Research and development performance evaluation method and system based on process work item statistics

Abstract

The invention discloses a research and development efficiency evaluation method and system based on process work item statistics, and relates to the technical field of software research and development management and efficiency evaluation, and the method comprises the steps: refining demands, tasks and defect work items according to the design, development and test stages of a project research and development process, and collecting related basic data; according to the basic data of the work item, calculating a research and development efficiency index of each stage; and according to the research and development efficiency index, analyzing the research and development efficiency of the project group and the project group. The research and development efficiency evaluation method based on process work item statistics has the beneficial effects that by monitoring the research and development efficiency indexes, teams can better understand the efficiency and effectiveness in the research and development process, and necessary adjustment is carried out according to the efficiency and effectiveness, so that the software quality is improved. It should be noted that these indicators should be seen as part of the entirety. And the team restores the index data regularly and performs continuous improvement according to feedback.

Description

Technical Field

[0001] The present invention relates to the technical field of software R&D management and performance evaluation, and in particular to a R&D performance evaluation method and system based on process work item statistics. Background Art

[0002] As the country promotes "digital industrialization, industrial digitization, data value, and digital governance services", it is accelerating the digital transformation of all industries, improving the level of public services, and enhancing national competitiveness. The demand for digital project construction is increasing, and the standard requirements are getting higher and higher. At the same time, in order to ensure the efficient construction of digital projects, R&D efficiency evaluation has become a difficult problem in the R&D process.

[0003] There are many methods for evaluating the effectiveness of digital project R&D, but they all have certain shortcomings. The potential shortcomings of common evaluation methods are: it is easy for the team to focus only on the indicator itself and ignore the project quality or other important aspects; KPIs may be too rigid and fail to reflect the actual progress of the project or new challenges in a timely manner; they rely on honest feedback from team members and are affected by team atmosphere or personal attitudes; they become difficult to understand and implement due to the complexity of the process; they cannot accurately reflect the actual complexity of the project; they oversimplify complex business logic and may be difficult to maintain and update in large projects. Summary of the invention

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

[0005] Therefore, the technical problem solved by the present invention is: how to introduce more objective data and establish a generally recognized evaluation and decision-making system that can be used for cross-team or cross-project evaluation, to assist and guide the R&D team in making closed-loop improvements, and to ensure that each evaluation can bring substantial improvements.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a research and development efficiency evaluation method based on process work item statistics, comprising:

[0007] According to the design, development and testing phases of the software project development process, refine requirements, tasks, defect work items, and collect relevant basic data;

[0008] Calculate the R&D efficiency indicators for each stage based on the basic data of the work items;

[0009] Analyze the R&D performance of project teams and project groups based on R&D performance indicators.

[0010] As a preferred solution of the R&D efficiency evaluation method based on process work item statistics described in the present invention, the detailed requirements, tasks, and defect work items include being divided into design, development, and testing stages according to the characteristics of the software project R&D process, and being managed according to the agile R&D model;

[0011] Divide the overall project delivery process into multiple iterations, and plan the work items of the three stages of design, development, and testing in one iteration; refine the key contents of the work items;

[0012] The requirements include the requirement name, requirement description, person responsible for the requirement, requirement start time, and requirement completion time; the tasks include the task name, task description, person responsible for the task, task-related requirements, task start time, and task completion time; the defects include the defect name, defect description, person responsible for the defect, defect-related requirements, defect start time, and defect completion time.

[0013] As a preferred solution of the R&D efficiency evaluation method based on process work item statistics described in the present invention, wherein: the collection of relevant basic data includes collecting relevant work item data of software development, preferably a project R&D management tool, to assist in recording relevant basic work item data during the R&D process; and complete the collection of basic work item data by department organization and project.

[0014] As a preferred scheme of the R&D efficiency evaluation method based on process work item statistics described in the present invention, wherein: the calculation of the R&D efficiency indicators of each stage includes the R&D efficiency indicators of the software project design stage, specifically including, iterative demand throughput, demand completion degree, average demand completion time, average demand completion rate, demand change rate, and average number of demands per capita. The indicators reflect the demand completion efficiency and the workload of designers during iteration.

[0015] As a preferred solution of the R&D efficiency evaluation method based on process work item statistics described in the present invention, wherein: the R&D efficiency index of each stage calculated also includes the main R&D efficiency index of the software project development stage, the number of iterative R&D tasks, the average task duration, the task completion degree, the average task completion rate, the task delay rate, and the average task delay time;

[0016] The testing phase of a software project includes test case execution rate, test case pass rate, defect discovery rate, defect escape rate, regression test pass rate, and test execution time.

[0017] As a preferred solution of the R&D efficiency evaluation method based on process work item statistics described in the present invention, the analysis of the R&D efficiency of the project group and the project group includes normalizing the quantitative indicators of the R&D efficiency of the three stages, and the calculation formula is expressed as follows:

[0018]

[0019] Among them, IDX m It is represented by the index m, whose value range is the index set described in the previous step, AVG(IDX m ) represents the average value of different project indicators m, MAX(IDX m ) represents the maximum value of different project indicators m, MIN(IDX m ) represents the minimum value of different project indicators m;

[0020] Calculate the project team's R&D efficiency score, the formula is:

[0021]

[0022] Among them, ρ represents the adjustment coefficient, which takes the value of 1 or -1. When the indicator is a negative evaluation indicator, the value is -1; score n represents item n, which is the arithmetic mean of the scores of different normalized indicators of the item;

[0023] The project team's R&D efficiency score is scored by stage. According to the obtained efficiency score, the product's R&D efficiency is ranked from high to low. Products with higher scores have higher R&D efficiency.

[0024] As a preferred solution of the R&D efficiency evaluation method based on process work item statistics described in the present invention, the R&D efficiency analysis of the project group and the project group also includes that the R&D efficiency index is used to evaluate the R&D efficiency of the project group or department organization, and the formula is expressed as:

[0025]

[0026] Among them, score O is the weighted average of the R&D efficiency scores of all projects in the group or department, w n is the R&D efficiency score weight of project n, and its value is normalized according to the importance of the project, and the project contract amount is preferably used as the standard. Here is CA n Indicates the contract amount of project n, CA total Indicates the contract amount of a group or department.

[0027] As a preferred solution of the R&D efficiency evaluation system based on process work item statistics described in the present invention, it includes:

[0028] The data collection and management module is responsible for collecting and managing the basic data of work items at each stage of the software development project development process, including detailed information on requirements, tasks, and defects;

[0029] The efficiency calculation module calculates the R&D efficiency indicators at each stage based on the work item data provided by the data collection module;

[0030] The performance analysis and evaluation module analyzes the R&D performance of each project team and project group of the software project, quantifies the performance indicators using normalization methods, calculates the R&D performance scores of the project teams, and ranks the R&D performance of each product;

[0031] The result visualization and report generation module displays the performance evaluation results intuitively in the form of charts or reports, allowing managers to view and analyze the R&D performance of the project and automatically generate periodic R&D performance reports.

[0032] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a research and development effectiveness evaluation method based on process work item statistics.

[0033] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a research and development effectiveness evaluation method based on process work item statistics.

[0034] Beneficial effects of the present invention: The R&D efficiency evaluation method based on process work item statistics provided by the present invention can help the team better understand the efficiency and effectiveness of the R&D process by monitoring R&D efficiency indicators, and make necessary adjustments to improve software quality. It should be noted that these indicators should be viewed as part of a whole. The team regularly reviews indicator data and makes continuous improvements based on feedback. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0036] Figure 1 An overall flow chart of a R&D efficiency evaluation method based on process work item statistics provided in the first embodiment of the present invention.

[0037] Figure 2 A digital project R&D phase and work item division diagram of a R&D efficiency evaluation method based on process work item statistics is provided in the second embodiment of the present invention.

[0038] Figure 3 A comparative chart of the R&D efficiency trends of the selected R&D departments in the past six months according to a R&D efficiency evaluation method based on process work item statistics provided in a second embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0040] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a method for evaluating R&D effectiveness based on process work item statistics, comprising:

[0041] S1: According to the design, development and testing phases of the software project development process, refine the requirements, tasks, and defect work items, and collect relevant basic data.

[0042] Furthermore, two software development departments with equivalent overall performance were selected for comparative implementation, such as Figure 1 As shown in the figure, a research and development efficiency evaluation method and system based on process work item statistics are presented. In the design, development, and testing phases of the software project research and development process, requirements, tasks, and defect work items are refined, and relevant basic data are collected, such as Figure 2 As shown, it is mainly divided into the following steps:

[0043] Step 1: According to the characteristics of the software project development process, it is divided into design, development, and testing stages, and managed according to the agile development model. Therefore, the overall delivery process of the software project will be divided into multiple iterations, and work items and tasks in the three stages of design, development, and testing will be planned in one iteration.

[0044] Step 2: refine the key contents of the work items, where requirements include requirement name, requirement description, person responsible for requirement, requirement start time, and requirement completion time; R&D tasks include task name, task description, person responsible for task, task-related requirements, task start time, and task completion time; defects include defect name, defect description, person responsible for defect, defect-related requirements, defect start time, and defect completion time.

[0045] Step 3: Collect relevant work item data. You can select software project development management tools, such as ZenTao, Cloud Effect, and other common tools, to assist in recording relevant basic work item data during the development process. Complete the collection of basic work item data by department organization and project.

[0046] S2: Calculate the R&D efficiency indicators for each stage based on the basic data of the work items.

[0047] Furthermore, according to the basic data of work items, the R&D efficiency indicators of each stage are calculated, mainly including:

[0048] Step 1: The main R&D efficiency indicators in the design phase include iterative demand throughput, demand completion rate, average demand completion time, average demand completion rate, demand change rate, and number of demands per capita. These indicators reflect the efficiency of demand completion and the workload of designers during iteration.

[0049] Step 1-1 Required throughput:

[0050] Definition: The number of requirements completed within one iteration.

[0051] Calculation formula: Demand throughput rate = total number of demands completed within the iteration cycle.

[0052] Step 1-2 Requirement Completion Rate:

[0053] Definition: The proportion of requirements completed within an iteration cycle to the planned requirements.

[0054] Calculation formula: Demand completion = (total number of requirements completed within the iteration cycle / total number of requirements planned within the iteration cycle)*100%.

[0055] Average Lead Time for Steps 1-3:

[0056] Definition: The average time from when a requirement enters the backlog to when it is completed.

[0057] Calculation formula: Average completion time of requirements = (total completion time of all completed requirements / total number of completed requirements).

[0058] Steps 1-4 require average completion rate (Velocity):

[0059] Definition: The amount of work that a team can complete within a unit period, usually expressed as user story requirements per unit time.

[0060] Calculation formula: Average completion rate of requirements = the sum of the number of requirements completed within the iteration cycle / the total completion time of all completed requirements.

[0061] Step 1-5 Requirement Change Rate:

[0062] Definition: The ratio of requirements that change during an iteration.

[0063] Calculation formula: Demand change rate = (total number of requirements changed within the iteration cycle / total number of all requirements within the iteration cycle) * 100%.

[0064] Steps 1-6 Workload per Person:

[0065] Definition: The number of requirements that each team design member is responsible for within an iteration cycle.

[0066] Calculation formula: Number of requirements per person = total number of requirements completed within the iteration cycle / total number of team design members.

[0067] Step 2: The main R&D efficiency indicators in the development phase include the number of iterative R&D tasks, average task duration, task completion rate, average task completion rate, task delay rate, and average task extension time.

[0068] Step 2-1 Task Count:

[0069] Definition: The number of tasks completed within a certain period of time.

[0070] Calculation formula: Number of tasks = total number of tasks completed within the specified time frame.

[0071] Step 2-2 Average task duration (TaskDuration):

[0072] Definition: The average time required to complete a single task.

[0073] Calculation formula: Average task duration = total time taken for all completed tasks / total number of completed tasks.

[0074] Step 2-3 Task Completion Rate:

[0075] Definition: The proportion of planned tasks completed within a given time.

[0076] Calculation formula: Task completion = number of completed tasks / number of planned tasks*100%.

[0077] Average completion rate of tasks in steps 2-4 (TaskVelocity):

[0078] Definition: The average amount of work completed by a team in an iteration or a specific period of time.

[0079] Calculation formula: Average task completion rate = number of work item tasks completed in an iteration or time period / total completion time of all completed tasks.

[0080] Step 2-5 Task Delay Rate:

[0081] Definition: The percentage of tasks that are not completed as planned.

[0082] Calculation formula: Task delay rate = number of delayed tasks / number of planned tasks*100%.

[0083] Step 2-6 Task average delay time (TaskBlockTime):

[0084] Definition: The time a task is stuck for some reason (such as waiting for resources, dependencies not completing, etc.).

[0085] Calculation formula: Average task delay time = total delay time of all tasks / total number of completed tasks.

[0086] Step 3: The main R&D efficiency indicators in the testing phase include test case execution rate, test case pass rate, defect discovery rate, defect escape rate, regression test pass rate, and test execution time.

[0087] Step 3-1 Test Case Execution Rate:

[0088] Definition: The ratio of executed test cases to total test cases.

[0089] Calculation formula: Test case execution rate = (number of executed test cases / total number of test cases) * 100%.

[0090] Step 3-2 Test Case Pass Rate:

[0091] Definition: The ratio of passed test cases to executed test cases.

[0092] Calculation formula: Test case pass rate = (number of passed test cases / number of executed test cases)*100%.

[0093] Step 3-3 Defect Detection Rate:

[0094] Definition: The number of defects found during the testing phase.

[0095] Calculation formula: Defect discovery rate = (total number of defects found / total number of test case executions) * 100%

[0096] Step 3-4 Defect Escape Rate:

[0097] Definition: The ratio of defects found after release to total defects found.

[0098] Calculation formula: Defect escape rate = (number of defects found after release / total number of defects found before release) * 100%

[0099] Step 3-5 Regression Test Pass Rate:

[0100] Definition: The ratio of test cases that passed in regression testing to the test cases executed in regression testing.

[0101] Calculation formula: Regression test pass rate = (number of test cases passed by regression test / number of test cases executed by regression test)*100%.

[0102] Step 3-6 Test Execution Time:

[0103] Definition: The time required to complete a testing activity.

[0104] Calculation formula: Test execution time = test end time - test start time.

[0105] S3: Analyze the R&D performance of project teams and project groups based on various R&D performance indicators.

[0106] Furthermore, according to various R&D efficiency indicators, the R&D efficiency of the project team and project group of the software project is analyzed, mainly including:

[0107] The quantitative indicators of R&D efficiency in the three stages are normalized, and the calculation formula is as follows:

[0108]

[0109] Among them, IDX m It is represented by the index m, whose value range is the index set described in the previous step, AVG(IDX m ) represents the average value of different project indicators m, MAX(IDX m ) represents the maximum value of different project indicators m, MIN(IDX m ) represents the minimum value of different project indicators m.

[0110] Calculate the project team's R&D efficiency score using the following formula:

[0111]

[0112] Among them, ρ is the adjustment coefficient, which takes a value of 1 or -1. When the indicator is a negative evaluation indicator, the value is -1, such as the demand change rate, the average task delay time, the defect escape rate, etc. n Represents item n, which is the arithmetic mean of the scores of different normalized indicators of the item.

[0113] Furthermore, the project team's R&D efficiency score can be scored by stage, such as IDX mThe indicator set is only for the design or development stage.

[0114] According to the obtained efficiency scores, the R&D efficiency of products is ranked from high to low, and products with higher scores have higher R&D efficiency.

[0115] Furthermore, the above indicators can be used to evaluate the R&D performance of a project group or department organization. The calculation formula is as follows:

[0116]

[0117] Among them, score O is the weighted average of the R&D efficiency scores of all projects in the group or department, w n is the R&D efficiency score weight of project n, and its value is normalized according to the importance of the project, and the project contract amount is preferably used as the standard. Here is CA n is the contract amount of project n, CA total The contract amount for the group or department.

[0118] Example 2, reference Figure 3 , which is an embodiment of the present invention, provides a research and development efficiency evaluation method based on process work item statistics. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0119] One of the two software project R&D departments selected monitors R&D performance indicators so that the team can better understand the efficiency and effectiveness of the R&D process and make necessary adjustments accordingly. The team regularly reviews the indicator data and makes continuous improvements based on feedback. Figure 3 As shown in the figure, based on the statistical results, the R&D efficiency change trends of the two departments in the past six months were calculated. It can be seen that, at the beginning, due to the relatively consistent management models, the R&D efficiency of the two departments was comparable. However, as Department 2 continued to optimize, while Department 1 remained as it was without continuous optimization, its R&D efficiency fluctuated at a low level, and a gap gradually emerged in the R&D efficiency of the two departments.

[0120] A comparative experiment was conducted on two independent software development project groups A and B, which were responsible for different modules of the same software platform, using the same R&D tools and process management, and following the agile development model, with each iteration cycle lasting 2 weeks. This experiment aims to evaluate the performance of the two groups of projects in the three stages of design, development and testing, and conduct a comparative analysis.

[0121] Before the experiment, an automated data collection tool was prepared to record the relevant data of requirements, tasks, and defects, including requirement name, task name, task start time, task completion time, defect discovery time, defect repair time, etc. The tool was integrated into the project management platform, and the data of each R&D work item was automatically recorded at each stage.

[0122] The requirements of the two project teams were determined by the customer requirements document and the results of the design discussion. The design phase included requirements analysis and functional module design. The data collection tool automatically recorded the requirements name, description, start and end time of the requirements. The requirements completion and requirements change rate of each project team in the design phase were recorded.

[0123] After the design phase is completed, the project team enters the development phase. Each developer is responsible for several development tasks, and the tool records the start and completion time of the task, the requirements associated with the task, and the developer's information. The system calculates performance indicators such as task completion rate and task delay rate based on task data.

[0124] After the development phase, the project enters the testing phase. Testers design test cases and execute tests based on the functional modules provided by developers. The tool records the test case execution time, pass rate, defects found and their repair time, etc., and generates indicators such as test case pass rate, defect discovery rate and regression test pass rate.

[0125] The experiment cycle was carried out for three iterations. In each iteration, the basic data of design, development, and testing were recorded, and the performance indicators were calculated based on these data. In order to ensure the objectivity and scientificity of the results, the task scale, developer experience level, and test environment of the two project teams were kept consistent during the experiment.

[0126] Table 1 Software project development comparison data table

[0127]

[0128] It is obvious from the data in Table 1 that Project Group A has shown significant advantages in multiple performance indicators, especially in terms of demand throughput, task completion, and regression test pass rate in the testing phase. The demand throughput of Project Group A is 85%, significantly higher than the industry average of 75%, indicating that the group is more efficient in handling demand and can quickly respond to and meet customer needs. In addition, the demand change rate of Project Group A is only 10%, much lower than the 15% of Project Group B and the industry average of 20%, which means that Project Group A has a more accurate understanding of demand in the demand analysis and design phase, reducing demand changes in the subsequent development process.

[0129] During the development phase, Project Group A's task completion rate was 92%, higher than Project Group B's 87% and the industry average of 85%. This directly reflects that Project Group A has higher development efficiency and is able to complete more tasks within a given time. The average task delay is also about 3 hours shorter than Project Group B and the industry average. This shows that Project Group A has better optimization in task allocation and development progress control, and developers are able to complete tasks more efficiently.

[0130] Embodiment 3, referring to FIG. 123 , is an embodiment of the present invention, which provides a R&D efficiency evaluation system based on process work item statistics, including:

[0131] The data collection and management module is responsible for collecting and managing the basic data of work items at each stage of the project development process, including detailed information on requirements, tasks, and defects.

[0132] The efficiency calculation module calculates the R&D efficiency indicators of each stage based on the work item data provided by the data collection module.

[0133] The performance analysis and evaluation module analyzes the R&D performance of each project team and project group, quantifies the performance indicators using normalization methods, calculates the R&D performance score of the project team, and ranks the R&D performance of each product.

[0134] The result visualization and report generation module displays the performance evaluation results intuitively in the form of charts or reports, allowing managers to view and analyze the R&D performance of the project and automatically generate periodic R&D performance reports.

[0135] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0136] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0137] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0138] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0139] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A R&D efficiency evaluation method based on process work item statistics, characterized in that: include: According to the design, development and testing phases of the software project development process, refine requirements, tasks, defect work items, and collect relevant basic data; Calculate the R&D efficiency indicators for each stage based on the basic data of the work items; Analyze the R&D performance of project teams and project groups based on R&D performance indicators.

2. The R&D efficiency evaluation method based on process work item statistics according to claim 1, characterized in that: The detailed requirements, tasks, and defect work items include, according to the characteristics of the software project development process, divided into design, development, and testing phases, and managed according to the agile development model; Divide the overall project delivery process into multiple iterations, and plan the work items of the three stages of design, development, and testing in one iteration; refine the key contents of the work items; The requirements include the requirement name, requirement description, person responsible for the requirement, requirement start time, and requirement completion time; The task includes the task name, task description, task responsible person, task related requirements, task start time, and task completion time; the defect includes the defect name, defect description, defect responsible person, defect related requirements, defect start time, and defect completion time.

3. The R&D efficiency evaluation method based on process work item statistics according to claim 2, characterized in that: The collecting of relevant basic data includes collecting relevant work item data of software development, preferably a project development management tool, to assist in recording relevant basic work item data during the development process; Complete the collection of basic work item data by department organization and project.

4. The R&D efficiency evaluation method based on process work item statistics according to claim 3, characterized in that: The R&D efficiency indicators calculated at each stage include R&D efficiency indicators in the software project design stage, specifically, iterative demand throughput, demand completion degree, average demand completion time, average demand completion rate, demand change rate, and average number of demands per capita. The indicators reflect the efficiency of demand completion and the workload of designers during iteration.

5. The R&D efficiency evaluation method based on process work item statistics according to claim 4, characterized in that: The calculation of the R&D efficiency indicators at each stage also includes the main R&D efficiency indicators at the software project development stage, the number of iterative R&D tasks, the average task duration, the task completion degree, the average task completion rate, the task delay rate, and the average task delay time; The testing phase of a software project includes test case execution rate, test case pass rate, defect discovery rate, defect escape rate, regression test pass rate, and test execution time.

6. The R&D efficiency evaluation method based on process work item statistics according to claim 5, characterized in that: The analysis of the R&D efficiency of the project team and project group includes normalizing the quantitative indicators of the R&D efficiency in the three stages. The calculation formula is expressed as follows: Among them, IDX m It is represented by the index m, whose value range is the index set described in the previous step, AVG(IDX m ) represents the average value of different project indicators m, MAX(IDX m ) represents the maximum value of different project indicators m, MIN(IDX m ) represents the minimum value of different project indicators m; Calculate the project team's R&D efficiency score, the formula is: Among them, ρ represents the adjustment coefficient, which takes the value of 1 or -1. When the indicator is a negative evaluation indicator, the value is -1; score n represents item n, which is the arithmetic mean of the scores of different normalized indicators of the item; The project team's R&D efficiency score is scored by stage. According to the obtained efficiency score, the product's R&D efficiency is ranked from high to low. Products with higher scores have higher R&D efficiency.

7. The R&D efficiency evaluation method based on process work item statistics according to claim 6, characterized in that: The analysis of the R&D effectiveness of the project team and project group also includes that the R&D effectiveness index is used to evaluate the R&D effectiveness of the project group or department organization, and the formula is expressed as follows: Among them, score O is the weighted average of the R&D efficiency scores of all projects in the group or department, w n is the R&D efficiency score weight of project n, and its value is normalized according to the importance of the project, and the project contract amount is preferably used as the standard. Here is CA n Indicates the contract amount of project n, CA total Indicates the contract amount of a group or department.

8. A system using the R&D efficiency evaluation method based on process work item statistics as claimed in any one of claims 1 to 7, characterized in that: The data collection and management module is responsible for collecting and managing the basic data of work items at each stage of the software development project development process, including detailed information on requirements, tasks, and defects; The efficiency calculation module calculates the R&D efficiency indicators at each stage based on the work item data provided by the data collection module; The performance analysis and evaluation module analyzes the R&D performance of each project team and project group of the software project, quantifies the performance indicators using normalization methods, calculates the R&D performance scores of the project teams, and ranks the R&D performance of each product; The result visualization and report generation module displays the performance evaluation results intuitively in the form of charts or reports, allowing managers to view and analyze the R&D performance of the project and automatically generate periodic R&D performance reports.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the R&D effectiveness evaluation method based on process work item statistics described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the R&D effectiveness evaluation method based on process work item statistics described in any one of claims 1 to 7 are implemented.

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