Data management system based on agile development application

Abstract

The invention belongs to the field of agile development, relates to a data management technology, is used for solving the problem that agile development processing methods cannot be matched and screened according to development task characteristics before project development in the prior art, and particularly relates to a data management system based on agile development application, which comprises a data management platform, the system comprises a development statistics module, a development execution module, an optimization development module and a database. Obtaining development data and sending the development data to a database through the data management platform; after the database receives the development data, the number of the development data in the database is counted, an accumulated development value is obtained, and development processing mode analysis is conducted through the accumulated development value; according to the method, the agile development task can be subjected to optimized development processing, the recommendation method is obtained, and the recommendation method is an agile processing method which is obtained through multi-angle screening and is most suitable for executing the development object development task, so that the execution efficiency of agile development is improved.

Description

Technical Field

[0001] The present invention belongs to the field of agile development, relates to data management technology, and specifically is a data management system based on agile development application. Background Art

[0002] Agile development focuses on the evolution of user needs and adopts an iterative, step-by-step approach to software development. In agile development, software projects are divided into multiple sub-projects at the initial stage of construction. The results of each sub-project are tested and have the characteristics of being visible, integrable, and operational.

[0003] The invention patent with announcement number CN111445137B discloses an agile development management system and method. The agile development management system detects agile development data more comprehensively and meticulously from multiple detection dimensions, realizes effective management and accurate detection of agile development data, and enables the software development team to easily learn about its shortcomings and make improvements and optimizations. However, there are many agile development processing methods. The existing technology cannot match and screen agile development processing methods according to the characteristics of development tasks before project development, resulting in agile development projects being unable to directly adopt the most appropriate agile processing method for development and processing, resulting in the inability to improve the execution efficiency of agile development.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a data management system based on agile development applications, which is used to solve the problem that the prior art cannot match and screen agile development processing methods according to development task characteristics before project development;

[0006] The technical problem to be solved by the present invention is: how to provide a data management system based on agile development applications that can match and screen agile development processing methods according to development task characteristics before project development.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A data management system based on agile development applications, comprising a data management platform, wherein the data management platform is communicatively connected with a development statistics module, a development execution module, an optimization development module and a database;

[0009] The development statistics module is used to perform statistical analysis on the development data when receiving an agile development task: the development data includes the task coefficient RW, application field, and number of people supplied by the development team of the agile development task; the development data is sent to the database through the data management platform; after receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value, and analyzes the development processing method based on the cumulative development value;

[0010] The development execution module is used to perform development processing on the agile development task: randomly select a method from the agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, mark the ratio of the actual development time to the task coefficient RW as the actual efficiency value of the agile development task; send the actual efficiency value of the agile development task to the database through the data management platform;

[0011] The optimized development module is used to optimize the development processing of agile development tasks: marking the agile development tasks to be processed as development objects, screening recommended methods for the development objects from agile processing methods, developing the development objects using the recommended methods, and sending the actual efficiency values ​​of the development objects to the database through the data management platform after the development is completed.

[0012] Furthermore, the process of obtaining the task coefficient RW of the agile development task includes: marking the number of function points of the agile development task as function data GN, obtaining the average development time of each function point of the agile development task in the historical development process and marking it as the historical efficiency value of the function point, and summing the historical efficiency values ​​of all function points of the agile development task to obtain the time consumption data HS; the task coefficient RW of the agile development task is obtained by the formula RW=k1*GN+k2*HS, where k1 and k2 are both proportional coefficients, and k1>k2>1.

[0013] Furthermore, the specific process of development processing method analysis includes: comparing the cumulative development value with the preset cumulative development threshold: if the cumulative development value is less than the cumulative development threshold, then generating a development execution signal and sending the development execution signal to the development execution module through the data management platform; if the cumulative development value is greater than or equal to the cumulative development threshold, then generating an optimized development signal and sending the optimized development signal to the optimized development module through the data management platform.

[0014] Furthermore, the specific process of the optimized development module performing optimized development processing on the agile development task includes: filtering the historical development data to obtain secondary data; forming a task range from the maximum and minimum values ​​of the task coefficient RW in all the secondary data, dividing the task range into several task intervals, calculating the average value of the actual efficiency values ​​of all the secondary data corresponding to different agile processing methods with the task coefficient RW located in the task interval and marking it as the task priority value of the agile processing method relative to the task interval; forming a supply range from the maximum and minimum values ​​of the number of development team suppliers in all the secondary data, dividing the supply range into several supply intervals, calculating the average value of the actual efficiency values ​​of all the secondary data corresponding to different agile processing methods with the number of team suppliers located in the supply interval and marking it as the supply priority value of the agile processing method relative to the supply interval; then marking the task lock interval and the supply lock interval of the development object, marking the sum of the task priority value of the agile processing method relative to the task lock interval and the supply priority value relative to the supply lock interval as the comprehensive priority value of the agile processing method, and marking the agile processing method with the smallest comprehensive priority value as the recommended method.

[0015] Furthermore, the secondary data acquisition process includes: marking the agile development tasks to be processed as development objects, retrieving all historical development data through the database and marking them as reference data, and marking the reference data whose application fields are exactly the same as the application fields of the development objects as secondary data.

[0016] Furthermore, the process of obtaining the task lock interval and the supply lock interval of the development object includes: obtaining the task coefficient RW of the development object and the number of supply persons of the development team, marking the task interval corresponding to the task coefficient RW of the development object as the task lock interval, and marking the supply interval corresponding to the number of supply persons of the development team of the development object as the supply lock interval.

[0017] Furthermore, the working method of the data management system based on agile development application comprises the following steps:

[0018] Step 1: Statistically analyze the development data and send the development data to the database through the data management platform; after receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value;

[0019] Step 2: Determine whether the cumulative development value is less than the cumulative development threshold: if so, execute step 3; if not, execute step 4;

[0020] Step 3: Randomly select a method from the agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, send the actual efficiency value of the agile development task to the database through the data management platform;

[0021] Step 4: Optimize the development of agile development tasks: Mark the agile development tasks to be processed as development objects, retrieve all historical development data from the database and mark them as reference data, and filter the secondary data in the reference data by application field;

[0022] Step 5: Generate task intervals and supply intervals, mark the task lock intervals and supply lock intervals according to the task coefficient RW of the development object and the development team supply data, obtain the comprehensive priority value through the task lock interval and supply lock interval, and screen the recommended methods through the comprehensive priority value.

[0023] The present invention has the following beneficial effects:

[0024] 1. The development statistics module can be used to perform statistical analysis on development data when receiving agile development tasks. After the development data is sent to the database, the total amount of development data stored is counted to obtain the cumulative development value. The development method is selected based on the cumulative development value, providing users with a variety of agile processing methods.

[0025] 2. The development execution module can be used to perform routine development processing on agile development tasks. The execution method can be randomly selected from the agile processing method to develop agile development tasks. After the development is completed, the actual efficiency value of the development process is counted to provide data support for optimizing the development processing process.

[0026] 3. Agile development tasks can be optimized through the development optimization module. Recommended methods can be screened and marked according to the application field of the development object, task coefficient RW, team development supply data and all historical development data. The recommended method is the most suitable agile processing method for executing the development task of the development object obtained from multiple angles, thereby improving the execution efficiency of agile development. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0029] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0030] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Embodiment 1: Figure 1 As shown, a data management system based on agile development applications includes a data management platform, which is communicatively connected to a development statistics module, a development execution module, an optimization development module and a database.

[0032] The development statistics module is used to perform statistical analysis on the development data when receiving an agile development task: the development data includes the task coefficient RW, application field, and number of development team supply of the agile development task, where the number of development team supply is the number of developers assigned by the platform for the agile development task; the process of obtaining the task coefficient RW of the agile development task includes: marking the number of function points of the agile development task as function data GN, obtaining the average development time of each function point of the agile development task in the historical development process and marking it as the historical efficiency value of the function point, and summing up the historical efficiency values ​​of all function points of the agile development task to obtain the time consumption data HS; the task coefficient RW of the agile development task is obtained by the formula RW=k1*GN+k2*HS, where k1 and k2 are both proportional coefficients, and k1>k2>1;

[0033] The development data is sent to the database through the data management platform; after the database receives the development data, the amount of development data in the database is counted and the cumulative development value is obtained, and the cumulative development value is compared with the preset cumulative development threshold: if the cumulative development value is less than the cumulative development threshold, a development execution signal is generated and sent to the development execution module through the data management platform; if the cumulative development value is greater than or equal to the cumulative development threshold, an optimized development signal is generated and sent to the optimized development module through the data management platform; when an agile development task is received, the development data is statistically analyzed, and after the development data is sent to the database, the total storage amount of the development data is counted to obtain the cumulative development value, and the development method is selected based on the cumulative development value, providing users with a variety of agile processing methods.

[0034] The development execution module is used to develop and process agile development tasks: randomly select a method from agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, mark the ratio of the actual development time to the task coefficient RW as the actual efficiency value of the agile development task; agile processing methods include Scrum, incremental iterative development, XP (extreme programming), Lean and Kanban;

[0035] Scrum is a commonly used agile method that emphasizes teamwork, continuous delivery, and constant feedback. Scrum usually includes activities such as Sprint planning meetings, daily stand-up meetings, Sprint retrospective meetings, and Sprint summary meetings;

[0036] Incremental iterative development means dividing the development process into multiple independent increments, each of which can be tested, released, and used, thereby reducing the risk of the entire development process;

[0037] XP is an agile method that combines rapid iteration and test-driven development. XP emphasizes practices such as teamwork, simple design, refactoring, and continuous integration.

[0038] Lean is a method that emphasizes value stream mapping, lean production, and waste reduction. It can be applied to project management, manufacturing, service provision, and other fields.

[0039] Kanban is a visualization-based approach to managing work by using boards, limiting workflow, and optimizing value flow.

[0040] The actual efficiency value of the agile development task is sent to the database through the data management platform; the execution method is randomly selected from the agile processing method to develop the agile development task, and the actual efficiency value of the development process is counted after the development is completed to provide data support for optimizing the development process.

[0041] The optimized development module is used to optimize the development processing of agile development tasks: mark the agile development tasks to be processed as development objects, retrieve all historical development data through the database and mark them as reference data, and mark the reference data whose application fields are exactly the same as those of the development objects as secondary data.

[0042] The maximum and minimum values ​​of the task coefficients RW in all the secondary data constitute the task range, and the task range is divided into several task intervals. The average value of the actual efficiency values ​​of all the secondary data corresponding to different agile processing methods with task coefficients RW in the task interval is calculated and marked as the task priority value of the agile processing method relative to the task interval;

[0043] The maximum and minimum values ​​of the number of development team supply in all secondary data constitute the supply range, and the supply range is divided into several supply intervals. The average value of the actual efficiency values ​​of all secondary data corresponding to different agile processing methods with team supply numbers within the supply interval is calculated and marked as the supply priority value of the agile processing method relative to the supply interval;

[0044] The task coefficient RW and the number of supply members of the development team are obtained, the task interval corresponding to the task coefficient RW of the development object is marked as the task lock interval, the supply interval corresponding to the number of supply members of the development team of the development object is marked as the supply lock interval, the sum of the task priority value of the agile processing method relative to the task lock interval and the supply priority value relative to the supply lock interval is marked as the comprehensive priority value of the agile processing method, the agile processing method with the smallest comprehensive priority value is marked as the recommended method, the development object is developed using the recommended method, and after the development is completed, the actual efficiency value of the development object is sent to the database through the data management platform; the recommended methods are screened and marked according to the application field of the development object, the task coefficient RW, the team development supply data and all historical development data. The recommended method is the agile processing method that is most suitable for executing the development task of the development object obtained from multi-angle screening, so as to improve the execution efficiency of agile development.

[0045] Embodiment 2: Figure 2 As shown, a data management method based on agile application development includes the following steps:

[0046] Step 1: Statistically analyze the development data and send the development data to the database through the data management platform; after receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value;

[0047] Step 2: Determine whether the cumulative development value is less than the cumulative development threshold: if so, execute step 3; if not, execute step 4;

[0048] Step 3: Randomly select a method from the agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, send the actual efficiency value of the agile development task to the database through the data management platform;

[0049] Step 4: Optimize the development of agile development tasks: Mark the agile development tasks to be processed as development objects, retrieve all historical development data from the database and mark them as reference data, and filter the secondary data in the reference data by application field;

[0050] Step 5: Generate task intervals and supply intervals, mark the task lock intervals and supply lock intervals according to the task coefficient RW of the development object and the supply data of the development team, mark the sum of the task priority value of the agile processing method relative to the task lock interval and the supply priority value relative to the supply lock interval as the comprehensive priority value of the agile processing method, screen the recommended methods according to the comprehensive priority value, and use the recommended methods to develop and process the development tasks.

[0051] A data management system based on agile development applications, when working, statistically analyzes the development data and sends the development data to the database through the data management platform; after receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value; determines whether the cumulative development value is less than the cumulative development threshold: if so, randomly selects a method from the agile processing methods as the execution method, and develops the agile development task using the execution method; if not, optimizes the development processing of the agile development task and screens the recommended methods, and uses the recommended method to develop the development task.

[0052] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0053] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula RW = k1*GN + k2*HS; technicians in this field collect multiple groups of sample data and set corresponding task coefficients for each group of sample data; substitute the set task coefficients and the collected sample data into the formula, any two formulas constitute a set of two-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of k1 and k2 as 3.68 and 2.12 respectively;

[0054] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding task coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the task coefficient is proportional to the value of the functional data.

[0055] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0056] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data management system based on agile development application, characterized in that: It includes a data management platform, which is communicatively connected with a development statistics module, a development execution module, an optimization development module and a database; The development statistics module is used to perform statistical analysis on the development data when receiving the agile development task: the development data includes the task coefficient RW, application field, and number of people supplied by the development team of the agile development task; Send development data to the database through the data management platform; After receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value, and analyzes the development processing method based on the cumulative development value; The development execution module is used to perform development processing on the agile development task: randomly select a method from the agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, mark the ratio of the actual development time to the task coefficient RW as the actual efficiency value of the agile development task; Send the actual efficiency value of the agile development task to the database through the data management platform; The optimized development module is used to optimize the development processing of agile development tasks: marking the agile development tasks to be processed as development objects, screening recommended methods for the development objects from agile processing methods, developing the development objects using the recommended methods, and sending the actual efficiency values ​​of the development objects to the database through the data management platform after the development is completed.

2. A data management system based on agile development application according to claim 1, characterized in that: The process of obtaining the task coefficient RW of the agile development task includes: marking the number of function points of the agile development task as function data GN, obtaining the average development time of each function point of the agile development task in the historical development process and marking it as the historical efficiency value of the function point, and summing the historical efficiency values ​​of all function points of the agile development task to obtain the time consumption data HS; the task coefficient RW of the agile development task is obtained by the formula RW=k1*GN+k2*HS, where k1 and k2 are both proportional coefficients, and k1>k2>1.

3. A data management system based on agile development application according to claim 2, characterized in that: The specific process of development processing method analysis includes: comparing the cumulative development value with the preset cumulative development threshold: if the cumulative development value is less than the cumulative development threshold, then generating a development execution signal and sending the development execution signal to the development execution module through the data management platform; if the cumulative development value is greater than or equal to the cumulative development threshold, then generating an optimized development signal and sending the optimized development signal to the optimized development module through the data management platform.

4. A data management system based on agile development application according to claim 3, characterized in that: The specific process of the optimized development module for optimizing the development of agile development tasks includes: filtering historical development data to obtain secondary data; forming a task range from the maximum and minimum values ​​of the task coefficient RW in all secondary data, dividing the task range into several task intervals, calculating the average value of the actual efficiency values ​​of all secondary data corresponding to different agile processing methods with the task coefficient RW in the task interval and marking it as the task priority value of the agile processing method relative to the task interval; forming a supply range from the maximum and minimum values ​​of the number of development team suppliers in all secondary data, dividing the supply range into several supply intervals, calculating the average value of the actual efficiency values ​​of all secondary data corresponding to different agile processing methods with the number of team suppliers in the supply interval and marking it as the supply priority value of the agile processing method relative to the supply interval; then marking the task lock interval and the supply lock interval of the development object, marking the sum of the task priority value of the agile processing method relative to the task lock interval and the supply priority value relative to the supply lock interval as the comprehensive priority value of the agile processing method, and marking the agile processing method with the smallest comprehensive priority value as the recommended method.

5. A data management system based on agile development application according to claim 4, characterized in that: The process of acquiring secondary data includes: marking the agile development tasks to be processed as development objects, retrieving all historical development data through the database and marking them as reference data, and marking the reference data whose application fields are exactly the same as those of the development objects as secondary data.

6. A data management system based on agile development application according to claim 5, characterized in that: The process of obtaining the task lock interval and the supply lock interval of the development object includes: obtaining the task coefficient RW of the development object and the number of supply members of the development team, marking the task interval corresponding to the task coefficient RW of the development object as the task lock interval, and marking the supply interval corresponding to the number of supply members of the development team of the development object as the supply lock interval.

7. A data management system based on agile development applications according to any one of claims 1 to 6, characterized in that: The working method of the data management system based on agile development application includes the following steps: Step 1: Statistically analyze the development data and send the development data to the database through the data management platform; after receiving the development data, the database counts the number of development data in the database and obtains the cumulative development value; Step 2: Determine whether the cumulative development value is less than the cumulative development threshold: if so, execute step 3; if not, execute step 4; Step 3: Randomly select a method from the agile processing methods as the execution method, use the execution method to develop the agile development task, and after the development is completed, send the actual efficiency value of the agile development task to the database through the data management platform; Step 4: Optimize the development of agile development tasks: Mark the agile development tasks to be processed as development objects, retrieve all historical development data from the database and mark them as reference data, and filter the secondary data in the reference data by application field; Step 5: Generate task intervals and supply intervals, mark the task lock intervals and supply lock intervals according to the task coefficient RW of the development object and the development team supply data, obtain the comprehensive priority value through the task lock interval and supply lock interval, and screen the recommended methods through the comprehensive priority value.

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