R&D data management method, device and equipment and readable storage medium

Abstract

This application discloses a research and development data management method, apparatus, device, and readable storage medium. The method includes acquiring process execution data corresponding to the current research and development project, wherein the process execution data is collected by tracking points set on the project management platform of an instant messaging system. The project management platform includes all research and development process nodes of the current research and development project, and each research and development process node is equipped with a corresponding tracking point; acquiring performance data of different research and development outputs of all external research and development tools corresponding to the current research and development project; and processing the process execution data and the performance data of each research and development output to generate a research and development indicator analysis report. Therefore, this application can realize research and development process analysis through a complete chain of automatically collecting process execution data through tracking points, aggregating external tool research and development performance data, and uniformly analyzing and generating indicator reports.

Description

Technical Field

[0001] This application relates to the field of software development technology, and more specifically, to a research and development data management method, apparatus, device, and readable storage medium. Background Technology

[0002] In the software development field, different developers are responsible for the development work of various business segments and need to use corresponding types of development tools. This results in fragmented development data scattered across various tool systems, making each business line's development process a self-contained system. Consequently, data from different development segments is disconnected, forming data silos and making it difficult to accurately control the overall development progress.

[0003] To meet the diverse tool usage needs of R&D personnel, existing technologies require customized development of R&D platforms that integrate multiple tool capabilities, which suffers from high development costs and long construction cycles. Summary of the Invention

[0004] In view of this, this application provides a research and development data management method, apparatus, device and readable storage medium to solve the shortcomings of the prior art in that it is difficult to assess the research and development progress.

[0005] To achieve the above objectives, the following solution is proposed:

[0006] A research and development data management method, comprising:

[0007] Obtain the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is set with a corresponding tracking point.

[0008] Obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project;

[0009] The process execution data and the performance data of each R&D output are processed to generate an R&D indicator analysis report.

[0010] Optionally, obtaining the process execution data corresponding to the current R&D project includes:

[0011] When an update event of a development node is detected, the update subject, update time, and update node are collected, and process execution data is generated and stored.

[0012] Optionally, obtaining the performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project includes:

[0013] Obtain the code submission subject, code submission time, and code line number of each process node from the code development tool;

[0014] Obtain the number of builds, build time, and build results for each process node from integrated R&D tools;

[0015] Obtain the number of test cases created, executed, and pass rate for each process node from the test case creation tool;

[0016] The online defect count, missed test rate, failure rate, and test case coverage are obtained from the testing tools.

[0017] Optionally, obtaining the code submission subject, code submission time, and code line number of the process node from the code development tool includes:

[0018] The code submission subject, submission time, and line number of each process node can be obtained from the code development tool via API calls or scheduled synchronization.

[0019] Optionally, the process of processing the execution data of the process and the efficiency data of each R&D output to generate an R&D indicator analysis report includes:

[0020] The process execution data and various performance data are cleaned.

[0021] The cleaned process execution data and various performance data are correlated to form a research and development data link;

[0022] The R&D data chain is analyzed to generate an R&D indicator analysis report.

[0023] Optionally, the R&D data chain can be analyzed to generate an R&D indicator analysis report, including:

[0024] Analyze the process blockages in the R&D data link and generate an R&D indicator analysis report.

[0025] Optionally, the analysis of process blockages in the R&D data link and the generation of an R&D indicator analysis report include:

[0026] Based on the dwell time of each process node represented by the R&D data link and the test pass rate of the process node, an R&D indicator analysis report is generated.

[0027] A research and development data management device, comprising:

[0028] The process execution data acquisition module is used to acquire the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is equipped with a corresponding tracking point.

[0029] The performance data acquisition module is used to acquire performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project.

[0030] The report generation module is used to process the process execution data and the performance data of each R&D output to generate an R&D indicator analysis report.

[0031] A research and development data management device, including a memory and a processor;

[0032] The memory is used to store programs;

[0033] The processor is used to execute the program to implement the various steps of the above-described R&D data management method.

[0034] A readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps of the above-described R&D data management method.

[0035] As can be seen from the above technical solution, the R&D data management method provided in this application can obtain the process execution data corresponding to the current R&D project. The process execution data is collected by tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node has a corresponding tracking point. Based on this, this application can unify the process of the current R&D project through the project management platform provided by the instant messaging system, and collect process execution data through tracking points when R&D personnel update the R&D process nodes. This allows for timely understanding of the R&D progress of the corresponding business line through the process execution data, improving collaboration efficiency. Process execution data can be obtained by processing the project management platform provided by the instant messaging system. This application provides efficient and low-cost data integration for data collection. To aggregate R&D data from different R&D tools, it can obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project. This enables the aggregation of multi-dimensional R&D output performance data from various external R&D tools, breaking down data barriers between different tool systems, solving the problems of scattered, isolated, and fragmented R&D data, and achieving unified collection of multi-source R&D performance data. Subsequently, by processing the process execution data and the performance data of each R&D output, an R&D indicator analysis report is generated. This application can integrate, clean, and analyze the two types of heterogeneous data collected, transforming the original scattered data into a standardized and visual analysis report, enabling quantitative assessment of R&D status, accurate judgment of R&D progress, and intuitive presentation of the entire R&D process performance. As can be seen, this application can automatically collect process execution data through data tracking, aggregate R&D performance data from external tools, and generate indicator reports through unified analysis, thus breaking down data silos between R&D process data and multi-tool performance data. This enables automatic collection, unified aggregation, and intelligent analysis of R&D process data. It eliminates the need for customized development of a multi-functional integration platform, significantly reducing the development cost and construction cycle of R&D data integration, while improving the efficiency of R&D collaboration management and the comprehensiveness and accuracy of R&D data analysis. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0037] Figure 1 This is a flowchart of a research and development data management method disclosed in an embodiment of this application;

[0038] Figure 2 This is a structural block diagram of a research and development data management device disclosed in an embodiment of this application;

[0039] Figure 3 This is a hardware structure block diagram of a research and development data management device disclosed in an embodiment of this application. Detailed Implementation

[0040] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] This application provides a research and development data management method, which can be applied to various instant messaging systems or research and development management systems, as well as to various computer terminals or smart terminals. The executing entity can be the processor or server of the computer terminal or smart terminal.

[0042] Next, combine Figure 1 The research and development data management method described in this application is detailed, including the following steps:

[0043] Step S1: Obtain the process execution data corresponding to the current R&D project.

[0044] Specifically, process execution data can be collected by data points set up on the project management platform of the instant messaging system.

[0045] Instant messaging systems are office communication systems that allow for the instant sending and receiving of information.

[0046] The project management platform can be MeeGo or Teambition.

[0047] The project management platform can contain all the nodes of the current R&D project's entire R&D process, with corresponding tracking points set on each node.

[0048] The current R&D project process can be divided into three stages: the requirements design stage, the R&D stage, and the release stage.

[0049] Each stage contains multiple R&D process nodes.

[0050] For example, the requirements design phase may include development process nodes such as requirements pool, interaction design, and UI design.

[0051] The R&D phase may include R&D process nodes such as product committee review, interaction review, UI review, technical review, task decomposition, and use case writing.

[0052] The release phase may include development process nodes such as testing, test submission, delivery and acceptance, and interactive acceptance.

[0053] Step S2: Obtain the performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project.

[0054] Specifically, different external R&D tools can correspond to different R&D outputs;

[0055] It can collect performance data corresponding to each R&D output.

[0056] It can extract corresponding core performance parameters for different types of external R&D tools, ensuring that the acquired performance data can accurately correspond to the output quality and efficiency of each R&D stage.

[0057] For example, during the code development phase, relevant data can be extracted from the code dimension.

[0058] During the testing phase, relevant quality data from the testing dimensions can be extracted to ensure that performance data corresponds one-to-one with the nodes in the R&D process.

[0059] Step S3: Process the process execution data and the performance data of each R&D output to generate an R&D indicator analysis report.

[0060] Specifically, based on management needs, a multi-dimensional data model can be constructed, an indicator calculation scheme can be formulated, process execution data and efficiency data of various R&D outputs can be processed, and an R&D indicator analysis report can be generated.

[0061] Management needs may include R&D efficiency assessment, team productivity analysis, project quality control, process bottlenecks, and resource allocation decisions.

[0062] Multi-dimensional data models can include delivery dimensions, human efficiency dimensions, quality dimensions, and value delivery dimensions, etc.

[0063] The first-pass rate of use case reviews can be equal to the ratio of the number of requirements with one use case review to the total number of requirements;

[0064] The online missed test rate can be equal to the ratio of the number of online defects to the total number of test cases;

[0065] Code submission equivalent can be equal to the cumulative value of code submission equivalent associated with Lark;

[0066] The defect resolution rate can be equal to the ratio of the number of resolved defects to the total number of defects.

[0067] As can be seen from the above technical solution, the R&D data management method provided in this application can obtain the process execution data corresponding to the current R&D project. The process execution data is collected by tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node has a corresponding tracking point. Based on this, this application can unify the process of the current R&D project through the project management platform provided by the instant messaging system, and collect process execution data through tracking points when R&D personnel update the R&D process nodes. This allows for timely understanding of the R&D progress of the corresponding business line through the process execution data, improving collaboration efficiency. Process execution data can be obtained by processing the project management platform provided by the instant messaging system. This application provides efficient and low-cost data integration for data collection. To aggregate R&D data from different R&D tools, it can obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project. This enables the aggregation of multi-dimensional R&D output performance data from various external R&D tools, breaking down data barriers between different tool systems, solving the problems of scattered, isolated, and fragmented R&D data, and achieving unified collection of multi-source R&D performance data. Subsequently, by processing the process execution data and the performance data of each R&D output, an R&D indicator analysis report is generated. This application can integrate, clean, and analyze the two types of heterogeneous data collected, transforming the original scattered data into a standardized and visual analysis report, enabling quantitative assessment of R&D status, accurate judgment of R&D progress, and intuitive presentation of the entire R&D process performance. As can be seen, this application can automatically collect process execution data through data tracking, aggregate R&D performance data from external tools, and generate indicator reports through unified analysis, thus breaking down data silos between R&D process data and multi-tool performance data. This enables automatic collection, unified aggregation, and intelligent analysis of R&D process data. It eliminates the need for customized development of a multi-functional integration platform, significantly reducing the development cost and construction cycle of R&D data integration, while improving the efficiency of R&D collaboration management and the comprehensiveness and accuracy of R&D data analysis.

[0068] In some embodiments of this application, the process of obtaining the process execution data corresponding to the current R&D project in step S1 is described in detail, and the steps are as follows:

[0069] S10. When a development node update event is detected, collect the update subject, update time and update node, and generate and store process execution data.

[0070] Specifically, by configuring custom fields and interfaces in the instant messaging system, when a development node update event is detected, the system can automatically trigger the tracking node priority, node identifier, update subject, update time, and update node.

[0071] Node priority, node identifier, update subject, update time, and update node can be organized into process execution data.

[0072] The updating entity can represent the person performing the node update operation.

[0073] The trigger point can also collect abnormal information and operation information;

[0074] Operation information may include node completion time, whether the node passed, and the reason for rejection.

[0075] As can be seen from the above technical solution, this embodiment provides an optional method for obtaining process execution data corresponding to the current R&D project. Through this method, the project management platform can be used to automatically collect process execution data without requiring large-scale modifications to the platform's original functions, further reducing the development cost of data collection. Simultaneously, it can completely record the flow of each process node, providing complete raw data support for subsequent analysis of the time consumption and pass rate of R&D nodes, achieving standardization and normalization of the R&D process, and obtaining full data during process execution, thus solving the problems of process chaos and data loss.

[0076] In some embodiments of this application, the process of step S2, obtaining performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project, is described in detail as follows:

[0077] S20. Obtain the code submission subject, code submission time, and code line number of the process node from the code development tool.

[0078] Specifically, by sending a data retrieval request to the code development tool through the pre-defined first open interface, the code submission subject, code submission time, and code line number associated with the corresponding process node can be obtained.

[0079] Furthermore, the corresponding code submission equivalent can be calculated according to preset rules, thus completing the collection of code-dimensional performance data.

[0080] The code development tool can be GitLab.

[0081] S21. Obtain the number of builds, build duration, and build results of process nodes from the integrated R&D tools.

[0082] Specifically, by initiating a data pull request to the integrated development tool through the corresponding second open interface, the number of builds, build duration, and build results associated with the corresponding process node can be obtained.

[0083] Based on this, metrics such as success rate and average build time can be statistically obtained, thus completing the collection of performance data across the integrated build dimension.

[0084] Among them, the integrated development tool can be Jenkins.

[0085] S22. Obtain the number of test cases created, the number of executions, and the pass rate for each process node from the test case creation tool.

[0086] Specifically, a data retrieval request can be initiated to the test case creation tool through a preset third open interface to obtain the number of test cases created, executed, and pass rate associated with the corresponding process node.

[0087] Furthermore, metrics such as first-time pass rate for test case reviews and requirement coverage can be calculated, thus completing the collection of performance data at the test case dimension.

[0088] The use case creation tool can be Simayi.

[0089] S23. Obtain online defect count, missed test rate, failure rate, and test case coverage from the testing tools.

[0090] Specifically, by initiating a data retrieval request to the testing tool through the preset fourth open interface, data such as the number of online defects, defect distribution, missed test rate, failure rate, and test case coverage associated with the corresponding process node can be obtained, directly completing the collection of test quality dimension performance data.

[0091] It can also obtain R&D data such as human resource input and resource usage.

[0092] As can be seen from the above technical solution, this embodiment provides an optional method for obtaining performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project. Through this method, targeted data retrieval can be performed for different types of external R&D tools, and automated data collection can be completed through open interfaces. There is no need for manual data export and import, which ensures the comprehensiveness and accuracy of data acquisition while reducing the workload and error probability of manual operations. It can stably and efficiently aggregate R&D performance data from different dimensions of various tools, effectively breaking down data barriers between different R&D tools and providing a complete data foundation for subsequent multi-dimensional analysis.

[0093] In some embodiments of this application, the process of obtaining the code submission subject, code submission time, and code line number of the process node from the code development tool is described in detail, and the steps are as follows:

[0094] S200: Obtain the code submission subject, code submission time, and code line number of the process node from the code development tool through interface calls or timed synchronization.

[0095] Specifically, for external R&D tools that do not support real-time interfaces, performance data can be synchronized using scheduled tasks.

[0096] For external R&D tools that support real-time interfaces, performance data can be synchronized via interface calls when reports need to be generated, or it can be synchronized via scheduled tasks.

[0097] Therefore, the code submission subject, code submission time, and code line number of a process node can be obtained from the code development tool through interface calls or timed synchronization.

[0098] Similarly, the number of builds, build duration, and build results of process nodes can be obtained from the integrated development tools through API calls or timed synchronization.

[0099] The number of test cases created, executed, and pass rate for process nodes can be obtained from the test case creation tool via API calls or timed synchronization.

[0100] The number of online defects, missed test rate, failure rate, and test case coverage can be obtained from the testing tool through interface calls or timed synchronization.

[0101] As can be seen from the above technical solution, this embodiment provides an optional method for obtaining the code submission subject, code submission time, and code line number of a process node from a code development tool. This method can adapt to different data synchronization functions of external development tools. Whether it's a tool that supports real-time open interfaces or only supports batch data export, automated data collection can be achieved, improving the method's adaptability and compatibility. No additional customization or modification is required to adapt to different tools, further reducing the overall implementation and modification costs of the solution.

[0102] In some embodiments of this application, the process of processing the process execution data and the performance data of each R&D output to generate an R&D indicator analysis report is described in detail, and the steps are as follows:

[0103] S30. Clean the process execution data and various performance data.

[0104] Specifically, the process execution data and various performance data are deduplicated, corrected, completed, and their formats are standardized to ensure the accuracy and consistency of the data.

[0105] S31. The cleaned process execution data and various performance data are associated to form a research and development data link.

[0106] Specifically, by using process nodes as the core associated fields, the cleaned process execution data and various performance data can be linked to form a research and development data link, ensuring that the data is traceable and associative.

[0107] S32. Analyze the R&D data link and generate an R&D indicator analysis report.

[0108] Specifically, based on a pre-set multi-dimensional data model and combined with different management needs, indicators of corresponding dimensions can be extracted from the R&D data chain for calculation and analysis, generating a visualized R&D indicator analysis report that intuitively presents the R&D efficiency of each dimension.

[0109] As can be seen from the above technical solution, this embodiment provides an optional method for generating R&D indicator analysis reports. By cleaning, associating and analyzing the original heterogeneous data, it is possible to integrate scattered and fragmented data into structured and usable data, ensuring the accuracy and traceability of the final analysis results and meeting the R&D management decision-making needs of multiple scenarios.

[0110] In some embodiments of this application, the process of step S32, analyzing the R&D data link and generating an R&D indicator analysis report, is described in detail as follows:

[0111] S320. Analyze the process blockage of the R&D data link and generate an R&D indicator analysis report.

[0112] Specifically, it can analyze the dwell time of all process nodes currently in the R&D data link and the test pass rate of the process nodes, and generate an R&D indicator analysis report.

[0113] Since R&D projects typically involve multiple business lines operating in parallel, there can be multiple process nodes that remain in place at the same time.

[0114] As can be seen from the above technical solution, this embodiment provides an optional method for analyzing the R&D data chain and generating an R&D indicator analysis report. This method can present the flow status of process nodes during project R&D, pinpoint blocked R&D stages, help managers intervene in a timely manner to coordinate resources, promote project progress according to the established cycle, avoid slowing down the overall R&D progress due to process blockages, and improve the overall efficiency of the R&D project.

[0115] In some embodiments of this application, the process of step S320, analyzing the process blockage of the R&D data link, and generating an R&D indicator analysis report is described in detail, and the steps are as follows:

[0116] S3200: Based on the dwell time of each process node represented by the R&D data link and the test pass rate of the process node, generate an R&D indicator analysis report.

[0117] Specifically, based on the dwell time of each process node represented by the R&D data link and the test pass rate of the process node, an overall R&D report, a business line report, an individual report, and detailed reports of various indicators can be generated.

[0118] Furthermore, an automatic report update mechanism can be set up to synchronize the latest R&D data in real time, ensuring the timeliness of the report data and facilitating timely reflection of R&D dynamics.

[0119] As can be seen from the above technical solution, this embodiment provides an optional method for analyzing the process blockage of the R&D data link and generating an R&D indicator analysis report. This method can meet the R&D process management needs at different levels.

[0120] Next, we will combine Figure 2 The R&D data management device provided in this application is described in detail. The R&D data management device described below can be compared with the R&D data management method described above.

[0121] See Figure 2 It can be observed that the research and development of data management devices may include:

[0122] The process execution data acquisition module 10 is used to acquire the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is equipped with a corresponding tracking point.

[0123] The performance data acquisition module 20 is used to acquire performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project;

[0124] The report generation module 30 is used to process the process execution data and the efficiency data of each R&D output to generate an R&D indicator analysis report.

[0125] Furthermore, the process execution data acquisition module 10 may include:

[0126] The update subject acquisition unit is used to collect the update subject, update time and update node when an update event of the R&D node is detected, and to generate and store process execution data.

[0127] Furthermore, the performance data acquisition module 20 may include:

[0128] The line-of-code acquisition unit is used to obtain the code submission subject, code submission time, and line-of-code number of a process node from the code development tool;

[0129] The result acquisition unit is used to obtain the number of builds, build time, and build results of process nodes from the integrated R&D tools;

[0130] The pass rate acquisition unit is used to obtain the number of test cases created, the number of executions, and the pass rate of process nodes from the test case creation tool;

[0131] The test case coverage acquisition unit is used to obtain online defect count, missed test rate, failure rate and test case coverage from the testing tools.

[0132] Furthermore, the code line count acquisition unit may include:

[0133] The data synchronization subunit is used to obtain the code submission subject, code submission time, and code line number of process nodes from the code development tool through interface calls or timed synchronization.

[0134] Furthermore, the report generation module 30 may include:

[0135] The performance data cleaning unit is used to clean the process execution data and various performance data.

[0136] The R&D data link generation unit is used to associate the cleaned process execution data and various performance data to form an R&D data link;

[0137] The report generation unit is used to analyze the R&D data link and generate an R&D indicator analysis report.

[0138] Furthermore, the report generation unit may include:

[0139] The process blockage analysis unit is used to analyze the process blockage of the R&D data link and generate an R&D indicator analysis report.

[0140] Furthermore, the report generation unit may include:

[0141] The dwell time analysis subunit is used to generate an R&D indicator analysis report based on the dwell time of each process node represented by the R&D data link and the test pass rate of the process node.

[0142] The R&D data management device provided in this application embodiment can be applied to R&D data management equipment, such as PC terminals, cloud platforms, servers, and server clusters. Optionally, Figure 3 The hardware structure block diagram of the R&D data management device is shown below. Figure 3 The hardware structure of the R&D data management device may include: at least one processor 1, at least one communication interface 2, at least one memory 3, and at least one communication bus 4;

[0143] In this embodiment of the application, the number of processor 1, communication interface 2, memory 3, and communication bus 4 is at least one, and processor 1, communication interface 2, and memory 3 communicate with each other through communication bus 4;

[0144] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0145] Memory 3 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device;

[0146] The memory stores a program, which the processor can call. The program is used for:

[0147] Obtain the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is set with a corresponding tracking point.

[0148] Obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project;

[0149] The process execution data and the performance data of each R&D output are processed to generate an R&D indicator analysis report.

[0150] Optionally, the refined and extended functions of the program can be referred to the above description.

[0151] This application embodiment also provides a readable storage medium that can store a program suitable for execution by a processor, the program being used for:

[0152] Obtain the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is set with a corresponding tracking point.

[0153] Obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project;

[0154] The process execution data and the performance data of each R&D output are processed to generate an R&D indicator analysis report.

[0155] Optionally, the refined and extended functions of the program can be referred to the above description.

[0156] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0157] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0158] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. The various embodiments of this application can be combined with each other. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A research and development data management method characterized by comprising: include: Obtain the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is set with a corresponding tracking point. Obtain performance data of different R&D outputs from all external R&D tools corresponding to the current R&D project; The process execution data and the performance data of each R&D output are processed to generate an R&D indicator analysis report.

2. The R&D data management method according to claim 1, characterized by, The acquisition of process execution data corresponding to the current R&D project includes: When an update event of a development node is detected, the update subject, update time, and update node are collected, and process execution data is generated and stored.

3. The R&D data management method according to claim 1, characterized by, The acquisition of performance data for different R&D outputs of all external R&D tools corresponding to the current R&D project includes: Obtain the code submission subject, code submission time, and code line number of each process node from the code development tool; Obtain the number of builds, build time, and build results for each process node from integrated R&D tools; Obtain the number of test cases created, executed, and pass rate for each process node from the test case creation tool; The online defect count, missed test rate, failure rate, and test case coverage are obtained from the testing tools.

4. The R&D data management method according to claim 3, characterized by, The process of obtaining the code submission subject, code submission time, and code line number of the process node from the code development tool includes: The code submission subject, submission time, and line number of each process node can be obtained from the code development tool via API calls or scheduled synchronization.

5. The R&D data management method according to claim 1, characterized by, The process of processing the execution data of the process and the efficiency data of each R&D output to generate an R&D indicator analysis report includes: The process execution data and various performance data are cleaned. The cleaned process execution data and various performance data are correlated to form a research and development data link; The R&D data chain is analyzed to generate an R&D indicator analysis report.

6. The R&D data management method according to claim 5, characterized by, The R&D data chain is analyzed to generate an R&D indicator analysis report, including: Analyze the process blockages in the R&D data link and generate an R&D indicator analysis report.

7. The R&D data management method according to claim 6, characterized by, The analysis of process blockages in the R&D data chain generates an R&D indicator analysis report, including: Based on the dwell time of each process node represented by the R&D data link and the test pass rate of the process node, an R&D indicator analysis report is generated.

8. A research and development data management device, characterized in that, include: The process execution data acquisition module is used to acquire the process execution data corresponding to the current R&D project. The process execution data is collected by the tracking points set on the project management platform of the instant messaging system. The project management platform contains all the R&D process nodes of the current R&D project, and each R&D process node is equipped with a corresponding tracking point. The performance data acquisition module is used to acquire performance data of different R&D outputs of all external R&D tools corresponding to the current R&D project. The report generation module is used to process the process execution data and the performance data of each R&D output to generate an R&D indicator analysis report.

9. A research and development data management device, characterized in that, Including memory and processor; The memory is used to store programs; The processor is used to execute the program to implement each step of the R&D data management method as described in any one of claims 1-7.

10. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the R&D data management method as described in any one of claims 1-7.

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