review result;

[0127] Reviewing the document data of the plurality of common components based on the fourth review layer to generate a fourth review result;

[0128] The first review result, the second review result, the third review result, and the fourth review result are integrated to obtain the common component review result.

[0129] Furthermore, the system also includes:

[0130] Calculating the problem repair rate of the plurality of common component information based on the repair feedback data;

[0131] Analyze and obtain the repair efficiency of the plurality of common component information;

[0132] Filter the plurality of common component information based on the problem repair rate and the repair efficiency to obtain a filtering result;

[0133] A component optimization strategy is formulated according to the screening result, and the component optimization strategy is executed to optimize the quality of the plurality of common component information.

[0134] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0135] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0136] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A common component optimization method based on an application market, characterized in that: The method comprises: Collect multiple public component information within the target enterprise through registration; Retrieving operation records of the plurality of common component information, performing call analysis on the plurality of common component information according to the operation records, and generating a call analysis result; Establishing a review mechanism based on the call analysis result, reviewing the plurality of common component information, and obtaining a common component review result; Establishing a feedback channel based on the management model of the application market, synchronizing the public component review results to the feedback channel, and outputting repair feedback data; The plurality of common component information are screened based on the repair feedback data, and quality of the plurality of common component information is optimized according to the screening result.

2. The method according to claim 1, characterized in that Collect multiple public component information within the target enterprise through registration, including: Based on SpringBoot, it provides a unified interface through RESTAPI; Determine multiple access methods based on the unified interface, and determine query entry information in combination with the adaptability plug-in; The plurality of common component information is extracted according to the query entry.

3. The method according to claim 1, characterized in that Retrieving the operation records of the plurality of common component information, the method comprising: Determine the version release management record of the plurality of common component information using Jenkins; According to the version release management record, in combination with the multi-language analysis tool record, the operation record of the plurality of common component information is obtained.

4. The method according to claim 1, characterized in that Performing call analysis on the plurality of common component information according to the operation record and generating a call analysis result, the method comprising: Counting the number of calls and the frequency of calls of each common component based on the operation records; Analyze the operation efficiency of the plurality of common components according to the number of calls and the calling frequency, and obtain a plurality of operation times of the plurality of common components; Extracting the number of error occurrences and the error types within the multiple running time periods; The target common component is located based on the number of error occurrences and the type of error occurrences, and a call trend analysis is performed on the multiple common components according to the location result to generate the call analysis result.

5. The method according to claim 1, characterized in that Establishing a review mechanism based on the call analysis result, the method includes: Performing correlation analysis on the plurality of common components based on the call analysis result to generate a correlation factor; Determining the review scope of the public components to be reviewed based on the relevance factors; The business scenarios of the multiple common components are extracted, and the review mechanism is established according to the review scope based on the component types of the multiple common components.

6. The method according to claim 1, characterized in that The plurality of common component information is reviewed to obtain common component review results, the method comprising: The review mechanism includes multiple review layers, and each review layer is connected by communication; Review the code data of the plurality of common components line by line based on the first review layer to generate a first review result; Reviewing the performance data of the plurality of common components based on the second review layer to generate a second review result; Reviewing the security data of the plurality of common components based on the third review layer to generate a third review result; Reviewing the document data of the plurality of common components based on the fourth review layer to generate a fourth review result; The first review result, the second review result, the third review result, and the fourth review result are integrated to obtain the common component review result.

7. The method according to claim 1, characterized in that The plurality of common component information are screened based on the repair feedback data, and quality optimization is performed on the plurality of common component information according to the screening result, the method comprising: Calculating the problem repair rate of the plurality of common component information based on the repair feedback data; Analyze and obtain the repair efficiency of the plurality of common component information; Filter the plurality of common component information based on the problem repair rate and the repair efficiency to obtain a filtering result; A component optimization strategy is formulated according to the screening result, and the component optimization strategy is executed to optimize the quality of the plurality of common component information.

8. A common component optimization system based on the application market, characterized in that: The system comprises: A public component information collection module, which collects information of multiple public components in a target enterprise through registration; A call analysis result generation module, wherein the call analysis result generation module retrieves the operation records of the plurality of common component information, performs call analysis on the plurality of common component information according to the operation records, and generates a call analysis result; A common component review result acquisition module, wherein the common component review result acquisition module establishes a review mechanism based on the call analysis result, reviews the plurality of common component information, and acquires a common component review result; A repair feedback data output module, wherein the repair feedback data output module establishes a feedback channel based on the management mode of the application market, synchronizes the public component review result to the feedback channel, and outputs the repair feedback data; A quality optimization module is provided, wherein the quality optimization module screens the plurality of common component information based on the repair feedback data, and optimizes the quality of the plurality of common component information according to the screening result.

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