A project R&D capability diagnosis method and system

Abstract

The present invention discloses a method and system for diagnosing project R&D capabilities. The method captures data from a data source through a thread to form a R&D data warehouse. After the R&D data in the R&D data warehouse is cleaned to obtain structured data, it is input into a pre-established diagnostic model to perform an overall diagnosis of the R&D project capabilities and obtain scoring information corresponding to the diagnostic results. Based on the scoring information corresponding to the diagnostic results, a scoring report is generated to display the outstanding items and problem points of related products. Through the product status clearly displayed by the above diagnostic scheme, managers and project personnel can determine the future product R&D direction and formulate strategies for the project. In addition, during the R&D implementation and improvement process, the change data returned to the warehouse will be reflected in the diagnostic system again to form a closed-loop management. The proposal of the above scheme solves the problems of no perception of R&D process capabilities, high-intensity analysis, and difficulty in formulating improvement measures in the past.

Description

Technical Field

[0001] The present invention relates to a method and a system, and in particular to a project R&D capability diagnosis method and a system. Background Art

[0002] Existing projects often generate a large amount of data during the R&D process, but most of this data may be semi-structured or even unstructured. As a result, many products do not integrate and utilize this data. Better products will initially integrate this data and then define it as indicators. However, due to the large number of indicators and different target groups, it is often impossible to grasp the key points or directly point out the problem. It takes a lot of time to re-analyze, and it may not necessarily achieve the expected results, which is time-consuming and laborious. Summary of the invention

[0003] The purpose of the present invention is to provide a project R&D capability diagnosis method and system. After cleaning the data to obtain structured data, the project diagnosis system can be used to perform an overall diagnosis of the R&D project capability and visually point out the problems of the project. This can solve the problem of no perception of R&D process capability, high-intensity analysis, and difficulty in formulating improvement measures.

[0004] The technical solution adopted by the present invention is:

[0005] A project R&D capability diagnosis method, comprising:

[0006] Capture data from data sources through threads to form a research and development data warehouse;

[0007] After the R&D data in the R&D data warehouse is cleaned to obtain structured data, the data is input into a pre-established diagnostic model, and the R&D project capabilities are diagnosed as a whole through the diagnostic model, and scoring information corresponding to the diagnostic results is obtained;

[0008] Generate a scoring report based on the scoring information corresponding to the diagnosis results, showing the excellent items and problems of related products;

[0009] Wherein, the diagnostic model is constructed based on data captured from the data source.

[0010] Preferably, the capturing of data from a data source through a thread to form a research and development data warehouse includes:

[0011] Configure multiple data source information in the application, and load the data source configuration items when starting the application;

[0012] Establish an independent thread of the connection pool for each data source, and a single thread operates a single data source;

[0013] When adding a new data source, add the corresponding configuration data source information and start a connection pool thread for the new data source;

[0014] When the system starts a log file of a data collection thread; multiple parallel data collection threads are started according to the log file, and when an instruction for synchronous data collection for each service terminal is received, the target data in each data source is collected through the data collection thread;

[0015] The receiving thread receives the collected data, summarizes the collected data, and generates a research and development data warehouse.

[0016] Preferably, the step of cleaning the data in the R&D data warehouse to obtain structured data includes:

[0017] The data in the R&D data warehouse is classified according to pre-defined indicators for judging the project R&D capabilities, and the classified data is cleaned to filter out erroneous data to obtain structured data.

[0018] Preferably, the diagnostic model is constructed based on the data captured by the data source, including:

[0019] Obtain pre-defined indicators for judging project R&D capabilities, and formulate corresponding project score rules and weight ratios for each indicator, so as to automatically check and score the R&D capabilities of each product;

[0020] Acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples;

[0021] The input parameters are used as input parameters for judging the project R&D capability, the score values ​​and weight ratios corresponding to the indicators are used as target data to establish a diagnostic model, and the diagnostic model is trained using the training samples to obtain a diagnostic model for judging the project R&D capability.

[0022] Furthermore, the predefined indicators for judging the project R&D capability include: quality, efficiency and platform capability indicators;

[0023] The indicator includes one or more sub-indicators;

[0024] Among them, the sub-indicators of quality indicators include: missed test rate, demand delay delivery rate, and test rejection rate;

[0025] The sub-indicators of the efficiency indicator include: demand delivery and demand development cycle;

[0026] The sub-indicators of the platform capability indicator include automation coverage and use case conversion rate.

[0027] A project R&D capability diagnosis system, comprising:

[0028] The database establishment module is used to capture data from the data source through threads to form a research and development data warehouse;

[0029] The diagnostic module is used to clean the R&D data in the R&D data warehouse to obtain structured data and then input the data into the pre-

[0030] First, establish a diagnostic model, use it to conduct an overall diagnosis of the R&D project capabilities, and obtain the scoring information corresponding to the diagnostic results;

[0031] Visual display module, used to generate a scoring report based on the scoring information corresponding to the diagnosis results, and to display the excellent items and problems of related products;

[0032] Wherein, the diagnostic model is constructed based on data captured from the data source.

[0033] Preferably, the database establishment module includes:

[0034] A first configuration unit is used to configure multiple data source information in the application program, and load the data source configuration items when the application program is started;

[0035] The second configuration unit is used to establish an independent thread of a connection pool for each data source, and a single thread operates a single data source;

[0036] The startup unit is used to add corresponding configuration data source information when adding a data source, and start a connection pool thread for the newly added data source;

[0037] A collection unit, configured to start a plurality of parallel data collection threads according to a log file of a data collection thread when the system starts the log file, and collect target data in each data source through the data collection thread when receiving an instruction to perform synchronous data collection for each service terminal;

[0038] The database generation unit is used for receiving the collected data through the receiving thread, summarizing the collected data, and generating a research and development data warehouse.

[0039] Preferably, the diagnostic module comprises:

[0040] The classification unit is used to classify the data in the R&D data warehouse according to pre-defined indicators for judging the R&D capabilities of the project;

[0041] The cleaning unit is used to clean the classified data, filter out erroneous data, and obtain structured data.

[0042] Preferably, the project R&D capability diagnosis system further comprises: a construction module for constructing a diagnosis model based on data captured by a data source;

[0043] Wherein, the building blocks include:

[0044] The acquisition unit is used to obtain pre-defined indicators for judging the R&D capability of the project, and formulate the corresponding project score rules and weight proportions for each indicator, so as to automatically check and score the R&D capability of each product;

[0045] A sample acquisition unit, used to acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples;

[0046] The model training unit is used to use the input parameters as input parameters for judging the project R&D capability, and to establish a diagnostic model with the score value and weight ratio corresponding to the indicator as target data, and to train the diagnostic model using the training samples to obtain a diagnostic model for judging the project R&D capability.

[0047] Compared with the closest prior art, the technical solution of the present invention has the following advantages:

[0048] When facing a large amount of R&D data generated during the R&D process, project personnel and managers often feel confused when they want to obtain high-value data for analysis. The project R&D capability diagnosis method and system proposed in the present invention is based on existing R&D data, and uses the platform data diagnosis and visual recognition capabilities to intelligently express, analyze, and test project R&D capabilities, so that project personnel can see their shortcomings, and managers can clearly formulate guidance directions based on the results. This will help improve efficiency, ensure quality, and reduce costs for the project.

[0049] After the data is cleaned to obtain structured data, the present invention uses the project diagnosis system to conduct an overall diagnosis of the R&D project capabilities and visually point out the problems of the project. This solves the problem of no perception of R&D process capabilities, high-intensity analysis, and difficulty in formulating improvement measures in the past. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flow chart of a project R&D capability diagnosis method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments. The following embodiments are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0052] refer to Figure 1 This embodiment provides a method for diagnosing project R&D capabilities from the aspects of acquiring data, analyzing data, presenting data and diagnosing data. The method includes the following steps:

[0053] S1 captures data from the data source through threads to form a R&D data warehouse;

[0054] S2: After cleaning the R&D data in the R&D data warehouse to obtain structured data, the data is input into a pre-established diagnostic model, and the R&D project capabilities are diagnosed as a whole through the diagnostic model, and scoring information corresponding to the diagnostic results is obtained; wherein the diagnostic model is constructed based on the data captured from the data source;

[0055] S3 generates a scoring report based on the scoring information corresponding to the diagnostic results, showing the outstanding items and problems of related products.

[0056] In step S1, the data in the data source is captured through threads to form a research and development data warehouse, including:

[0057] Configure multiple data source information in the application, and load the data source configuration items when starting the application;

[0058] Establish an independent thread of the connection pool for each data source, and a single thread operates a single data source;

[0059] When adding a new data source, add the corresponding configuration data source information and start a connection pool thread for the new data source;

[0060] When the system starts a log file of a data collection thread; multiple parallel data collection threads are started according to the log file, and when an instruction for synchronous data collection for each service terminal is received, the target data in each data source is collected through the data collection thread;

[0061] The receiving thread receives the collected data, summarizes the collected data, and generates a research and development data warehouse.

[0062] In step S2, the data in the R&D data warehouse is cleaned to obtain structured data, including:

[0063] The data in the R&D data warehouse is classified according to pre-defined indicators for judging the project R&D capabilities, and the classified data is cleaned to filter out erroneous data to obtain structured data.

[0064] Pre-defined indicators for judging project R&D capabilities include: quality, efficiency, and platform capability indicators;

[0065] The indicator includes one or more sub-indicators;

[0066] Among them, the sub-indicators of quality indicators include: missed test rate, demand delay delivery rate, and test rejection rate;

[0067] The sub-indicators of the efficiency indicator include: demand delivery and demand development cycle;

[0068] The sub-indicators of the platform capability indicator include automation coverage and use case conversion rate.

[0069] In step S2, the diagnostic model is constructed based on the data captured by the data source, including:

[0070] Obtain pre-defined indicators for judging project R&D capabilities, and formulate corresponding project score rules and weight ratios for each indicator, so as to automatically check and score the R&D capabilities of each product;

[0071] Acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples;

[0072] The input parameters are used as input parameters for judging the project R&D capability, the score values ​​and weight ratios corresponding to the indicators are used as target data to establish a diagnostic model, and the diagnostic model is trained using the training samples to obtain a diagnostic model for judging the project R&D capability.

[0073] The above solution can be implemented through the following application architecture, including:

[0074] 1. Data is stored in MySQL, and the data sources include Jira, Tapd, Titan, etc.

[0075] 2. The server has python, APscheduler, and logzero. Python is used to write the backend. Apscheduler executes the specified job at the specified time rule, and logzero is responsible for log output.

[0076] 3. DingTalk and authentication are public services, mainly responsible for message reminders and authentication

[0077] 4. The gateway component is Nginx

[0078] 5. The front end includes Node, Vue, Echart and other components, which are mainly responsible for the display of diagnostic data

[0079] In the application architecture:

[0080] Data collection: mainly through API, MQ to obtain data, data sources include JIRA, TAPD, TITAN, SONARQUBE

[0081] Data analysis: The analysis is mainly concentrated on the backend, Python is used to write logical processing, and Apscheduler is used for timing processing. Data storage: MySQL is used for data storage, mainly for data storage

[0082] Data monitoring: authority management through authentication services, and alarm notifications through email and DingTalk

[0083] Data display: The front end is written in Vue for responsive data display and interaction

[0084] Embodiment 1:

[0085] Based on the above scheme, the following embodiment 1 is specifically proposed:

[0086] 1. The system captures data from the data source through threads every day to form a R&D data warehouse

[0087] 2. Classify the data in the data warehouse by indicators and clean up some erroneous or useless data to facilitate the subsequent construction of the data model.

[0088] 3. The diagnostic model consists of three major dimensions: quality, efficiency and platform capabilities. For each major dimension, there are corresponding sub-indicators. For example, quality is composed of missed detection rate, delayed delivery rate, and test rejection rate. Efficiency is composed of demand delivery and demand R&D cycle. Platform capabilities are composed of automation coverage and use case conversion rate.

[0089] 4. Based on the diagnostic model, formulate corresponding scoring rules and weight ratios for each indicator. For example:

[0090] Demand delayed delivery rate, the score rule is weight * demand delivery rate, and the weight is 50%

[0091] 5. According to the rules set for each project every day, the R&D capabilities of each product are automatically checked and scored. Then, a scoring report is sent to each project personnel based on the scoring results, showing the product's outstanding items and problems.

[0092] 6. Managers and project personnel can open the diagnostic system to clearly display the excellent items and problems of the product. Users can clarify the strategy through the displayed status: self-improvement and downward drive, etc.

[0093] 7. In the process of implementing improvements, R&D will generate changing data. The data will be returned to the warehouse and reflected in the diagnostic system again, forming a closed-loop management.

[0094] Embodiment 2: Based on the same technical concept, the present invention also provides a project R&D capability diagnosis system, including:

[0095] The database establishment module is used to capture data from the data source through threads to form a research and development data warehouse;

[0096] The diagnostic module is used to clean the R&D data in the R&D data warehouse to obtain structured data and then input the data into the pre-

[0097] First, establish a diagnostic model, use it to conduct an overall diagnosis of the R&D project capabilities, and obtain the scoring information corresponding to the diagnostic results;

[0098] Visual display module, used to generate a scoring report based on the scoring information corresponding to the diagnosis results, and to display the excellent items and problems of related products;

[0099] Wherein, the diagnostic model is constructed based on data captured from the data source.

[0100] Wherein, the database establishment module includes:

[0101] A first configuration unit is used to configure multiple data source information in the application program, and load the data source configuration items when the application program is started;

[0102] The second configuration unit is used to establish an independent thread of a connection pool for each data source, and a single thread operates a single data source;

[0103] The startup unit is used to add corresponding configuration data source information when adding a data source, and start a connection pool thread for the newly added data source;

[0104] A collection unit, configured to start a plurality of parallel data collection threads according to a log file of a data collection thread when the system starts the log file, and collect target data in each data source through the data collection thread when receiving an instruction to perform synchronous data collection for each service terminal;

[0105] The database generation unit is used for receiving the collected data through the receiving thread, summarizing the collected data, and generating a research and development data warehouse.

[0106] The diagnostic module comprises:

[0107] The classification unit is used to classify the data in the R&D data warehouse according to pre-defined indicators for judging the R&D capabilities of the project;

[0108] The cleaning unit is used to clean the classified data, filter out erroneous data, and obtain structured data.

[0109] In addition, the project R&D capability diagnosis system also includes: a construction module for building a diagnostic model based on the data captured by the data source;

[0110] Wherein, the building blocks include:

[0111] The acquisition unit is used to obtain pre-defined indicators for judging the R&D capability of the project, and formulate the corresponding project score rules and weight proportions for each indicator, so as to automatically check and score the R&D capability of each product;

[0112] A sample acquisition unit, used to acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples;

[0113] The model training unit is used to use the input parameters as input parameters for judging the project R&D capability, and to establish a diagnostic model with the score value and weight ratio corresponding to the indicator as target data, and to train the diagnostic model using the training samples to obtain a diagnostic model for judging the project R&D capability.

[0114] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0115] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application rather than to limit its protection scope. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present application, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, and these changes, modifications or equivalent substitutions are all within the scope of the claims to be approved by the application.

Claims

1. A project R&D capability diagnosis method, characterized in that: include: Capture data from data sources through threads to form a R&D data warehouse; After the R&D data in the R&D data warehouse is cleaned to obtain structured data, the data is input into a pre-established diagnostic model, and the R&D project capabilities are diagnosed as a whole through the diagnostic model, and scoring information corresponding to the diagnostic results is obtained; Generate a scoring report based on the scoring information corresponding to the diagnosis results, showing the excellent items and problems of related products; Wherein, the diagnostic model is constructed based on data captured from a data source; The diagnostic model is constructed based on the data captured by the data source, including: Obtain pre-defined indicators for judging project R&D capabilities, and formulate corresponding project score rules and weight ratios for each indicator, so as to automatically check and score the R&D capabilities of each product; Acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples; The input parameters are used as input parameters for diagnosing the R&D capability of the project, the score values ​​and weight ratios corresponding to the indicators are used as target data to establish a diagnostic model, and the diagnostic model is trained using the training samples to obtain a diagnostic model for judging the R&D capability of the project.

2. The method according to claim 1, characterized in that The method of capturing data from a data source through a thread to form a research and development data warehouse includes: Configure multiple data source information in the application, and load the data source configuration items when starting the application; Establish an independent connection pool for each data source, and operate a single data source in a single thread; When adding a new data source, add the corresponding configuration data source information and start a connection pool thread for the new data source; When the system starts the log file of the data collection thread; multiple parallel data collection threads are started according to the log file, and when an instruction for synchronous data collection for each business end is received, the target data in each data source is collected through the data collection thread; The receiving thread receives the collected data, summarizes the collected data, and generates a research and development data warehouse.

3. The method according to claim 1, characterized in that The step of obtaining structured data from the R&D data warehouse by cleaning the data includes: The data in the R&D data warehouse is classified according to the pre-defined indicators of the R&D capabilities of the diagnostic project, and the classified data is cleaned to filter out erroneous data to obtain structured data.

4. The method according to claim 1, characterized in that: The predefined indicators for judging the project R&D capability include: quality, efficiency and platform capability indicators; The indicator includes one or more sub-indicators; Among them, the sub-indicators of quality indicators include: missed test rate, demand delay delivery rate, and test rejection rate; The sub-indicators of the platform capability indicator include automation coverage and use case conversion rate.

5. A project R&D capability diagnosis system, characterized in that: include: The database establishment module is used to capture data from the data source through threads to form a research and development data warehouse; A construction module is used to build a diagnostic model based on the data captured by the data source; A diagnosis module, which is used to clean the R&D data in the R&D data warehouse to obtain structured data, input the data into a pre-established diagnosis model, perform an overall diagnosis of the R&D project capabilities through the diagnosis model, and obtain scoring information corresponding to the diagnosis results; Visual display module, used to generate a scoring report based on the scoring information corresponding to the diagnosis results, and to display the excellent items and problems of related products; Wherein, the building blocks include: The acquisition unit is used to obtain pre-defined indicators for judging the R&D capability of the project, and formulate the corresponding project score rules and weight proportions for each indicator, so as to automatically check and score the R&D capability of each product; A sample acquisition unit, used to acquire a research and development data warehouse, select input parameters in the research and development data warehouse, and perform structured processing on the input parameters in the research and development data warehouse according to the indicators to construct training samples; The model training unit is used to use the input parameters as input parameters for diagnosing the R&D capabilities of the project, and to establish a diagnostic model with the score value and weight ratio corresponding to the indicator as target data, and to train the diagnostic model using the training samples to obtain a diagnostic model for judging the R&D capabilities of the project.

6. The system according to claim 5, characterized in that The database establishment module includes: A first configuration unit is used to configure multiple data source information in the application program, and load the data source configuration items when the application program is started; The second configuration unit is used to establish an independent connection pool for each data source, and a single thread operates a single data source; The startup unit is used to add corresponding configuration data source information when adding a data source, and start a connection pool thread for the newly added data source; A collection unit is used to start a log file of a data collection thread when the system starts; start multiple parallel data collection threads according to the log file, and when receiving an instruction to perform synchronous data collection for each business end, collect the target data in each data source through the data collection thread; The database generation unit is used for receiving the collected data through the receiving thread, summarizing the collected data, and generating a research and development data warehouse.

7. The system according to claim 5, characterized in that The diagnostic module comprises: A classification unit is used to classify the data in the R&D data warehouse according to pre-defined indicators of the R&D capability of the diagnostic project; The cleaning unit is used to clean the classified data, filter out erroneous data, and obtain structured data.

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