Research and development personnel performance evaluation method and system, electronic equipment and storage medium

Abstract

The invention provides a research and development personnel performance evaluation method and system, electronic equipment and a storage medium. The evaluation method comprises the following steps: deploying a research and development personnel comprehensive performance evaluation model constructed based on a value calculation model, an output calculation model and a quality calculation model on a server; the value calculation model calculates a value metric value based on the work task data completed by the research and development personnel; the output calculation model calculates an output measurement value by calculating a code output amount according to an output conversion rule, an attendance day number and an output measurement rule; the quality calculation model calculates a quality measurement value based on the bug number and the vulnerability number; and carrying out fusion calculation on the value measurement value, the output measurement value and the quality measurement value according to a weight ratio to obtain a comprehensive efficiency measurement value of the research and development personnel. The efficiency of efficiency data collection and processing of research and development personnel is improved, the investment of time cost is reduced, consistency and standardized processing of statistical data are ensured, and comparability and reliability are achieved at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of R&D management, and in particular to a method, device, electronic device and storage medium for evaluating the performance of R&D personnel. Background Art

[0002] In the information technology and software development industry, as the scale of enterprises expands and the complexity of projects increases, the management and evaluation of R&D personnel has become an increasingly important issue. Traditional management methods rely on manual statistics and reporting, which is not only inefficient but also prone to errors, resulting in opaque and incomplete data, making it difficult to provide accurate and real-time decision support for management. In particular, for the performance evaluation of R&D personnel, traditional methods often focus on a single output volume or task completion rate, ignoring multi-dimensional considerations such as work value and code quality, and are unable to fully reflect the actual contributions and potential problems of R&D personnel.

[0003] Most existing R&D personnel performance evaluation systems are based on simple data aggregation and report generation, lacking in-depth analysis and dynamic adjustment mechanisms. These systems can usually only provide basic work statistics, such as the number of lines of code, the number of tasks completed, etc., but cannot conduct personalized evaluations based on factors such as the actual work situation of R&D personnel, project requirements, and technical difficulty, and cannot fully reflect the comprehensive performance of R&D personnel. Summary of the invention

[0004] A method for evaluating the effectiveness of R&D personnel comprises the following steps: Deploy a comprehensive performance evaluation model for R&D personnel based on the value calculation model, output calculation model, and quality calculation model on the server; The value calculation model performs the following steps to calculate the value measurement value, which is used to characterize the work efficiency and problem-solving ability of R&D personnel: Obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation model performs the following steps to calculate the output metric value, which is used to characterize the code output efficiency of the developer: Pull the amount of code submitted by developers to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on the preset output measurement rule, according to the output efficiency, the output measurement value is calculated; The quality calculation model performs the following steps to determine a quality metric value, which is used to characterize the quality of the code of the developer: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; Based on a preset comprehensive performance measurement benchmark value, the value measurement value, output measurement value and quality measurement value are fused and calculated according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel. The comprehensive performance measurement value is used to characterize the performance of the R&D personnel.

[0005] Optionally, the acquiring of the work task data completed by the R&D personnel and calling a preset value measurement value calculation strategy to calculate the value measurement value includes: Obtaining the work task data completed by the R&D personnel, and obtaining the points for completed tasks and resolved bugs based on the work task data; Based on the points of the completed tasks and the points of the resolved bugs, a preset value metric calculation strategy is called to calculate the value metric; The value measurement value calculation strategy is: value measurement value = completed task points + resolved bug points.

[0006] Optionally, before obtaining the completed task points and resolved bug points, the following steps are also included: Obtain user stories created based on business requirements and tasks broken down based on the user stories; Attribute data of the task is obtained to determine the completed task points based on the attribute data of the task.

[0007] Optionally, determining the completed task points based on the attribute data of the task includes: Based on the task type, task difficulty and estimated processing time in the attribute data of the task, corresponding points are allocated to each task; The task attribute data includes task type and task difficulty; The task types include tasks or subtasks, and bug resolution; The task difficulty levels include high, medium, and low; The points are evaluated based on the man-days required for an intermediate consultant to complete a medium-difficulty task under standard conditions, with 1 point = 1 man-day. For high-difficulty tasks, the points are increased according to a preset ratio; for low-difficulty tasks, the points are reduced according to a preset ratio. The points of the resolved bug are calculated based on the generation and resolution of the bug. The specific rules are: obtain the bug maker ID and the solver ID to determine whether the bug maker and the solver are the same person. If they are the same person, no points are calculated; if they are not the same person, points are calculated for the solver.

[0008] Optionally, the pulling of the amount of code submitted by the developer to the git repository to calculate the amount of code output includes: Get the cumulative number of added and deleted lines of code submitted to the git repository by R&D personnel through the preset account; The code output is determined based on the cumulative number of added code lines and the cumulative number of deleted code lines.

[0009] Optionally, the determining of the code output based on the cumulative number of added code lines and the cumulative number of deleted code lines is specifically: The code output is obtained based on the following code output calculation formula: Code output = increase in code + reduction in code; Wherein, the amount of increased code = the cumulative number of increased code lines; The reduced code volume = the cumulative number of reduced code lines * the reduced code volume coefficient; The code reduction coefficient can have different values ​​configured by R&D personnel.

[0010] Optionally, the calculating the output efficiency according to the output conversion rule, the attendance days, and the code output volume includes: Obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount; The output efficiency is calculated based on the code output conversion amount and the attendance days.

[0011] Optionally, obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount includes the following steps: Obtaining the level data of the R&D personnel, and obtaining the corresponding job grade conversion coefficient based on the level data; Obtain the development language used by the R&D personnel, and obtain the corresponding language conversion coefficient based on the development language; The code output conversion amount is obtained based on the following code output conversion calculation formula: Code output conversion amount = code output amount * job level conversion coefficient * language conversion coefficient; The job grade conversion coefficient is set based on the level of the R&D personnel and can be modified as needed; The language conversion factor is set based on the development language used by the developer and can be modified as needed.

[0012] Optionally, the output efficiency is calculated according to the code output conversion amount and the attendance days, and is specifically calculated based on the following output efficiency calculation rule: Output efficiency = code output conversion / attendance days; The output efficiency is used to represent the average converted output that employees can produce when they are on duty every day.

[0013] Optionally, the calculating the output measurement value based on the preset output measurement rule and according to the output efficiency specifically includes: If the output efficiency is <= 20, the output measure value is 10; If the output efficiency is >= 100, the output measure value is 60; If the output efficiency is between 20-100, the output measurement value = output efficiency * 0.6.

[0014] Optionally, scanning the code submitted by the developer based on the automatic code scanning suite to obtain a scanning result; and determining the number of bugs and vulnerabilities based on the scanning result specifically comprises the following steps: Configure the system front-end and back-end automated static code scanning suite in the continuous testing service under the project; Scanning the code submitted by the developer according to a preset period based on the scanning suite to obtain a scanning result; Based on the scan results, the number of bugs and the number of vulnerabilities are determined.

[0015] Optionally, the adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value specifically includes: Get the set basic quality metric value; Obtaining bug type data, and obtaining a corresponding bug deduction coefficient based on the bug type data; Obtain vulnerability type data, and obtain a corresponding vulnerability deduction coefficient based on the vulnerability type data; Calculate the total Bug deduction by multiplying the number of different types of bugs by the corresponding Bug deduction coefficient. Calculate the total vulnerability deduction score by multiplying the number of different types of vulnerabilities by the corresponding vulnerability deduction coefficient and summing them up; The quality metric value is calculated based on the following quality metric value calculation formula: Quality metric value = basic quality metric value - total bug deduction points - total vulnerability deduction points.

[0016] Optionally, the basic quality metric value is set to 20 as a starting reference point for code quality assessment, and the basic quality setting value can be adjusted according to demand.

[0017] Optionally, based on the preset comprehensive performance measurement benchmark value, the value measurement value, the output measurement value and the quality measurement value are integrated and calculated according to a preset weight ratio to obtain the comprehensive performance measurement value of the R&D personnel, including: Get the set comprehensive performance measurement benchmark value of 100 points; The value measurement value, output measurement value and quality measurement value are assigned values ​​according to a preset weight ratio, specifically: The value measurement value accounts for 20% of the comprehensive effectiveness measurement benchmark value; The output measurement value accounts for 60% of the comprehensive performance measurement benchmark value, and the full score of the output measurement value is set to 60 points accordingly; The quality metric value accounts for 20% of the comprehensive performance metric benchmark value, and the basic quality metric value is set at 20 points accordingly; The value measurement value, the output measurement value and the quality measurement value are added together to obtain a comprehensive performance measurement value of the R&D personnel.

[0018] Optionally, a multi-dimensional analysis is performed based on the collected comprehensive performance measurement data, including: Conduct statistical analysis on the overall effectiveness of teams, projects, and departments; Conduct horizontal comparative performance analysis based on R&D personnel with different roles, levels, and expertise; By customizing and optimizing the evaluation model, a personalized evaluation plan is formulated according to the actual situation and characteristics of each R&D personnel to convert the performance of R&D personnel into quantifiable indicators.

[0019] The present application also provides a research and development personnel effectiveness evaluation system, including: A comprehensive performance evaluation module, which includes a value calculation module, an output calculation module, a quality calculation module, and a comprehensive processing module; The value calculation module is used to calculate the value measurement value, specifically including: obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation module is used to calculate the output measurement value, specifically including: pulling the amount of code submitted by the R&D personnel to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on the preset output measurement rule, according to the output efficiency, the output measurement value is calculated; The quality calculation module is used to calculate the quality metric value, specifically including: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; The comprehensive processing module, based on a preset comprehensive performance measurement benchmark value, fuses and calculates the value measurement value, output measurement value and quality measurement value according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel.

[0020] The present application also provides an electronic device, comprising: a memory and a processor, wherein the memory stores a computer executable program, and the processor is used to execute the computer executable program to implement any one of the methods described in the present application.

[0021] The present application also provides a storage medium, on which a computer executable program is stored, and when the computer executable program is executed, any method described in the present application is implemented.

[0022] The present application provides a method for evaluating the performance of R&D personnel, which includes the following steps: deploying a comprehensive performance evaluation model for R&D personnel based on a value calculation model, an output calculation model and a quality calculation model on a server; the value calculation model executes the following steps to calculate a value measurement value, which is used to characterize the work efficiency and problem-solving ability of the R&D personnel: obtaining the work task data completed by the R&D personnel, and calling a preset value measurement value calculation strategy to calculate the value measurement value; the output calculation model executes the following steps to calculate an output measurement value, which is used to characterize the code output efficiency of the R&D personnel: pulling the amount of code submitted by the R&D personnel to the git repository to calculate the code output; obtaining a preset output conversion rule and the number of attendance days obtained from the attendance system; calculating the output conversion rule according to the output conversion rule. , the attendance days, the code output, calculate the output efficiency; based on the preset output measurement rules, calculate the output measurement value according to the output efficiency; the quality calculation model performs the following steps to determine the quality measurement value, which is used to characterize the quality of the code of the R&D personnel: scan the code submitted by the R&D personnel based on the automatic code scanning kit to obtain the scanning result; determine the number of bugs and the number of vulnerabilities based on the scanning result; adjust the set basic quality measurement value according to the number of bugs and the number of vulnerabilities to obtain the quality measurement value; based on the preset comprehensive performance measurement benchmark value, the value measurement value, the output measurement value and the quality measurement value are integrated and calculated according to the preset weight ratio to obtain the comprehensive performance measurement value of the R&D personnel, and the comprehensive performance measurement value is used to characterize the performance of the R&D personnel. It improves the efficiency of collecting and processing the performance data of the R&D personnel, significantly reduces the investment of time cost, ensures the consistency and standardized processing of statistical data, and has comparability at the same time, and improves management efficiency, personnel work efficiency and personnel work quality through more accurate performance data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 This is a flow chart of a method for evaluating the effectiveness of R&D personnel in an embodiment of the present application; Figure 2 This is a flow chart of a method for evaluating the effectiveness of R&D personnel in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solution of the present application, the following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions 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 should fall within the scope of protection of this application.

[0026] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0027] Figure 1 This is a flow chart of a method for evaluating the effectiveness of R&D personnel according to an embodiment of the present application; Figure 1 As shown, the present application provides a method for evaluating the effectiveness of R&D personnel, which comprises the steps of: Deploy a comprehensive performance evaluation model for R&D personnel based on the value calculation model, output calculation model, and quality calculation model on the server; The value calculation model performs the following steps to calculate the value measurement value, which is used to characterize the work efficiency and problem-solving ability of R&D personnel: Obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation model performs the following steps to calculate the output metric value, which is used to characterize the code output efficiency of the developer: Pull the amount of code submitted by developers to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on the preset output measurement rule, according to the output efficiency, the output measurement value is calculated; The quality calculation model performs the following steps to determine a quality metric value, which is used to characterize the quality of the code of the developer: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; Based on a preset comprehensive performance measurement benchmark value, the value measurement value, output measurement value and quality measurement value are fused and calculated according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel. The comprehensive performance measurement value is used to characterize the performance of the R&D personnel.

[0028] In this embodiment, through automated data collection and processing, such as pulling the amount of code from the git repository, obtaining the number of attendance days from the attendance system, and detecting the quality of the code by the automatic code scanning suite, human intervention is reduced, making the evaluation process more objective and fair. This helps to eliminate subjective bias and ensure the accuracy and credibility of the evaluation results. In addition, the model comprehensively evaluates the effectiveness of R&D personnel from three dimensions: value, output, and quality, covering multiple aspects such as work efficiency, problem-solving ability, code output efficiency, and code quality. This multi-dimensional evaluation method can more comprehensively reflect the actual performance of R&D personnel and provide managers with richer decision-making basis.

[0029] Optionally, the acquiring of the work task data completed by the R&D personnel and calling a preset value measurement value calculation strategy to calculate the value measurement value includes: Obtaining the work task data completed by the R&D personnel, and obtaining the points for completed tasks and resolved bugs based on the work task data; Based on the points of the completed tasks and the points of the resolved bugs, a preset value metric calculation strategy is called to calculate the value metric; The value measurement value calculation strategy is: value measurement value = completed task points + resolved bug points.

[0030] Optionally, before obtaining the completed task points and resolved bug points, the following steps are also included: Obtain user stories created based on business requirements and tasks broken down based on the user stories; Attribute data of the task is obtained to determine the completed task points based on the attribute data of the task.

[0031] In this embodiment, by refining business requirements into user stories and further decomposing them into specific tasks, the R&D work can be made more refined and manageable. Each task has a clear goal and scope, which helps R&D personnel to better understand and execute. In addition, the attribute data of the task provides an objective basis for determining the points of completed tasks. This method reduces subjective judgment and makes the evaluation results more fair and accurate. The process of user story and task decomposition and the recording of task attribute data increase the transparency and traceability of the evaluation. Managers and R&D personnel can clearly see the source, execution process and evaluation results of each task, which helps to find problems and improve work. In addition, the value measurement value is calculated by combining the points of completed tasks and the points of resolved bugs obtained based on JIRA, which not only considers the code output efficiency of R&D personnel, but also their contribution to solving practical problems. This comprehensive measurement method can more accurately reflect the actual work efficiency of R&D personnel. Furthermore, through the analysis of user stories and task attribute data, bottlenecks and problems in the R&D process can be found, and improvement measures can be formulated. This continuous improvement mechanism helps to improve the overall efficiency and competitiveness of the team.

[0032] Optionally, determining the completed task points based on the attribute data of the task includes: Based on the task type, task difficulty and estimated processing time in the attribute data of the task, corresponding points are allocated to each task; The task attribute data includes task type and task difficulty; The task types include tasks or subtasks, and bug resolution; The task difficulty levels include high, medium, and low; The points are evaluated based on the man-days required for an intermediate consultant to complete a medium-difficulty task under standard conditions, with 1 point = 1 man-day. For high-difficulty tasks, the points are increased according to a preset ratio; for low-difficulty tasks, the points are reduced according to a preset ratio. The points of the resolved bug are calculated based on the generation and resolution of the bug. The specific rules are: obtain the bug maker ID and the solver ID to determine whether the bug maker and the solver are the same person. If they are the same person, no points are calculated; if they are not the same person, points are calculated for the solver.

[0033] In this embodiment, by comprehensively considering factors such as task type, task difficulty and expected processing time, corresponding points are allocated to each task, ensuring the fairness and objectivity of the evaluation. This method reduces the influence of subjective judgment, so that the value of different tasks can be measured relatively accurately. In addition, the man-days required for an intermediate consultant to complete a medium-difficulty task under standard conditions are used as the benchmark evaluation points, and the points are adjusted according to the different task difficulties. This method can more accurately reflect the complexity of the task and the required workload. At the same time, for the calculation of points for resolved bugs, by judging whether the maker and the solver of the bug are the same person, the repeated calculation of points caused by self-correction is avoided, and the accuracy is further improved. In addition, for high-difficulty tasks, the points are increased according to a preset ratio, which can motivate R&D personnel to challenge more complex tasks and improve work enthusiasm and creativity. Furthermore, by calculating points for the solver of the resolved bug but not for the maker, this method promotes the division of responsibilities in team collaboration and helps to detect the actual work value of R&D personnel. Further, this point allocation method based on task attribute data has high flexibility and scalability. As business needs change and team structures adjust, task types, difficulty levels, and point calculation rules can be easily adjusted to suit new situations. Finally, through regular review and analysis of task attribute data and point calculation rules, problems and deficiencies in the evaluation process can be discovered, and improvement measures can be formulated. This continuous improvement mechanism helps to continuously optimize the evaluation method and improve the accuracy and effectiveness of the evaluation.

[0034] Optionally, the pulling of the amount of code submitted by the developer to the git repository to calculate the amount of code output includes: Get the cumulative number of added and deleted lines of code submitted by R&D personnel to the git repository through the preset account; The code output is determined based on the cumulative number of added code lines and the cumulative number of deleted code lines.

[0035] Optionally, the determining of the code output based on the cumulative number of added code lines and the cumulative number of deleted code lines is specifically: The code output is obtained based on the following code output calculation formula: Code output = increase in code + reduction in code; Wherein, the amount of increased code = the cumulative number of increased code lines; The reduced code volume = the cumulative number of reduced code lines * the reduced code volume coefficient; The code reduction coefficient can have different values ​​configured by R&D personnel.

[0036] In this embodiment, by considering both the increase in code volume and the reduction in code volume, the technical implementation can more comprehensively reflect the code output of R&D personnel. Reducing the amount of code, such as refactoring and optimization, is also an important work result and should be included in the evaluation scope. The coefficient of reducing the amount of code is introduced, and the contribution of reducing the amount of code can be adjusted according to the specific situation. This flexibility enables the evaluation method to adapt to different project requirements, team culture and code quality standards. In addition, by incorporating the reduction of the amount of code into the evaluation scope and allowing its contribution to be adjusted by configuring the coefficient of reducing the amount of code, the technical implementation can motivate R&D personnel to pay more attention to code quality and maintainability, and encourage employees to refactor and optimize code more actively to improve the overall quality of code output. In addition, the code output is calculated based on the actual submission data in the git repository, which reduces the influence of subjective judgment and makes the evaluation results more objective and fair. The evaluation process is based on the actual submission data in the git repository, which is public and traceable, which helps to enhance the transparency of the evaluation results, so that both R&D personnel and managers can clearly understand the evaluation process and results. Furthermore, by regularly reviewing and adjusting the code reduction coefficient and analyzing the changing trend of code output, this technical implementation can support the team to continuously improve code quality and evaluation methods.

[0037] Optionally, the calculating the output efficiency according to the output conversion rule, the attendance days, and the code output volume includes: Obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount; The output efficiency is calculated based on the code output conversion amount and the attendance days.

[0038] Optionally, obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount includes the following steps: Obtaining the level data of the R&D personnel, and obtaining the corresponding job grade conversion coefficient based on the level data; Obtain the development language used by the R&D personnel, and obtain the corresponding language conversion coefficient based on the development language; The code output conversion amount is obtained based on the following code output conversion calculation formula: Code output conversion amount = code output amount * job level conversion coefficient * language conversion coefficient; The job grade conversion coefficient is set based on the level of the R&D personnel and can be modified as needed; The language conversion factor is set based on the development language used by the developer and can be modified as needed.

[0039] Optionally, the level data of the R&D personnel include: junior, intermediate, senior, expert; The job grade conversion coefficients corresponding to the initial configuration levels are as follows: junior: 1.0; intermediate: 1.0; senior: 1.0; expert: 1.0, and the job grade conversion coefficients can be modified as needed.

[0040] Optionally, the development language includes: JS, .NET, Python, Java, C, C++; The language conversion coefficients corresponding to the development languages ​​are initially configured as follows: JS: 0.9; .NET: 1.0; Python: 1.0; Java: 0.9; C: 1.0; C++: 1.0, and the language conversion coefficients can be modified as needed.

[0041] In this embodiment, through the job grade conversion coefficient and the language conversion coefficient, the R&D personnel of different levels and using different development languages ​​are evaluated differently. This differentiated evaluation takes into account the skill level of the R&D personnel and the complexity of the development language, making the evaluation result more fair and objective. In addition, the setting of the job grade conversion coefficient and the language conversion coefficient can motivate R&D personnel to improve their skill level and choose a more efficient development language. For example, due to the high job grade conversion coefficient, the code output conversion amount of senior or expert R&D personnel will also increase accordingly, thereby obtaining a higher output efficiency evaluation, and can also motivate R&D personnel to pay more attention to code quality and maintainability to improve their output efficiency evaluation. Similarly, using a more efficient or more respected development language by the team can also obtain a higher language conversion coefficient, further motivating R&D personnel to optimize technology selection. In addition, both the job grade conversion coefficient and the language conversion coefficient can be modified according to demand, which makes the evaluation method highly flexible. As the team structure, project requirements or technology trends change, these coefficients can be adjusted in time to adapt to new situations. Furthermore, by converting the code output in two dimensions, namely, job level and language, we can achieve refined management of the work results of R&D personnel. This refined management helps to more accurately evaluate the contribution of R&D personnel and provides strong support for team management and resource allocation. Finally, by regularly reviewing the job level conversion coefficient and language conversion coefficient and adjusting them according to needs, we can continuously optimize the evaluation method and improve the accuracy and effectiveness of the evaluation. This continuous improvement mechanism helps the team to continuously adapt to new technology trends and project requirements and maintain competitiveness.

[0042] Optionally, the output efficiency is calculated according to the code output conversion amount and the attendance days, and is specifically calculated based on the following output efficiency calculation rule: Output efficiency = code output conversion / attendance days; The output efficiency is used to represent the average converted output that employees can produce when they are on duty every day.

[0043] Optionally, the calculating the output measurement value based on the preset output measurement rule and according to the output efficiency specifically includes: If the output efficiency is <= 20, the output measure value is 10; If the output efficiency is >= 100, the output measure value is 60; If the output efficiency is between 20-100, the output measurement value = output efficiency * 0.6.

[0044] In this embodiment, the output efficiency is calculated according to the converted amount of code output and the number of attendance days, and the output measurement value is further calculated according to the output efficiency. The calculation formula of the output efficiency (output efficiency = converted amount of code output / number of attendance days) is intuitive and easy to understand, and can directly reflect the average converted output that employees can generate when they are on duty every day. This intuitiveness helps managers quickly understand the work efficiency and output capacity of employees. In addition, by combining the output efficiency with the preset output measurement rules, a standardized evaluation of employee work output is achieved. This standardized evaluation helps to reduce the influence of subjective judgment and makes the evaluation results more objective and fair. Furthermore, the setting of the output measurement value, such as the output measurement value of 10 when the output efficiency is <= 20, and the output measurement value of 60 when the output efficiency is >= 100, provides employees with a clear incentive and feedback mechanism. Employees can clearly see the relationship between their output efficiency and output measurement value, so as to adjust their work status and methods to improve output efficiency. Furthermore, by regularly calculating and analyzing output efficiency and output measurement values, managers can understand the changing trends and existing problems of employees' work efficiency, which helps to formulate targeted improvement measures and promote the continuous improvement of employees and teams. Finally, output efficiency and output measurement values ​​can serve as an important basis for managers to make decisions. For example, in terms of employee promotion, bonus distribution or project resource allocation, you can refer to the output efficiency and output measurement values ​​of employees to make more reasonable and scientific decisions.

[0045] Optionally, scanning the code submitted by the developer based on the automatic code scanning suite to obtain a scanning result; and determining the number of bugs and vulnerabilities based on the scanning result specifically comprises the following steps: Configure the system front-end and back-end automated static code scanning suite in the continuous testing service under the project; Scanning the code submitted by the developer according to a preset period based on the scanning suite to obtain a scanning result; Based on the scan results, the number of bugs and the number of vulnerabilities are determined.

[0046] Optionally, the adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value specifically includes: Get the set basic quality metric value; Obtaining bug type data, and obtaining a corresponding bug deduction coefficient based on the bug type data; Obtain vulnerability type data, and obtain a corresponding vulnerability deduction coefficient based on the vulnerability type data; Calculate the total Bug deduction by multiplying the number of different types of bugs by the corresponding Bug deduction coefficient. Calculate the total vulnerability deduction score by multiplying the number of different types of vulnerabilities by the corresponding vulnerability deduction coefficient and summing them up; The quality metric value is calculated based on the following quality metric value calculation formula: Quality metric value = basic quality metric value - total bug deduction points - total vulnerability deduction points.

[0047] Optionally, the basic quality metric value is set to 20 as a starting reference point for code quality assessment, and the basic quality setting value can be adjusted according to demand.

[0048] Optionally, the Bug type data and the vulnerability type data both include: blocking, serious, and minor; The initial values ​​of the corresponding blocking, serious, and minor types of bug deduction coefficients and blocking, serious, and minor types of vulnerability deduction coefficients are all set to 1.0, and can be dynamically adjusted through the configuration interface or interface as needed.

[0049] In this embodiment, using automated scanning tools such as SonarCube to scan the code can accurately identify bugs and vulnerabilities in the code, including those that may be difficult to find through manual review, reducing the time and cost of manual review, and R&D personnel can get feedback faster and fix problems in time, thereby accelerating the development process, which helps to ensure the stability and reliability of code quality. In addition, by converting the number and type of bugs and vulnerabilities into specific deduction coefficients, this technical implementation provides a quantifiable evaluation standard for code quality, which makes the quality metric an intuitive and comparable indicator, which helps managers and team members understand the actual situation of code quality. In addition, the basic quality metric, the bug deduction coefficient and the vulnerability deduction coefficient can all be adjusted according to demand. This flexibility enables the technical implementation to adapt to the code quality assessment needs of different projects, different teams or different stages. Furthermore, by classifying bugs and vulnerabilities according to their severity and assigning different deduction coefficients, this technical implementation helps to identify and manage high-risk issues in the code, and helps the team prioritize those issues that may have a significant impact on the project, thereby reducing the risk of project failure. At the same time, automated scanning and quantitative evaluation provide the team with an opportunity for continuous improvement. By regularly scanning and evaluating code quality, the team can promptly discover and correct problems, thereby continuously improving code quality and development efficiency. Finally, by focusing on vulnerabilities and security issues in the code, this technical implementation helps to enhance the code security awareness of team members, reduce potential risks caused by security vulnerabilities, and protect the security and stability of the project. Quality metrics can serve as an important basis for managers to make decisions. When evaluating project progress, formulating reward mechanisms, or allocating resources, managers can refer to quality metrics to make more reasonable and scientific decisions.

[0050] Optionally, based on the preset comprehensive performance measurement benchmark value, the value measurement value, the output measurement value and the quality measurement value are integrated and calculated according to a preset weight ratio to obtain the comprehensive performance measurement value of the R&D personnel, including: Get the set comprehensive performance measurement benchmark value of 100 points; The value measurement value, output measurement value and quality measurement value are assigned values ​​according to a preset weight ratio, specifically: The value measurement value accounts for 20% of the comprehensive effectiveness measurement benchmark value; The output measurement value accounts for 60% of the comprehensive performance measurement benchmark value, and the full score of the output measurement value is set to 60 points accordingly; The quality metric value accounts for 20% of the comprehensive performance metric benchmark value, and the basic quality metric value is set at 20 points accordingly; The value measurement value, the output measurement value and the quality measurement value are added together to obtain a comprehensive performance measurement value of the R&D personnel.

[0051] In this embodiment, each indicator is assigned a value by a preset weight ratio, which ensures the objectivity and fairness of the evaluation process, and the importance of each dimension is reasonably reflected, avoiding the influence of subjective bias on the evaluation results. Although the comprehensive performance measurement benchmark value is set to 100 points, the value measurement value will fluctuate around 20, and it is allowed to exceed the limit of 100 points. The full score is unlimited, which means that for R&D personnel who are particularly outstanding in value creation, their comprehensive performance measurement value can exceed the comprehensive performance measurement benchmark value, thereby more flexibly reflecting their actual contribution. In addition, clear scoring standards and weight ratios can motivate R&D personnel to work hard to improve their performance in different dimensions, so that employees know which aspects are important and how to improve their comprehensive performance measurement value by improving these aspects, thereby enhancing work enthusiasm and motivation. Finally, the enterprise can help enterprises improve the management efficiency of the R&D team and reduce the cost of communication and reporting based on the performance data of different dimensions in real time, and make timely improvement measures for the aspects that may be insufficient after the performance data analysis.

[0052] Optionally, a multi-dimensional analysis is performed based on the collected comprehensive performance measurement data, including: Conduct statistical analysis on the overall effectiveness of teams, projects, and departments; Conduct horizontal comparative performance analysis based on R&D personnel with different roles, levels, and expertise; By customizing and optimizing the evaluation model, a personalized evaluation plan is formulated according to the actual situation and characteristics of each R&D personnel to convert the performance of R&D personnel into quantifiable indicators.

[0053] like Figure 2 As shown, in a possible implementation of the method for evaluating the effectiveness of R&D personnel, the specific steps are as follows: Step 1: System initialization and configuration 1.1 Configure the data interface in the performance analysis system to ensure that the system can access data from JIRA, Git repository, and SonarCube.

[0054] 1.2 Set the time window for data crawling, and select a period when the system load is low and the data is relatively stable for automatic crawling, such as early morning every night.

[0055] 1.3 Establish a personal account for each R&D personnel to record whether they have enabled performance scoring functions such as statistical points, code volume statistics, and static scanning.

[0056] Step 2: Automatic data capture 2.1 According to the preset time, the system starts the scheduled task and captures the task / defect story points of the R&D personnel from JIRA.

[0057] 2.2 At the same time, the number of added / deleted code lines of each R&D staff in the specified time period is captured from the Git repository.

[0058] 2.3 If the static scanning function is enabled, the static scanning results, including the number of bugs and vulnerabilities, are obtained from SonarCube.

[0059] Step 3: Data Storage 3.1 Store the data captured from JIRA, Git repository and SonarCube in the system database for subsequent calculations.

[0060] Step 4: Calculation of performance metrics 4.1 Value measurement calculation: Check the personnel records. If the statistical points function is turned on, the value measurement value of each R&D personnel is calculated based on the task / defect story points captured in JIRA and the preset value calculation model formula is applied.

[0061] If the point counting function is not enabled, skip this step and do not calculate the value measurement value.

[0062] 4.2 Output measurement value calculation: Check the personnel ledger. If the code volume statistics function is turned on, the output measurement value is calculated based on the number of added / deleted code lines captured from the Git repository using the preset output calculation model formula.

[0063] If the code volume statistics function is not enabled, skip this step and do not calculate the output metric value.

[0064] 4.3 Quality metric calculation: Check the personnel ledger. If the static scanning function is turned on, the quality metric value is calculated based on the number of bugs and vulnerabilities in SonarCube using the preset quality metric value calculation model formula.

[0065] If the static scanning function is not enabled, this step is skipped and the quality metric value is not calculated.

[0066] Step 5: Calculation and display of comprehensive performance measurement values 5.1 The value measurement value, output measurement value and quality measurement value are assigned initial values ​​according to the preset weights, such as 20% for value, 60% for output and 20% for quality, and the calculation results of the value measurement value, output measurement value and quality measurement value are summed to obtain the comprehensive performance measurement value of each R&D personnel.

[0067] 5.2 The system interface displays the comprehensive performance measurement value of each R&D personnel and the details of each measurement value, and supports filtering and comparison by time range, project, team and other dimensions.

[0068] This embodiment realizes a comprehensive and flexible evaluation of the comprehensive effectiveness of R&D personnel by automatically integrating multiple data sources. It ensures the accuracy and pertinence of the evaluation results through personalized configuration and dynamic adjustment of evaluation parameters, providing strong management decision support for enterprises. It realizes an automated and systematic evaluation of the comprehensive effectiveness of R&D team members, providing strong support for management decisions.

[0069] The present application also provides a research and development personnel effectiveness evaluation system, including: A comprehensive performance evaluation module, which includes a value calculation module, an output calculation module, a quality calculation module, and a comprehensive processing module; The value calculation module is used to calculate the value measurement value, specifically including: obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation module is used to calculate the output measurement value, specifically including: pulling the amount of code submitted by the R&D personnel to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on a preset output measurement rule, according to the output efficiency, calculating the output measurement value; The quality calculation module is used to calculate the quality metric value, specifically including: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; The comprehensive processing module, based on a preset comprehensive performance measurement benchmark value, fuses and calculates the value measurement value, output measurement value and quality measurement value according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel.

[0070] In another embodiment, the value calculation module is specifically used to: obtain the work task data completed by the R&D personnel, and obtain the points for completed tasks and the points for resolved bugs based on the work task data; based on the points for completed tasks and the points for resolved bugs, call the preset value measurement value calculation strategy to calculate the value measurement value; the value measurement value calculation strategy is: value measurement value = completed task points + resolved bug points.

[0071] In another embodiment, the value calculation module is specifically used to: before obtaining the completed task points and the resolved bug points, perform the steps of: obtaining user stories created according to business requirements and tasks decomposed based on the user stories; obtaining attribute data of the tasks to determine the completed task points based on the attribute data of the tasks; The determining of the points of completed tasks based on the attribute data of the tasks includes: allocating corresponding points to each task based on the task type, task difficulty and estimated processing time in the attribute data of the tasks; the task attribute data includes the task type and task difficulty; the task type includes tasks or subtasks, and bug resolution; Among them, the task difficulty levels include high, medium and low; the points are evaluated based on the man-days required for an intermediate consultant to complete a medium-difficulty task under standard conditions, and 1 point is preset = 1 man-day; for high-difficulty tasks, the points increase according to a preset ratio; for low-difficulty tasks, the points decrease according to a preset ratio; the points for resolved bugs are calculated based on the generation and resolution of the bugs, and the specific rules are: obtain the bug maker ID and solver ID to determine whether the bug maker and solver are the same person. If they are the same person, no points are calculated; if they are not the same person, points are calculated for the solver.

[0072] In another embodiment, the output calculation module is specifically used to: obtain the cumulative number of added code lines and the cumulative number of deleted code lines submitted by R&D personnel to the git repository through a preset account; and determine the code output based on the cumulative number of added code lines and the cumulative number of deleted code lines.

[0073] In another embodiment, the output calculation module is specifically used to: determine the code output based on the cumulative number of added code lines and the cumulative number of deleted code lines, specifically: the code output is obtained based on the following code output calculation formula: code output = increased code amount + reduced code amount; Among them, the increased code volume = the cumulative increased number of code lines; the reduced code volume = the cumulative reduced number of code lines * the code volume reduction coefficient; the code volume reduction coefficient can be configured with different values ​​based on R&D personnel.

[0074] In another embodiment, the output calculation module is specifically used to: obtain the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, convert the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount; calculate the output efficiency based on the code output conversion amount and the attendance days.

[0075] Among them, the obtaining of the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount, includes: obtaining the level data of the R&D personnel, and obtaining the corresponding job grade conversion coefficient based on the level data; obtaining the development language used by the R&D personnel, and obtaining the corresponding language conversion coefficient based on the development language; the code output conversion amount is obtained based on the following code output conversion calculation formula: code output conversion amount = code output amount * job grade conversion coefficient * language conversion coefficient; the job grade conversion coefficient is set based on the level of the R&D personnel and can be modified according to needs; the language conversion coefficient is set based on the development language used by the R&D personnel and can be modified according to needs.

[0076] Among them, the level data of the R&D personnel include: junior, intermediate, senior, and expert; the job grade conversion coefficients corresponding to the initial configuration of the levels are as follows: junior: 1.0; intermediate: 1.0; senior: 1.0; expert: 1.0, and the job grade conversion coefficients can be modified according to needs.

[0077] Among them, the development languages ​​include: JS, .NET, Python, Java, C, C++; the language conversion coefficients corresponding to the initial configuration of the development languages ​​are as follows: JS: 0.9; .NET: 1.0; Python: 1.0; Java: 0.9; C: 1.0; C++: 1.0, and the language conversion coefficients can be modified according to needs.

[0078] Among them, the output efficiency is calculated according to the code output conversion amount and the attendance days, and is specifically calculated based on the following output efficiency calculation rule: output efficiency = code output conversion amount / attendance days; the output efficiency is used to represent the average converted output that an employee can generate when he / she is on duty every day.

[0079] In another embodiment, the output calculation module is specifically used to: calculate the output measurement value based on the preset output measurement rule and according to the output efficiency, specifically including: if the output efficiency <= 20, the output measurement value is 10; if the output efficiency >= 100, the output measurement value is 60; if the output efficiency is between 20-100, the output measurement value = output efficiency * 0.6.

[0080] In another embodiment, the quality calculation module is specifically used to: configure a system front-end and back-end automated static code scanning suite in a continuous testing service under a project; scan the code submitted by the developer according to a preset cycle based on the scanning suite to obtain a scanning result; determine the number of bugs and vulnerabilities based on the scanning result; In another embodiment, the quality calculation module is specifically used to: adjust the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value, specifically including: obtaining the set basic quality metric value; obtaining bug type data, and obtaining the corresponding bug deduction coefficient based on the bug type data; obtaining vulnerability type data, and obtaining the corresponding vulnerability deduction coefficient based on the vulnerability type data; calculating the total bug deduction by multiplying the number of different types of bugs by the corresponding bug deduction coefficients and summing them up; calculating the total vulnerability deduction by multiplying the number of different types of vulnerabilities by the corresponding vulnerability deduction coefficients and summing them up; calculating the quality metric value based on the following quality metric value calculation formula: quality metric value = basic quality metric value - total bug deduction - total vulnerability deduction.

[0081] The basic quality metric value is set to 20 as a starting reference point for code quality assessment, and the basic quality setting value can be adjusted according to demand.

[0082] Among them, the Bug type data and the vulnerability type data both include: blocking, serious, and minor; the corresponding blocking, serious, and minor types of Bug deduction coefficients and blocking, serious, and minor types of vulnerability deduction coefficients are initially set to 1.0, and can be dynamically adjusted through the configured interface or interface as needed.

[0083] In another embodiment, the comprehensive processing module is used to fuse and calculate the value measurement value, output measurement value and quality measurement value according to a preset weight ratio based on a preset comprehensive performance measurement benchmark value to obtain a comprehensive performance measurement value of the R&D personnel, specifically including: obtaining a set comprehensive performance measurement benchmark value of 100 points; assigning values ​​to the value measurement value, output measurement value and quality measurement value according to a preset weight ratio, specifically: the value measurement value accounts for 20% of the comprehensive performance measurement benchmark value; the output measurement value accounts for 60% of the comprehensive performance measurement benchmark value, and the full score of the output measurement value is set to 60 points; the quality measurement value accounts for 20% of the comprehensive performance measurement benchmark value, and the basic quality measurement value is set to 20 points; the value measurement value, the output measurement value and the quality measurement value are added to obtain the comprehensive performance measurement value of the R&D personnel.

[0084] In another embodiment, the comprehensive processing module is specifically used to: conduct multi-dimensional analysis based on the collected comprehensive performance measurement data, specifically including: statistical analysis of the overall performance of teams, projects, and departments; horizontal comparative performance analysis based on R&D personnel of different roles, levels, and professional skills; and formulate personalized evaluation plans based on the actual situation and characteristics of each R&D personnel by customizing and optimizing the evaluation model, so as to convert the performance of the R&D personnel into quantifiable indicators.

[0085] The present application also provides an electronic device, including: a memory and a processor, wherein the memory stores a computer executable program, and the processor is used to execute the computer executable program to implement any one of the methods in the present embodiment.

[0086] The present application also provides a computer storage medium, on which a computer executable program is stored. When the computer executable program is executed, the method described in any one of the embodiments is implemented.

[0087] It should be noted that the same and similar parts between the various embodiments in this specification can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the modules described as separate components may or may not be physically separated, and the components indicated as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without paying creative labor.

[0088] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for evaluating the effectiveness of R&D personnel, characterized in that: Includes steps: Deploy a comprehensive performance evaluation model for R&D personnel based on the value calculation model, output calculation model, and quality calculation model on the server; The value calculation model performs the following steps to calculate the value measurement value, which is used to characterize the work efficiency and problem-solving ability of R&D personnel: Obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation model performs the following steps to calculate the output metric value, which is used to characterize the code output efficiency of the R&D personnel: Pull the amount of code submitted by developers to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on the preset output measurement rule, according to the output efficiency, the output measurement value is calculated; The quality calculation model performs the following steps to determine a quality metric value, which is used to characterize the quality of the code of the developer: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; Based on a preset comprehensive performance measurement benchmark value, the value measurement value, output measurement value and quality measurement value are fused and calculated according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel. The comprehensive performance measurement value is used to characterize the performance of the R&D personnel.

2. The R&D personnel performance evaluation method according to claim 1, characterized in that: The obtaining of the work task data completed by the R&D personnel and calling a preset value measurement value calculation strategy to calculate the value measurement value includes: Obtaining the work task data completed by the R&D personnel, and obtaining the points for completed tasks and resolved bugs based on the work task data; Based on the points of the completed tasks and the points of the resolved bugs, a preset value metric calculation strategy is called to calculate the value metric; The value measurement value calculation strategy is: value measurement value = completed task points + resolved bug points.

3. The R&D personnel performance evaluation method according to claim 1, characterized in that: The calculating of the output efficiency according to the output conversion rule, the attendance days, and the code output volume includes: Obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount; The output efficiency is calculated based on the code output conversion amount and the attendance days.

4. The R&D personnel performance evaluation method according to claim 3, characterized in that: The step of obtaining the job grade conversion coefficient of the R&D personnel and the language conversion coefficient of the language used for development, and converting the code output by the job grade conversion coefficient and the language conversion coefficient to obtain the code output conversion amount includes the following steps: Obtaining the level data of the R&D personnel, and obtaining the corresponding job grade conversion coefficient based on the level data; Obtain the development language used by the R&D personnel, and obtain the corresponding language conversion coefficient based on the development language; The code output conversion amount is obtained based on the following code output conversion calculation formula: Code output conversion amount = code output amount * job level conversion coefficient * language conversion coefficient; The job grade conversion coefficient is set based on the level of the R&D personnel and can be modified as needed; The language conversion factor is set based on the development language used by the developer and can be modified as needed.

5. The R&D personnel performance evaluation method according to claim 1, characterized in that: The calculating the output measurement value based on the preset output measurement rule and according to the output efficiency specifically includes: If the output efficiency is <= 20, the output measure value is 10; If the output efficiency is >= 100, the output measure value is 60; If the output efficiency is between 20-100, the output measurement value = output efficiency * 0.

6.

6. The R&D personnel performance evaluation method according to claim 1, characterized in that: The adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value specifically includes: Get the set basic quality metric value; Obtaining bug type data, and obtaining a corresponding bug deduction coefficient based on the bug type data; Obtain vulnerability type data, and obtain a corresponding vulnerability deduction coefficient based on the vulnerability type data; Calculate the total Bug deduction by multiplying the number of different types of bugs by the corresponding Bug deduction coefficient. Calculate the total vulnerability deduction score by multiplying the number of different types of vulnerabilities by the corresponding vulnerability deduction coefficient and summing them up; The quality metric value is calculated based on the following quality metric value calculation formula: Quality metric value = basic quality metric value - total bug deduction points - total vulnerability deduction points.

7. The R&D personnel performance evaluation method according to claim 1, characterized in that: Based on the preset comprehensive performance measurement benchmark value, the value measurement value, output measurement value and quality measurement value are integrated and calculated according to the preset weight ratio to obtain the comprehensive performance measurement value of the R&D personnel, including: Get the set comprehensive performance measurement benchmark value of 100 points; The value measurement value, output measurement value and quality measurement value are assigned values ​​according to a preset weight ratio, specifically: The value measurement value accounts for 20% of the comprehensive effectiveness measurement benchmark value; The output measurement value accounts for 60% of the comprehensive performance measurement benchmark value, and the full score of the output measurement value is set to 60 points accordingly; The quality metric value accounts for 20% of the comprehensive performance metric benchmark value, and the basic quality metric value is set at 20 points accordingly; The value measurement value, the output measurement value and the quality measurement value are added together to obtain a comprehensive performance measurement value of the R&D personnel.

8. A R&D personnel performance evaluation system, characterized in that: include: A comprehensive performance evaluation module, which includes a value calculation module, an output calculation module, a quality calculation module, and a comprehensive processing module; The value calculation module is used to calculate the value measurement value, specifically including: obtaining the work task data completed by the R&D personnel, and calling the preset value measurement value calculation strategy to calculate the value measurement value; The output calculation module is used to calculate the output measurement value, specifically including: pulling the amount of code submitted by the R&D personnel to the git repository to calculate the code output; Obtain the preset output conversion rules and attendance days obtained from the attendance system; Calculate the output efficiency according to the output conversion rule, the attendance days, and the code output; Based on the preset output measurement rule, according to the output efficiency, the output measurement value is calculated; The quality calculation module is used to calculate the quality metric value, specifically including: Scan the code submitted by the developer based on the automatic code scanning suite to obtain the scanning results; Based on the scan results, determine the number of bugs and the number of vulnerabilities; Adjusting the set basic quality metric value according to the number of bugs and the number of vulnerabilities to obtain the quality metric value; The comprehensive processing module, based on a preset comprehensive performance measurement benchmark value, fuses and calculates the value measurement value, output measurement value and quality measurement value according to a preset weight ratio to obtain a comprehensive performance measurement value of the R&D personnel.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer executable program, and the processor is used to execute the computer executable program to implement the method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a computer executable program, and the computer executable program implements the method according to any one of claims 1 to 7 when executed.

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