Software development management system based on big data and use method thereof

Abstract

The invention discloses a software development management system based on big data and a use method thereof, and relates to the technical field of software development management. Comprising a demand analysis and management module, a resource optimization distribution module, a security management module, a code quality monitoring module, an intelligent test module, a deployment and monitoring module, a user experience analysis module, a cloud service management module and a decision support module. According to the system, through cooperation of the demand analysis and management module, the resource optimization distribution module and the security management module, resource waste is avoided, and the development risk is reduced; the code quality monitoring module and the safety management module are utilized, the system can monitor the readability, complexity and safety of codes in real time, high-risk code segments are recognized and processed through static analysis and a machine learning algorithm, and therefore the code quality and safety are effectively improved; and the system integrates user feedback into demand adjustment and decision support in real time, so that the user adaptability and the market competitiveness of the product are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of software development management, and in particular to a software development management system based on big data and a method for using the same. Background Art

[0002] With the development of information technology and the popularization of big data applications, the importance of software development management systems in multiple industries has become increasingly prominent. Traditional software development processes rely more on manual demand analysis, static resource allocation and limited security management. However, with the expansion of project scale and the acceleration of demand changes, traditional methods are difficult to meet efficient and dynamic management needs. In recent years, intelligent management systems based on big data and artificial intelligence have gradually emerged. By integrating modules such as demand analysis, resource optimization, and security management, they provide an efficient management framework for software development. In particular, through modular design and automation tools, software development systems have improved development efficiency and product quality in terms of the rationality of resource allocation, quality monitoring of the development process, and continuous optimization of user experience, providing the possibility for dynamic management of complex projects.

[0003] The existing software development management system still has many deficiencies. In terms of demand analysis and resource allocation, most systems cannot dynamically adjust resources according to project changes in real time, resulting in resource waste or uneven allocation. Traditional systems often only perform static allocation at the beginning of the project, lack a mechanism to flexibly adjust resources according to demand changes, and cannot meet the dynamic demand of complex projects. In terms of code quality monitoring, existing technologies usually rely on a single quality monitoring tool, which is difficult to achieve collaborative work with the security management module, which makes it difficult to timely discover and deal with potential security risks. Especially in the code development stage, the existing code monitoring methods lack quality optimization for highly complex codes, resulting in frequent code problems. Third, in the testing and deployment stage, traditional test modules and deployment monitoring tools are mostly independent, lack efficient intelligent deployment, and often cannot optimize system performance in real time. In addition, existing technologies also have limitations in user experience analysis and feedback. They cannot dynamically combine user behavior with demand analysis data and lack efficient decision support mechanisms. Therefore, existing technologies are difficult to achieve full-process dynamic management and collaborative optimization of demand analysis, resource optimization, code quality monitoring, security management, and user experience feedback, and cannot give full play to the potential of big data in development management, thereby limiting development efficiency and the overall security of products. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the existing software development management methods lack a dynamic adjustment mechanism for resource allocation, lack of collaborative optimization of code quality and security monitoring, lack of intelligent allocation in the testing and deployment stages, and how to achieve dynamic management of the entire process of demand analysis, resource optimization, code quality and security management, and user experience feedback.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a software development management system based on big data, including a demand analysis and management module, a resource optimization allocation module, a security management module, a code quality monitoring module, an intelligent testing module, a deployment and monitoring module, a user experience analysis module, a cloud service management module, and a decision support module; the demand analysis and management module is used to collect and analyze user needs, generate demand reports, and obtain feedback from the user experience analysis module during project development, and adjust the demand documents, and process the demand analysis and resource allocation stages during the development process based on the demand analysis and management module, the resource optimization allocation module, and the security management module; the resource optimization allocation module is used to intelligently allocate resources; the security management module is used to formulate defense strategies; the code quality monitoring module is used to monitor The intelligent testing module is used to automatically generate and execute test cases, and to handle the testing and deployment stages of the development process based on the intelligent testing module, deployment and monitoring module, and cloud service management module; the deployment and monitoring module is used for automated deployment and system monitoring; the user experience analysis module is used to analyze user feedback and behavior, and provide a basis for product optimization, and to handle the user experience analysis and feedback stages of the development process based on the user experience analysis module, demand analysis and management module, and decision support module; the cloud service management module provides cloud resource management; the decision support module provides comprehensive data analysis to support management decisions.

[0007] As a preferred solution of the software development management system based on big data described in the present invention, the demand analysis and resource allocation stage in the development process includes a demand analysis and management module that generates demand documents based on user needs, a resource optimization allocation module that intelligently allocates resources based on needs and combined with team capabilities, and a security management module that intervenes to pay attention to security needs in demand analysis.

[0008] As a preferred solution of the software development management system based on big data described in the present invention, the code development and quality monitoring stages in the development process include a resource optimization allocation module to coordinate the allocation of development resources and start the project, a code quality monitoring module to continuously monitor the code quality and discover potential problems, a security management module to monitor security issues in the code, and collaborate with the code quality monitoring module to handle security risks.

[0009] As a preferred solution of the software development management system based on big data described in the present invention, wherein: the project startup includes the resource optimization allocation module receiving the input of the demand analysis and management module, generating a preliminary resource allocation plan, and allocating development resources when the project is started, and the resource optimization allocation module sends the resource configuration information to the code quality monitoring module and the security management module; discovering potential problems includes the code quality monitoring module receiving the resource information of the resource optimization allocation module, performing static code analysis and code quality measurement, using static analysis tools to evaluate the readability, complexity and repetition rate of the code segment, and the code quality monitoring module using static analysis to evaluate the readability of the code , Complexity Index and repetition rate The data is output to the security management module, and based on the complexity and repetition rate, potential high-risk code segments are marked; the processing of security risks includes the security management module executing anomaly detection algorithm after receiving the high-risk code segments and quality indicator data marked by the code quality monitoring module, using the machine learning model to analyze the marked code segments, and using the trained anomaly detection model to extract features of security vulnerabilities from them. The security management module feeds back the analysis results to the resource optimization allocation module through the anomaly detection model. The resource optimization allocation module dynamically adjusts the resources according to the feedback from the security management module. The resource optimization allocation module passes the updated resource configuration plan to the code quality monitoring module again. The code quality monitoring module continuously monitors the readability, complexity and repetition rate of the code, and analyzes the quality indicators of the new code in real time when code changes are detected. At the same time, the latest quality data is fed back to the security management module for secondary security detection. The security management module uses the machine learning model to detect anomalies on the newly added parts of the code to identify potential code security vulnerabilities. If a new high-risk code segment is detected, the information is immediately passed to the resource optimization allocation module, and it is recommended to allocate more security resources or adjust the task priority of the developer.

[0010] As a preferred solution of the big data-based software development management system described in the present invention, the testing and deployment stage in the development process includes an intelligent testing module executing automated testing to verify code quality. After the test passes, the deployment and monitoring module executes automated deployment and starts real-time system monitoring. The deployment and monitoring module collaborates with the cloud service management module to complete the operation of the system in a cloud environment.

[0011] As a preferred solution of the software development management system based on big data described in the present invention, the user experience analysis and feedback stage in the development process includes a user experience analysis module to collect user feedback and behavior data, a demand analysis and management module to continuously update the demand document based on user experience feedback, and a decision support module to integrate user data and demand information to provide decision suggestions.

[0012] As a preferred solution of the software development management system based on big data described in the present invention, the decision support module provides comprehensive information support to the management through report output of comprehensive evaluation information of the project, including resource utilization efficiency, code quality, system security and user feedback trends. At the same time, the decision support module updates the algorithm model according to management needs and continuously optimizes the analysis results.

[0013] Another object of the present invention is to provide a software development management method based on big data, which can handle the code development and quality monitoring stages in the development process based on a code quality monitoring module, a resource optimization allocation module, and a security management module, thereby solving the problem that the current software development management technology contains a lack of coordinated optimization of code quality and security monitoring.

[0014] As a preferred solution of the software development management method based on big data described in the present invention, it includes: including based on the demand analysis and management module, the resource optimization allocation module and the security management module, processing the demand analysis and resource allocation stage in the development process; based on the code quality monitoring module, the resource optimization allocation module and the security management module, processing the code development and quality monitoring stage in the development process, the resource optimization allocation module coordinates the allocation of development resources and starts the project, the code quality monitoring module continuously monitors the code quality and discovers potential problems, the security management module monitors the security issues in the code, and cooperates with the code quality monitoring module to deal with security risks; based on the intelligent testing module, the deployment and monitoring module and the cloud service management module, processing the testing and deployment stage in the development process; based on the user experience analysis module, the demand analysis and management module and the decision support module, processing the user experience analysis and feedback stage in the development process.

[0015] Beneficial effects of the present invention: The software development management system based on big data provided by the present invention can dynamically adjust resource allocation through the collaboration of the demand analysis and management module, the resource optimization allocation module and the security management module, ensure the efficiency and security of resource utilization, avoid resource waste and reduce development risks; using the code quality monitoring module and the security management module, the system can monitor the readability, complexity and security of the code in real time, identify and process high-risk code segments through static analysis and machine learning algorithms, thereby effectively improving the code quality and security; through the automated testing and cloud deployment of the intelligent testing module and the deployment and monitoring module, the system realizes efficient linkage of testing and deployment, greatly shortens the development cycle, and ensures the stability of the system in the cloud environment; through the feedback mechanism of the user experience analysis module, the demand analysis module and the decision support module, the system integrates user feedback into the demand adjustment and decision support in real time, ensures the user adaptability and market competitiveness of the product, and the present invention achieves better results in resource utilization, code quality, security assurance and user adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0017] Figure 1 An overall flow chart of a software development management system based on big data provided for the first embodiment of the present invention.

[0018] Figure 2 An overall flow chart of a software development management method based on big data provided for the third embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0020] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a software development management system based on big data, including: Demand analysis and management module 100, resource optimization allocation module 200, security management module 300, code quality monitoring module 400, intelligent testing module 500, deployment and monitoring module 600, user experience analysis module 700, cloud service management module 800, and decision support module 900.

[0021] Furthermore, the demand analysis and management module 100 is used to collect and analyze user needs, generate demand reports, and obtain feedback from the user experience analysis module 700 during the project development process, and adjust the demand documents. Based on the demand analysis and management module 100, the resource optimization allocation module 200 and the security management module 300, the demand analysis and resource allocation stages in the development process are processed; the resource optimization allocation module 200 is used to intelligently allocate resources; the security management module 300 is used to formulate defense strategies; the code quality monitoring module 400 is used to monitor the code quality in the development process, detect problems and feedback to the development team, based on the code quality monitoring module 400, the resource optimization allocation module 200, the security management module 300, The intelligent testing module 500 is used to automatically generate and execute test cases. Based on the intelligent testing module 500, the deployment and monitoring module 600 and the cloud service management module 800, the testing and deployment stages of the development process are handled. The deployment and monitoring module 600 is used for automated deployment and system monitoring. The user experience analysis module 700 is used to analyze user feedback and behavior to provide a basis for product optimization. Based on the user experience analysis module 700, the demand analysis and management module 100 and the decision support module 900, the user experience analysis and feedback stages of the development process are handled. The cloud service management module 800 provides cloud resource management. The decision support module 900 provides comprehensive data analysis to support management decisions.

[0022] It should be noted that the demand analysis and resource allocation stage in the development process includes a demand analysis and management module 100 that generates demand documents based on user needs, a resource optimization allocation module 200 that intelligently allocates resources based on needs and combined with team capabilities, and a security management module 300 that intervenes to focus on security needs in demand analysis.

[0023] It should also be noted that the demand analysis and resource allocation stage in the development process is processed through the synergy of the demand analysis and management module 100, the resource optimization allocation module 200 and the security management module 300, so as to realize the demand analysis and intelligent resource allocation of the development process. The demand analysis and management module 100 generates a demand report by collecting user needs. At the same time, it obtains feedback from the user experience analysis module 700 and adjusts the demand document during the development process to dynamically adapt to project needs. After receiving the demand information, the resource optimization allocation module 200 performs intelligent resource allocation based on the team's capabilities to ensure the rationality and efficiency of resource use. In addition, the security management module 300 intervenes in the demand analysis stage, pays attention to potential security needs, and strengthens the security protection of the system from an early stage, so that the system can meet user needs while ensuring the flexibility of resource allocation and the simultaneous improvement of security, effectively improving development efficiency and reducing the risk of resource waste.

[0024] It should also be noted that the code development and quality monitoring stage during the development process includes the resource optimization allocation module 200 coordinating the allocation of development resources and launching the project, the code quality monitoring module 400 continuously monitoring the code quality and discovering potential problems, and the security management module 300 monitoring the security issues in the code and coordinating with the code quality monitoring module 400 to handle security risks.

[0025] Furthermore, the project initiation includes the resource optimization allocation module 200 receiving the input of the demand analysis and management module 100, generating a preliminary resource allocation plan, and allocating development resources when the project is started, and the resource optimization allocation module 200 sends the resource configuration information to the code quality monitoring module 400 and the security management module 300; the discovery of potential problems includes the code quality monitoring module 400 receiving the resource information of the resource optimization allocation module 200, performing static code analysis and code quality measurement, using static analysis tools to evaluate the readability, complexity and repetition rate of the code segment, and the code quality monitoring module 400 using static analysis to evaluate the readability of the code. , Complexity Index and repetition rate The data is output to the security management module 300, and based on the complexity and repetition rate, potential high-risk code segments are marked; processing security risks includes the security management module 300 executing an anomaly detection algorithm after receiving the high-risk code segments and quality indicator data marked by the code quality monitoring module 400, using a machine learning model to analyze the marked code segments, and using the trained anomaly detection model to extract features of security vulnerabilities therefrom, the security management module 300 feeds back the analysis results to the resource optimization allocation module 200 through the anomaly detection model, and the resource optimization allocation module 200 dynamically adjusts resources according to the feedback of the security management module 30 ... The allocation module 200 passes the updated resource allocation plan to the code quality monitoring module 400 again. The code quality monitoring module 400 continuously monitors the readability, complexity and repetition rate of the code, and analyzes the quality indicators of the new code in real time when code changes are detected. At the same time, the latest quality data is fed back to the security management module 300 for secondary security testing. The security management module 300 uses a machine learning model to detect anomalies in the newly added parts of the code and identify potential code security vulnerabilities. If a new high-risk code segment is detected, the information is immediately passed to the resource optimization allocation module 200, suggesting the allocation of more security resources or the adjustment of the developer's task priority.

[0026] It should also be noted that the specific process of marking potentially high-risk code segments can be defined by defining a comprehensive risk score. , the score is the readability evaluation result , Complexity Index and repetition rate The weighted sum of the three indicators is expressed as:

[0027] in, , , are the weight coefficients of readability, complexity and repetition rate. Through empirical judgment and optimization, the weights are set to , , , that is, complexity plays a major role in the comprehensive score, and the comprehensive risk score The range is from 0 to 100, with higher scores indicating greater risk for the code segment. , the code segments are divided into different risk levels, so as to further refine the criteria for determining high-risk code segments. The specific classification of risk levels includes low risk ( ): The code quality is high, and the readability, complexity, and repetition rate are within a reasonable range, and no special treatment is required; medium risk ( ): There are some problems with the code, and quality optimization is recommended, but it does not pose a serious risk; high risk ( ): There are obvious defects in the code quality, which needs to be checked and optimized first; Very high risk ( ): The code has serious risks and may cause security risks, which requires immediate intervention.

[0028] It should also be noted that the code development and quality monitoring stage in the development process is handled through the collaborative work of the resource optimization allocation module 200, the code quality monitoring module 400 and the security management module 300, so as to realize the code quality monitoring and security risk prevention in the development process. The resource optimization allocation module 200 allocates development resources when the project starts, and passes the resource configuration information to the code quality monitoring module 400 and the security management module 300 to provide support for the development and monitoring process. The code quality monitoring module 400 continuously monitors the code quality during the development process, evaluates the readability, complexity and repetition rate of the code through static analysis tools, and outputs the analysis data to the security management module 300 to mark potential high-risk code segments. The security management module 300 uses anomaly detection algorithms to further analyze the marked high-risk code segments and identifies possible security vulnerabilities through machine learning models. The resource optimization allocation module 200 dynamically adjusts the resource configuration based on the feedback from the security management module to ensure the compatibility of resource allocation and security requirements in the development process. This process realizes efficient code quality control, effectively prevents potential security risks, and improves the security and stability of the code.

[0029] It should be noted that the testing and deployment stage in the development process includes the intelligent testing module 500 performing automated testing to verify the code quality. After the test passes, the deployment and monitoring module 600 performs automated deployment and starts real-time system monitoring. The deployment and monitoring module 600 collaborates with the cloud service management module 800 to complete the operation of the system in the cloud environment.

[0030] It should also be noted that the testing and deployment stages in the development process are handled through the joint action of the intelligent testing module 500, the deployment and monitoring module 600 and the cloud service management module 800, thereby realizing testing and automated deployment in the development process. The intelligent testing module 500 generates and executes test cases through automated testing to verify whether the code quality meets the standards. After the test passes, the deployment and monitoring module 600 is responsible for automated deployment and starting real-time monitoring of the system. At the same time, the cloud service management module 800 collaborates to complete resource management in the cloud environment to ensure the stable operation of the system in the cloud environment. Through this step, the system realizes automated verification of the test and intelligent control of the deployment process, thereby ensuring the quality of the system and the stability of its operation and improving deployment efficiency.

[0031] It should also be noted that the user experience analysis and feedback stage in the development process includes the user experience analysis module 700 collecting user feedback and behavior data, the demand analysis and management module 100 continuously updating the demand document based on the user experience feedback, and the decision support module 900 integrating user data and demand information to provide decision suggestions.

[0032] It should also be noted that user experience analysis and feedback optimization are achieved through the joint action of the user experience analysis module 700, the demand analysis and management module 100 and the decision support module 900. The user experience analysis module 700 collects user feedback and behavior data, and passes the data to the demand analysis and management module 100 and the decision support module 900. The demand analysis and management module 100 dynamically adjusts the demand document based on user feedback and continuously optimizes the system to meet user needs. The decision support module 900 integrates user data, demand information and other module data, provides decision suggestions and outputs comprehensive evaluation information, and provides comprehensive decision support for management. Through this step, the system achieves continuous optimization guided by user feedback, enhances the user experience of the product, and provides management with a reliable decision-making basis, effectively improving the market adaptability of the product.

[0033] Furthermore, the decision support module 900 provides comprehensive information support to the management by outputting comprehensive evaluation information of the project through reports, including resource utilization efficiency, code quality, system security and user feedback trends. At the same time, the decision support module 900 updates the algorithm model according to management needs and continuously optimizes the analysis results.

[0034] Example 2 is an embodiment of the present invention, which provides a software development management system based on big data. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0035] First, in this embodiment, in order to verify the performance and advantages of the software development management system based on big data, a complex software development project is simulated, and the performance of the system in demand analysis, code quality monitoring, security management, testing and deployment is tested in stages. The data is analyzed through the comprehensive output of each module. The project first enters the demand analysis and resource allocation stage. A detailed demand document is generated through the demand analysis and management module. The resource optimization allocation module receives the demand and generates a preliminary resource allocation plan based on the project team's capabilities to ensure efficient use of resources. The security management module also intervenes in the demand analysis process to identify and record potential security requirements and ensure the security strategy in the early stage of system development. In the code development and quality monitoring stage, after the project is launched, the resource optimization allocation module allocates development resources according to the plan. The code quality monitoring module continuously monitors the readability, complexity and repetition rate of the code segment, and quantifies the indicators through the static code analysis tool. A weighted scoring system is used in this stage to comprehensively score the readability, complexity and repetition rate, and divide them into four risk levels: low, medium, high and extremely high. The code quality The volume monitoring module passes the marked high-risk code segments to the security management module, which performs secondary analysis through the anomaly detection model to identify potential security risks. If an extremely high-risk code segment is detected, the security management module will feedback the resource adjustment requirements to the resource optimization allocation module so that the system can increase security resources in a timely manner. In the testing and deployment stage, the intelligent testing module automatically generates and executes test cases to verify the code quality, and the deployment and monitoring module automatically deploys it after the test passes. The cloud service management module collaborates to optimize cloud resource allocation during system deployment to ensure the efficient operation of the system in the cloud environment, and automatically adjusts resources based on real-time monitoring data to prevent resource waste. In the user experience analysis and feedback stage, the user experience analysis module collects user feedback data and quantifies indicators. The demand analysis and management module adjusts the demand documents based on user feedback to ensure that the system continues to meet user needs. The decision support module summarizes user data, project indicators and resource usage, generates a decision support report, and assists the management in making the next resource and development decision. Refer to Table 1 to record and analyze the system test data.

[0036] Table 1 System test data table stage Project cycle (days) Demand fulfillment rate (%) Resource utilization (%) Code quality score (0-100) Security vulnerability detection times Test pass rate (%) User satisfaction (0-10) Demand analysis and resource allocation 5 95 80 N / A 0 N / A N / A Code development and quality control 15 100 85 70 3 N / A N / A High-risk code snippet marker 5 N / A 90 50 5 N / A N / A Testing and deployment 7 N / A 88 75 1 92 N / A User experience analysis and feedback 3 N / A 70 N / A 0 N / A 8.5 Comprehensive performance evaluation 30 N / A 85 72 9 N / A 8.7 By recording the main indicators of each development stage, the effectiveness and advantages of the software development management system based on big data are clearly demonstrated. First, in the demand analysis and resource allocation stage, the demand completion rate reached 95% and the resource utilization rate was 80%, indicating that the resource optimization allocation module reasonably allocated development resources in the demand analysis stage, achieving the effect of rapid response to demand and efficient resource configuration. Compared with the static resource allocation mode in traditional systems, the present invention realizes dynamic resource management, making resource utilization more flexible and efficient. In the code development and quality monitoring stage, through the collaborative work of the code quality monitoring module and the security management module, the project achieved a resource utilization rate of 85% and a code quality score of 70 points. Compared with traditional systems, the present invention adds a static analysis tool based on big data, which can discover and mark potential high-risk code segments in the early stage of development. Especially in the process of marking high-risk code segments, the comprehensive risk score of 50 points The code segment was marked by the security management module, and 5 security vulnerabilities were successfully detected, effectively avoiding the potential risks of the code. In the testing and deployment stage, the intelligent testing module realized automated testing with a pass rate of 92%, which is much higher than the manual testing method of the traditional system. At the same time, the cloud service management module automatically allocated resources during deployment and achieved a resource utilization rate of 88%. This process shows the automation level of the present invention in the testing and deployment process, significantly improves the system stability, and shows innovation in cloud resource optimization. In the user experience analysis and feedback stage, the user satisfaction collected by the user experience analysis module was 8.5 points, combined with the user satisfaction of 8.7 points achieved in the comprehensive performance evaluation stage, indicating that the system can continuously adjust requirements according to user feedback to ensure the optimization of user experience. Through the comprehensive data analysis of the decision support module, the management can make scientific decisions based on user feedback and system resource usage.

[0037] Example 3, reference Figure 2, which is an embodiment of the present invention, provides a software development management method based on big data, including processing the demand analysis and resource allocation stage in the development process based on the demand analysis and management module 100, the resource optimization allocation module 200 and the security management module 300; processing the code development and quality monitoring stage in the development process based on the code quality monitoring module 400, the resource optimization allocation module 200, and the security management module 300, the resource optimization allocation module 200 coordinates the allocation of development resources and starts the project, the code quality monitoring module 400 continuously monitors the code quality and finds potential problems, the security management module 300 monitors the security issues in the code and cooperates with the code quality monitoring module 400 to handle security risks; processing the testing and deployment stage in the development process based on the intelligent testing module 500, the deployment and monitoring module 600 and the cloud service management module 800; processing the user experience analysis and feedback stage in the development process based on the user experience analysis module 700, the demand analysis and management module 100, and the decision support module 900.

[0038] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0039] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0040] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0041] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logical function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0042] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A software development management system based on big data, characterized in that: include: Demand analysis and management module (100), resource optimization allocation module (200), security management module (300), code quality monitoring module (400), intelligent testing module (500), deployment and monitoring module (600), user experience analysis module (700), cloud service management module (800), decision support module (900); The demand analysis and management module (100) is used to collect and analyze user needs, generate demand reports, obtain feedback from the user experience analysis module (700) during the project development process, and adjust the demand documents. Based on the demand analysis and management module (100), the resource optimization allocation module (200) and the security management module (300), the demand analysis and resource allocation stage in the development process is processed; The resource optimization allocation module (200) is used to intelligently allocate resources; The security management module (300) is used to formulate a defense strategy; The code quality monitoring module (400) is used to monitor the code quality during the development process, detect problems and feed back to the development team, and based on the code quality monitoring module (400), the resource optimization allocation module (200), and the security management module (300), the code development and quality monitoring stages during the development process are processed; The intelligent testing module (500) is used to automatically generate and execute test cases, and based on the intelligent testing module (500), the deployment and monitoring module (600) and the cloud service management module (800), the testing and deployment phases in the development process are processed; The deployment and monitoring module (600) is used for automated deployment and system monitoring; The user experience analysis module (700) is used to analyze user feedback and behavior to provide a basis for product optimization, and to process the user experience analysis and feedback phase of the development process based on the user experience analysis module (700), the demand analysis and management module (100), and the decision support module (900); The cloud service management module (800) provides cloud resource management; The decision support module (900) provides comprehensive data analysis to support management decisions.

2. The software development management system based on big data according to claim 1, characterized in that: The demand analysis and resource allocation stage in the processing development process includes a demand analysis and management module (100) generating a demand document according to user demand, a resource optimization allocation module (200) performing intelligent resource allocation according to demand and in combination with team capabilities, and a security management module (300) intervening to focus on security requirements in demand analysis.

3. The software development management system based on big data as claimed in claim 2, characterized in that: The code development and quality monitoring stage in the development process includes a resource optimization allocation module (200) coordinating the allocation of development resources and launching the project, a code quality monitoring module (400) continuously monitoring the code quality and discovering potential problems, and a security management module (300) monitoring security issues in the code and coordinating with the code quality monitoring module (400) to handle security risks.

4. The software development management system based on big data as claimed in claim 3, characterized in that: The project initiation includes the resource optimization allocation module (200) receiving the input of the demand analysis and management module (100), generating a preliminary resource allocation plan, and allocating development resources when the project is initiated, and the resource optimization allocation module (200) sending the resource configuration information to the code quality monitoring module (400) and the security management module (300); The potential problem is discovered by the code quality monitoring module (400) receiving the resource information from the resource optimization allocation module (200), performing static code analysis and code quality measurement, using a static analysis tool to evaluate the readability, complexity and repetition rate of the code segment, and the code quality monitoring module (400) analyzing the readability evaluation results of the code. , Complexity Index and repetition rate The data is output to the security management module (300), and based on the complexity and repetition rate, potential high-risk code segments are marked; Processing security risks includes the following steps: after receiving the high-risk code segments and quality indicator data marked by the code quality monitoring module (400), the security management module (300) executes an anomaly detection algorithm, uses a machine learning model to analyze the marked code segments, and uses the trained anomaly detection model to extract features of security vulnerabilities from the code segments; the security management module (300) feeds back the analysis results to the resource optimization allocation module (200) through the anomaly detection model; the resource optimization allocation module (200) dynamically adjusts resources according to the feedback from the security management module (300); and the resource optimization allocation module (200) sends the updated resource configuration plan to the resource optimization allocation module (200). The code is then passed to the code quality monitoring module (400) again. The code quality monitoring module (400) continuously monitors the readability, complexity and repetition rate of the code, and analyzes the quality indicators of the new code in real time when a code change is detected. At the same time, the latest quality data is fed back to the security management module (300) for secondary security detection. The security management module (300) uses a machine learning model to perform anomaly detection on the newly added part of the code to identify potential code security vulnerabilities. If a new high-risk code segment is detected, the information is immediately passed to the resource optimization allocation module (200) to recommend allocating more security resources or adjusting the task priority of the developer.

5. The software development management system based on big data as claimed in claim 4, characterized in that: The testing and deployment phase in the development process includes an intelligent testing module (500) performing automated testing to verify code quality. After the test passes, the deployment and monitoring module (600) performs automated deployment and starts real-time system monitoring. The deployment and monitoring module (600) collaborates with the cloud service management module (800) to complete the operation of the system in a cloud environment.

6. The software development and management system based on big data according to claim 5, characterized in that: The user experience analysis and feedback phase of the development process includes a user experience analysis module (700) collecting user feedback and behavior data, a demand analysis and management module (100) continuously updating demand documents based on user experience feedback, and a decision support module (900) integrating user data and demand information to provide decision suggestions.

7. The software development and management system based on big data according to claim 6, characterized in that: The decision support module (900) outputs comprehensive evaluation information of the project through reports, including resource utilization efficiency, code quality, system security and user feedback trends, to provide all-round information support for the management. At the same time, the decision support module (900) updates the algorithm model according to management needs and continuously optimizes the analysis results.

8. A method of using the big data-based software development management system as claimed in any one of claims 1 to 7, characterized in that: It includes a requirement analysis and management module (100), a resource optimization allocation module (200) and a security management module (300) to process the requirement analysis and resource allocation stages in the development process; Based on the code quality monitoring module (400), the resource optimization allocation module (200), and the security management module (300), the code development and quality monitoring stages in the development process are handled. The resource optimization allocation module (200) coordinates the allocation of development resources and initiates the project. The code quality monitoring module (400) continuously monitors the code quality and discovers potential problems. The security management module (300) monitors the security issues in the code and cooperates with the code quality monitoring module (400) to handle security risks. Based on the intelligent testing module (500), the deployment and monitoring module (600) and the cloud service management module (800), the testing and deployment phases in the development process are processed; The user experience analysis and feedback phase of the development process is processed based on the user experience analysis module (700), the demand analysis and management module (100), and the decision support module (900).

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