Personal research and development efficiency improvement method and system and medium

Abstract

The invention provides an individual research and development efficiency improvement method and system and a medium, and belongs to the technical field of research and development efficiency evaluation, and the method comprises the following steps: obtaining a code which is submitted by a to-be-evaluated individual and is combined with a review request; determining a continuous integration score, an automatic test score, a code normalization score and a code reusability score of the codes according to the number of the codes submitted by the to-be-evaluated individual, an integration condition, a test condition of an automatic test script, a static scanning result and a calling condition of the packaged codes in a fixed period; performing weighting coefficient distribution on the codes according to the influence factors of the codes in each practical application result to obtain a weighted sum score; and obtaining the review opinion adoption rate of the to-be-evaluated individual, and determining an efficiency comprehensive evaluation result according to the weighted sum score and the result of the review opinion adoption rate. According to the method, behaviors and corresponding results of research and development personnel can be accurately analyzed, and targeted implementation of an efficiency improvement plan is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of R&D efficiency evaluation, and in particular to a method for improving personal R&D efficiency. Background Art

[0002] With the continuous iteration and update of software development models, especially the emergence of large-scale agile systems and DevOps integrated development and operation systems in recent years, both Internet companies and traditional software industries need a set of technical methods to analyze the performance status of individual R&D personnel, find bottlenecks and improve them, so as to promote the entire team to achieve the expected performance goals.

[0003] R&D performance analysis plays an important role in the field of software development and technological innovation. It is not only a key indicator for measuring the work efficiency and output quality of R&D personnel, but also an important tool for promoting team collaboration, optimizing resource allocation, and improving overall R&D performance. The existing performance improvement methods rely heavily on the human judgment of reviewers. This subjective judgment model has many limitations. First, human judgment inevitably carries subjective bias and individual differences, which may lead to deviations in the performance evaluation results of the same R&D personnel or the same R&D project, affecting the accuracy and fairness of the evaluation. Second, subjective judgment is difficult to fully and objectively reflect the actual performance status of R&D personnel. The work of R&D personnel often involves multiple aspects, including technological innovation ability, team collaboration ability, project management ability, etc., and the performance of these aspects is difficult to be fully measured through a single subjective judgment. Therefore, the existing performance improvement methods may not be able to accurately capture the actual performance of R&D personnel, resulting in one-sidedness and incompleteness of the evaluation results. In addition, with the increasing complexity and diversity of R&D work, the work performance of R&D personnel has also become more diversified. Traditional performance improvement methods often have difficulty adapting to such changes and are unable to dynamically and real-time monitor and evaluate the performance of R&D personnel, which further limits the effectiveness of existing methods in characterizing the actual performance status of R&D personnel.

[0004] In summary, the current performance improvement methods mainly rely on the human judgment of reviewers. Subjective judgment is inaccurate and cannot effectively represent the actual performance status of current R&D personnel. Summary of the invention

[0005] To solve the above problems, the present invention provides a method for improving personal R&D efficiency, which can accurately analyze the behavior of R&D personnel and the corresponding results, and help to implement the efficiency improvement plan in a targeted manner later.

[0006] To achieve the above object, the present invention provides the following technical solutions.

[0007] A method for improving personal R & D efficiency includes the following steps:

[0008] Obtain the code of the PullRequest merged into the review request submitted by the individual to be evaluated;

[0009] Determine the continuous integration score, automated test score, code standardization score, and code reuse degree score of the code according to the number of codes submitted by the individual to be evaluated, the integration situation, the test situation of the automated test script, the static scan result, and the call situation of the encapsulated code within a fixed period;

[0010] Respectively allocate weighted coefficients to the continuous integration score, automated test score, code standardization score, and code reuse degree score of the code according to the influencing factors of the actual application results of the code to obtain the weighted total score; obtain the acceptance rate of the review opinions of the individual to be evaluated, and determine the comprehensive efficiency evaluation result according to the results of the weighted total score and the acceptance rate of the review opinions;

[0011] According to the comprehensive efficiency evaluation result, conduct efficiency tracking on individuals whose comprehensive efficiency evaluation results do not meet the preset conditions, and respectively construct efficiency improvement plans in terms of efficiency, quality, standardization, and code reuse.

[0012] Preferably, the obtaining of the continuous integration score of the code includes the following steps:

[0013] Obtain the number of codes submitted by the individual to be evaluated and the integration situation, and determine the minimum number of code submissions per day and the continuous integration duration;

[0014] According to the minimum number of code submissions per day and the continuous integration duration, determine the code submission frequency score and the continuous integration result score of the code submitted by the individual to be evaluated based on the preset minimum number of code submissions per day threshold and the continuous integration duration threshold after new code submission; among them, corresponding score deductions are made when the number of code submissions per day is lower than the threshold and the continuous integration duration is higher than the threshold;

[0015] Respectively allocate weighted coefficients to the code submission frequency score and the continuous integration result score according to the influencing factors of the actual application results of the code, and determine the continuous integration score of the code of the individual to be evaluated.

[0016] Preferably, the obtaining of the automated test score includes the following steps:

[0017] Obtain the code submitted by the individual to be evaluated, trigger the continuous integration pipeline, and continuously execute the automated test script or the automated test result on the code submitted by the individual to be evaluated in sequence;

[0018] Judge whether it affects the core functions of the system according to the automated test results, and count the execution pass rate of the automated test cases. Respectively obtain the number of serious defects, the number of general defects, and the number of minor defects.

[0019] According to the impact factors of the defect degree on the code quality, assign weighted coefficients to the number of serious defects, the number of general defects, and the number of minor defects respectively, and determine the code quality score of the individual to be evaluated.

[0020] Preferably, the obtaining of the code standardization score includes the following steps:

[0021] Obtain the code submitted by the individual to be evaluated.

[0022] Continuously perform static scans on the code submitted by the individual to be evaluated in sequence to obtain static scan results; the static scan results include the number of code smells, the number of security vulnerabilities, complexity, and duplication rate.

[0023] According to the impact factors of each static scan result, assign weighted coefficients to the scores of the number of code smells, the number of security vulnerabilities, complexity, and duplication rate respectively, and determine the code standardization score of the individual to be evaluated.

[0024] Preferably, the obtaining of the code reuse degree score includes the following steps:

[0025] Obtain the code submitted by the individual to be evaluated, and encapsulate the common functions of the code submitted by the individual to be evaluated into classes, methods, and functions.

[0026] Count the number of times the encapsulated code is called by other developers within a fixed period, the reuse times of function-level reuse, method-level reuse, component-level reuse, and suite-level reuse.

[0027] Average the weighted coefficients for function-level reuse, method-level reuse, component-level reuse, and suite-level reuse, and determine the code reuse degree score.

[0028] Preferably, the review opinion adoption rate is the adoption score of the satisfaction degree of the individual to be evaluated with the results of the manual review opinions; determine the comprehensive evaluation result of the efficiency by summing the weighted total score and the satisfaction degree adoption score.

[0029] Preferably, it also includes determining an efficiency improvement plan according to the comprehensive evaluation result of the efficiency, including the following steps:

[0030] Obtain the comprehensive evaluation result of the efficiency of the code of the individual to be evaluated, conduct efficiency tracking on the individuals whose comprehensive evaluation results of the efficiency do not meet the preset conditions, and respectively construct efficiency improvement plans in terms of efficiency, quality, standardization, and code reuse.

[0031] The efficiency improvement plan adopts real-time reminders for individuals to submit code for continuous integration, counts the number of code submissions and the duration of code integration, and intercepts code submissions that do not meet the completion standard DOD.

[0032] The quality improvement plan adopts automated testing of the code in the development environment using the Jenkins pipeline before merging it into the main branch; determines whether to allow the submission of a PullRequest request based on the results of the automated testing.

[0033] The standardization improvement plan adopts hook program checks on the code submitted by individuals, reports errors and gives requirement prompts when the submission format does not conform; performs static scanning on the code submitted by individuals and outputs the static scanning results.

[0034] The code reuse improvement plan pushes files, code blocks, and methods / functions with a high duplication rate in the code submitted by individuals, and through AIGC-related capabilities, guides developers to complete code refactoring, reduces the code duplication rate, and completes unified encapsulation and call management.

[0035] Preferably, the efficiency, quality, standardization, and code reuse improvement plans include the following: Efficiency improvement plan: Real-time reminders for individuals to submit code for continuous integration, counts the number of code submissions and the duration of code integration, and intercepts code submissions that do not meet the completion standard DOD.

[0036] Quality improvement plan: Performs automated testing of the code in the development environment using the Jenkins pipeline before merging it into the main branch; determines whether to allow the submission of a PullRequest request based on the results of the automated testing.

[0037] Standardization improvement plan: Performs hook program checks on the code submitted by individuals, reports errors and gives requirement prompts when the submission format does not conform; performs static scanning on the code submitted by individuals and outputs the static scanning results.

[0038] Code reuse improvement plan: Pushes files, code blocks, and methods / functions with a high duplication rate in the code submitted by individuals, and through AIGC-related capabilities, guides developers to complete code refactoring, reduces the code duplication rate, and completes unified encapsulation and call management.

[0039] A personal R & D efficiency analysis system, the system includes:

[0040] A processor;

[0041] A memory, on which a computer program that can run on the processor is stored;

[0042] Wherein, when the computer program is executed by the processor, the steps of the personal R & D efficiency improvement method are implemented.

[0043] A computer-readable storage medium, on which a data processing program is stored. When the data processing program is executed by a processor, the steps of the personal R & D efficiency improvement method are implemented.

[0044] Advantages of the present invention:

[0045] The present invention provides a personal R & D efficiency improvement method, system and medium. The method provides a method and an efficiency platform for accurate analysis and improvement of personal R & D efficiency. By using methods such as automatic script testing and static scanning, accurate code quality analysis is automatically performed on the code submitted by R & D personnel. Combining the collection of application situation data of the code for comprehensive analysis and judgment, effective evaluation information such as the time of code submission, the frequency of code submission, the success rate of triggering builds, the number of code scanning odors, the code complexity, and the one-time passing rate of testing is determined. More objective and accurate analysis of the R & D behaviors of R & D personnel and the corresponding R & D results is realized, solving the problem of subjective judgment existing in the existing manual review, which affects the accuracy of personal R & D efficiency analysis. Based on the comprehensive evaluation result of efficiency, the efficiency of individuals whose comprehensive evaluation result of efficiency does not meet the preset conditions is tracked, and efficiency improvement plans in terms of efficiency, quality, standardization, and code reuse are respectively constructed to improve the capabilities of developers in all aspects. Description of the Drawings

[0046] Figure 1 is the overall analysis flowchart of the personal R & D efficiency improvement method in the embodiment of the present invention;

[0047] Figure 2 is the personal R & D efficiency evaluation flowchart of the personal R & D efficiency improvement method in the embodiment of the present invention;

[0048] Figure 3 is the expert review execution evaluation flowchart of the personal R & D efficiency improvement method in the embodiment of the present invention;

[0049] Figure 4 is the efficiency improvement plan execution step flowchart of the personal R & D efficiency improvement method in the embodiment of the present invention;

[0050] Figure 5 is the personal efficiency improvement tracking flowchart of the personal R & D efficiency improvement method in the embodiment of the present invention. Detailed Embodiments

[0051] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0052] Embodiment 1

[0053] The analysis of R & D efficiency plays a crucial role in the fields of software development and technological innovation. It is not only a key indicator for measuring the work efficiency and output quality of R & D personnel, but also an important tool for promoting team collaboration, optimizing resource allocation, and enhancing overall R & D efficiency. The efficiency analysis of individual R & D can help accurately evaluate the work performance of each person. Through quantitative analysis, such as code submission frequency, defect repair speed, task completion rate, etc., managers can clearly understand the actual contributions of each R & D personnel, so as to make more fair performance evaluations. Efficiency analysis can reveal the bottlenecks and weaknesses in the R & D process. Through in-depth analysis of individual efficiency, the team can discover and solve the key factors affecting work efficiency, such as insufficient skills, cumbersome processes, or inefficient tools. This helps the team continuously optimize the work process and improve overall R & D efficiency. Moreover, the efficiency analysis of individual R & D is crucial for promoting team collaboration. By sharing efficiency data, team members can more clearly understand their respective strengths and weaknesses, and then form a good atmosphere of mutual complementarity and assistance. At the same time, this also helps to stimulate the enthusiasm and creativity of team members and jointly promote the project forward.

[0054] However, the existing methods for improving efficiency mainly focus on the overall goals of the team, lacking methods for R & D efficiency analysis, feedback, and improvement for individuals. They cannot systematically help each person in the team find specific matters to be improved and cannot effectively improve individual R & D efficiency.

[0055] Therefore, a method for improving individual R & D efficiency of the present invention has an overall evaluation flowchart as Figure 1 shown, and the specific steps are as follows:

[0056] S1: Obtain the code of the Pull Request merged into the review request submitted by the individual to be evaluated.

[0057] S2: Determine the continuous integration score, automated test score, code standardization score, and code reuse degree score of the code according to the number of codes submitted by the individual to be evaluated, the integration situation, the test situation of the automated test script, the static scan result, and the call situation of the packaged code within a fixed period. The specific R & D efficiency evaluation flowchart is as Figure 2 shown.

[0058] Specifically:

[0059] S2.1: Obtaining the continuous integration score of the code includes the following steps:

[0060] Obtain the number of codes submitted by the individual to be evaluated and the integration status, and determine the minimum number of code submissions per day and the duration of continuous integration.

[0061] Based on the minimum number of code submissions per day and the duration of continuous integration, determine the code submission frequency score and the continuous integration result score for the codes submitted by the individual to be evaluated based on the preset threshold for the minimum number of code submissions per day and the threshold for the duration of continuous integration after new code submissions; among them, corresponding score deductions are made when the number of code submissions per day is lower than the threshold and the duration of continuous integration is higher than the threshold.

[0062] Respectively allocate weighting coefficients to the code submission frequency score and the continuous integration result score according to the impact factors of the actual application results of the codes, and determine the continuous integration score of the individual to be evaluated.

[0063] Among them, the threshold for the number of code submissions is, for example, at least one code submission per day; the threshold for the duration of continuous integration is, for example, not exceeding 3 minutes.

[0064] S2.2: Obtaining the automated test score, including the following steps:

[0065] Obtain the codes submitted by the individual to be evaluated, trigger the continuous integration pipeline, and continuously execute the automated test script or the automated test results on the codes submitted by the individual to be evaluated in sequence.

[0066] Judge whether it affects the core functions of the system according to the automated test results and count the execution pass rate of the automated test cases, and respectively obtain the number of serious defects, the number of general defects, and the number of minor defects. The execution pass rate refers to how many test cases pass and how many fail.

[0067] Respectively allocate weighting coefficients to the number of serious defects, the number of general defects, and the number of minor defects according to the impact factors of the defect degree on the code quality, and determine the code quality score of the individual to be evaluated.

[0068] S2.3: Obtaining the code standardization score, including the following steps:

[0069] Obtain the codes submitted by the individual to be evaluated.

[0070] Continuously perform static scans on the codes submitted by the individual to be evaluated in sequence, and obtain the static scan results; the static scan results include the number of code smells, the number of security vulnerabilities, the complexity, and the duplication rate.

[0071] Respectively allocate weighting coefficients to the scores of the number of code smells, the number of security vulnerabilities, the complexity, and the duplication rate according to the impact factors of each static scan result, and determine the code standardization score of the individual to be evaluated.

[0072] S2.4: Obtaining the code reuse degree score, including the following steps:

[0073] Obtain the code submitted by the individual to be evaluated, and encapsulate the general functions of the code submitted by the individual to be evaluated into classes, methods, and functions.

[0074] Count the number of times the encapsulated code is called by other developers within a fixed period, and the reuse times of function-level reuse, method-level reuse, component-level reuse, and suite-level reuse.

[0075] Evenly distribute the weighting coefficients to function-level reuse, method-level reuse, component-level reuse, and suite-level reuse to determine the code reuse degree score.

[0076] The evaluation details are shown as follows:

[0077] (1) Code continuous integration score = weighting coefficient A1 * code submission frequency score + weighting coefficient A2 * continuous integration result score.

[0078] Submission frequency: Submitting daily is the full score. If it exceeds 1 day, appropriate deductions will be made.

[0079] Continuous integration result: A one-time successful build and integration is the full score. For other cases, appropriate deductions will be made.

[0080] (2) Automated test score = 100 - weighting coefficient B1 * number of serious defects + weighting coefficient B2 * number of general defects + weighting coefficient B3 * number of minor defects.

[0081] (3) Code standardization score = weighting coefficient C1 * complexity + weighting coefficient C2 * repetition rate + weighting coefficient C3 * number of serious code smells + weighting coefficient C4 * number of security vulnerabilities.

[0082] (4) Code reuse degree score = weighting coefficient D1 * function-level reuse + weighting coefficient D2 * method-level reuse + weighting coefficient D3 * component-level reuse + weighting coefficient D4 * suite-level reuse.

[0083] S3: Respectively allocate the weighting coefficients to the code continuous integration score, automated test score, code standardization score, and code reuse degree score according to the impact factors of the actual application results of the code to obtain the weighted total score; obtain the acceptance rate of the review opinions of the individual to be evaluated, and determine the comprehensive efficiency evaluation result according to the results of the weighted total score and the acceptance rate of the review opinions. The review opinion execution flow chart is as Figure 3 shown.

[0084] Among them, when developers submit a Pull Request to merge into the review request, senior developers will act as technical experts to review the code to be merged. Valid review comments will be accepted by the submitter. Counting the acceptance rate of review comments can reflect the effectiveness of code review.

[0085] Specifically:

[0086] S3.1: After developers complete the code writing, create a Pull Request (PR) through the version control system (Git) to request to merge their code branch into the main branch or the target branch.

[0087] S3.2: Automatically assign or recommend suitable reviewers according to preset rules or policies through the version control system or CI / CD tools.

[0088] S3.3: The assigned reviewers receive the Pull Request notification, download or view the code to be merged. The reviewers carefully read the code, check the code quality, logical correctness, and whether it conforms to the coding specifications, etc.

[0089] S3.4: The reviewers fill in the review comments in the version control system or the review tool, including pointing out the problems in the code and putting forward improvement suggestions. The review comments can include specific code line numbers, screenshots, sample code, etc., so that the Pull Request requester can clearly understand the problem.

[0090] S3.5: After the Pull Request requester receives the review comments, carefully read and understand each comment. According to the review comments, the requester modifies, optimizes or explains the code. The requester replies to the review comments in the system, stating the acceptance situation (such as modified, partially adopted, not adopted and reasons, etc.).

[0091] S3.6: The reviewers review the modified code again: If the requester modifies the code, the reviewers may need to view the modified code again to confirm whether the problem has been solved. The reviewers can update the review status in the system, such as "reviewed", "still need to be modified", etc.

[0092] S3.7: The version control system or the review tool automatically counts the number of review comments, the number of acceptances by the requester, etc. for each Pull Request to form a score.

[0093] The schematic diagram for solving the score of the comprehensive performance evaluation is as follows:

[0094] Performance evaluation (developer role) = weighting coefficient A * code continuous integration score + weighting coefficient B * automated test score + weighting coefficient C * code standardization score + weighting coefficient D * code reuse degree score.

[0095] Performance evaluation (reviewer role) = weighting factor E * acceptance rate of review comments = weighting factor E1 * review response cycle + weighting factor E2 * adoption rate of review comments.

[0096] Comprehensive performance evaluation = performance evaluation (developer role) + performance evaluation (reviewer role).

[0097] S4: Obtain the comprehensive performance evaluation results of the personal code to be evaluated, conduct performance tracking on individuals whose comprehensive performance evaluation results do not meet the preset conditions, and separately construct performance improvement plans in terms of efficiency, quality, standardization, and code reuse. The specific implementation steps of the improvement plan are as Figure 4 shown, and the implementation steps of personal performance improvement tracking are as Figure 5 shown.

[0098] Study excellent code: Individuals select and study excellent code libraries within the team or the industry, focusing on understanding their architecture design, code style, algorithm implementation, etc. Through study, individuals learn and absorb the best practices and coding specifications in excellent code, laying a foundation for writing high-quality code.

[0099] Complete the exam: According to team requirements or personal learning plans, participate in relevant programming, algorithm, architecture design, etc. exams to test learning outcomes. The exam content may include theoretical knowledge, code writing, problem-solving abilities, etc., aiming to comprehensively evaluate an individual's technical capabilities.

[0100] Set a timed reminder for the personal code submission date: Use project management tools or calendar applications to set the deadline and reminder time for personal code submission. Timed reminders help individuals arrange their time reasonably and ensure that code writing and submission tasks are completed on time.

[0101] Personal code submission for SonarLint scanning: Before submitting the code, use static code analysis tools such as SonarLint to scan the personal code. The scan results will show potential problems, code smells, security vulnerabilities, etc. in the code, and individuals need to correct and optimize the code according to the scan results.

[0102] Execute P0-level and P1-level automated test cases: Before submitting the code, run the P0-level (critical, high priority) and P1-level (important, medium priority) automated test cases defined by the team. Ensure that code modifications do not break existing functions and meet quality standards and business logic requirements.

[0103] Personal code submission for Pull Request review: Submit the code that has been scanned by SonarLint and verified by automated tests to the version control system, and create a Pull Request (PR) to request a merge. Invite team members for code review, collect and handle review comments to ensure that the code quality meets the team standards.

[0104] Track the review progress and handle comments: Continuously monitor the review progress of the Pull Request, and respond promptly to the questions and suggestions raised by the reviewers. Make necessary modifications and optimizations to the code according to the review comments until the review is passed.

[0105] Improve the personal R & D efficiency score after the implementation of the improvement plan: Calculate the personal R & D efficiency score based on the individual's performance in the processes of code writing, submission, review, etc., and the team's evaluation criteria for personal R & D efficiency. By comparing the scores before and after the implementation of the improvement plan, evaluate the improvement of the individual in terms of code quality, work efficiency, team collaboration ability, etc.

[0106] According to the evaluation results, individuals can formulate further improvement plans to continuously improve R & D efficiency.

[0107] Implement the following improvement plan in terms of efficiency, quality, standardization, and code reuse:

[0108] Efficiency improvement plan: Remind individuals to submit code for continuous integration in real time, and count the number of code submissions and the duration of code integration. Intercept code submissions that do not meet the completion standard DOD.

[0109] Quality improvement plan: Automatically test the code before merging into the main branch in the development environment through the Jenkins pipeline; Determine whether to allow a Pull Request request to be submitted based on the results of the automated tests.

[0110] Standardization improvement plan: Check the code submitted by individuals through a hook program, report an error when it does not meet the submission format and give requirement prompts; Perform a static scan on the code submitted by individuals and output the static scan results.

[0111] Code reuse improvement plan: Push files, code blocks, and methods / functions with a high duplication rate in the code submitted by individuals, and through AIGC-related capabilities, assist developers to complete code refactoring, reduce the code duplication rate, and complete unified encapsulation and call management.

[0112] The above is the personal R & D efficiency improvement method provided by an embodiment of this embodiment. Based on the same idea, this embodiment also provides a corresponding personal R & D efficiency analysis system. For the specific limitations of the personal R & D efficiency analysis system, reference can be made to the limitations on the personal R & D efficiency improvement method in the above text, which will not be elaborated here. Each module in the above personal R & D efficiency analysis system can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in the form of hardware or independent of it, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0113] This embodiment also provides a computer-readable storage medium, which stores a computer program that can be used to execute the above Figure 1 provided personal R & D efficiency improvement method.

[0114] Those of ordinary skill in the art can understand that all or part of the processes in the above embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0115] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for improving personal R&D efficiency, characterized in that: The following steps are involved: Get the code of the merge review request submitted by the individual to be evaluated; Determine the continuous integration score, automated testing score, code standardization score, and code reuse score of the code based on the number of codes submitted by the individual to be evaluated, the integration status, the test status of the automated test scripts, the static scanning results, and the call status of the packaged code within a fixed period; According to the influencing factors of the code in various practical application results, weighted coefficients are allocated to the continuous integration score, automated testing score, code standardization score and code reuse score of the code to obtain the weighted total score; the adoption rate of the review opinions of the individuals to be evaluated is obtained, and the comprehensive performance evaluation result is determined based on the weighted total score and the review opinion adoption rate; According to the comprehensive performance evaluation results, performance tracking is carried out on individuals whose comprehensive performance evaluation results do not meet the preset conditions, and performance improvement plans are constructed in terms of efficiency, quality, standardization and code reuse.

2. The method for improving personal R&D efficiency according to claim 1, characterized in that: The acquisition of the continuous integration score of the code includes the following steps: Obtain the number of codes submitted and the integration status of the individuals to be evaluated, and determine the minimum number of codes submitted per day and the duration of continuous integration; According to the minimum number of code submissions per day and the continuous integration duration, the code submission frequency score and the continuous integration result score of the code submission of the individual to be evaluated are determined based on the preset minimum number of code submissions per day threshold and the continuous integration duration threshold after the new code submission; wherein, when it is lower than the minimum number of code submissions per day threshold and higher than the continuous integration duration threshold, the corresponding score is deducted; The code submission frequency score and the continuous integration result score are weighted according to the impact factors of the actual application results of the code, and the code continuous integration score of the individual to be evaluated is determined.

3. The method for improving personal R&D efficiency according to claim 1, characterized in that: The acquisition of the automated test score comprises the following steps: Obtain the code submitted by the individual to be evaluated, trigger the continuous integration pipeline, and continuously execute the automated test scripts or automated test results on the code submitted by the individual to be evaluated; Determine whether the core functions of the system are affected based on the automated test results and calculate the execution pass rate of automated test cases to obtain the number of serious defects, general defects, and minor defects respectively; According to the influencing factors of the degree of defects that affect the code quality, weighted coefficients are assigned to the number of serious defects, the number of general defects and the number of minor defects to determine the code quality score of the individual to be evaluated.

4. The method for improving personal R&D efficiency according to claim 1, characterized in that: The acquisition of the code standardization score includes the following steps: Obtain code submitted by individuals to be evaluated; The codes submitted by the individuals to be evaluated are continuously statically scanned in sequence to obtain static scanning results; the static scanning results include the number of code smells, the number of security vulnerabilities, complexity, and repetition rate; According to the influencing factors of each static scanning result, weighted coefficients are assigned to the scores of the number of code smells, the number of security vulnerabilities, complexity and repetition rate to determine the code standardization score of the individual to be evaluated.

5. The method for improving personal R&D efficiency according to claim 1, characterized in that: The acquisition of the code reuse score includes the following steps: Obtain the code submitted by the individual to be evaluated, and encapsulate the common functions of the code submitted by the individual to be evaluated into classes, methods and functions; Count the number of times the encapsulated code is called by other developers within a fixed period, and the number of times the code is reused at the function level, method level, component level, and suite level. Weighted coefficients are evenly assigned to function-level reuse, method-level reuse, component-level reuse, and suite-level reuse to determine the code reuse score.

6. The method for improving personal R&D efficiency according to claim 1, characterized in that: The review opinion adoption rate is to adopt a score based on the satisfaction of the individual to be evaluated with the manual review opinion results; the comprehensive performance evaluation result is determined by the sum of the weighted total score and the satisfaction adoption score.

7. The method for improving personal R&D efficiency according to claim 1, characterized in that: It also includes determining a performance improvement plan based on the comprehensive performance evaluation results, including the following steps: Obtain the comprehensive performance evaluation results of the individual code to be evaluated, track the performance of individuals whose comprehensive performance evaluation results do not meet the preset conditions, and build performance improvement plans in terms of efficiency, quality, standardization and code reuse; The efficiency improvement plan adopts real-time reminders for individuals to submit code for continuous integration, and counts the number of code submissions and code integration time, and intercepts code submissions that do not meet the completion standard DOD; The quality efficiency improvement plan adopts the following method: the code before merging into the main branch is automatically tested by the Jenkins pipeline in the development environment; based on the results of the automated test, it is determined whether to allow the submission of the PullRequest request; The efficiency improvement plan for the normative aspect adopts the following methods: a hook program is used to check the code submitted by individuals, and an error is reported and a requirement prompt is given when the submission format is not met; a static scan is performed on the code submitted by individuals, and the static scan results are output; The efficiency improvement plan for code reuse is adopted to push files, code blocks and methods / functions with high repetition rates in personally submitted codes, and through AIGC related capabilities, guide developers to complete code refactoring, reduce code repetition rates, and complete unified packaging and call management.

8. The method for improving personal R&D efficiency according to claim 1, characterized in that: The performance improvement plan in terms of efficiency, quality, standardization and code reuse includes the following: Efficiency improvement plan: remind individuals to submit code for continuous integration in real time, count the number of code submissions and the duration of code integration, and intercept code submissions that do not meet the completion standard DOD; Quality efficiency improvement plan: Perform automated testing of the Jenkins pipeline in the development environment before merging the code into the main branch; determine whether to allow the submission of PullRequest requests based on the results of automated testing; Efficiency improvement plan in terms of standardization: hook program check for individual submitted code, report error and give requirement prompt when it does not meet the submission format; Perform static scanning on the code submitted by individuals and output the static scanning results; Efficiency improvement plan for code reuse: push files, code blocks, and methods / functions with high repetition rates in personally submitted codes, and use AIGC-related capabilities to guide developers to complete code refactoring, reduce code repetition rates, and complete unified encapsulation and call management.

9. A personal R&D performance analysis system, characterized in that: The system comprises: processor; a memory having stored thereon a computer program executable on the processor; Wherein, when the computer program is executed by the processor, the steps of the method for improving personal R&D efficiency as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data processing program, and when the data processing program is executed by a processor, the steps of the method for improving personal R&D efficiency as described in any one of claims 1 to 8 are implemented.

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