A data processing method in Git repository management

Abstract

The application discloses a data processing method in Git repository management, and relates to the technical field of software engineering. The method solves the problem that the different characteristic data entered in different time periods are not processed to monitor the progress of a project. The application identifies whether the progress of the project is abnormal based on the comprehensive characteristics of the project determined at the current time. The specific abnormality identification standard is based on the data characteristics generated by the project in the past period, so that the abnormal progress can be quickly and effectively identified. The abnormal progress is displayed based on the identified abnormal progress, so that the external relevant personnel can check and take timely measures to ensure that each different project can complete the related work within the controllable progress.

Description

Technical Field

[0001] This invention relates to the field of software engineering technology, specifically to a data processing method in Git repository management. Background Technology

[0002] In software development, Git, as a popular version control system, is widely used for code management. However, for large projects, effectively utilizing Git commit history to evaluate project progress and team member productivity has become a challenge. Existing tools often lack in-depth analysis and visualization of this data, making it difficult for developers to quickly obtain key information.

[0003] Application CN115586919A discloses a Git-based code management method and its management device. Specifically: based on a development task request, a master branch is created in a centralized repository; based on the development tasks on the master branch, multiple independent feature branches are created in the centralized repository, and a mapping relationship is established between the development tasks on the feature branches and the development tasks on the master branch, and they are cloned to the local repository; after the development tasks on the feature branches are completed, a dev branch is created in the centralized repository, and the feature branches that have completed the development tasks are merged into the dev branch, and simultaneously cloned to the local repository; after the dev branch passes self-testing, this branch is merged into the master branch, and after successful merging, the dev branch is deleted, and a tag branch is created and marked; in case of emergency handling, a hotfix branch is created in the centralized repository.

[0004] Currently, Git repositories only adjust and store the entered code data based on preset or specific data characteristics during data management. However, they do not process the different characteristic data entered in different time periods to monitor the project progress. Furthermore, they do not provide real-time feedback on whether the project progress is abnormal based on the corresponding entry progress. The original functionality of Git repositories needs to be enhanced. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a data processing method for Git repository management, which solves the problem of not processing data with different characteristics entered in different time periods for specific monitoring of project progress.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a data processing method in Git repository management, comprising the following steps:

[0007] Step 1: Define the monitoring association period. Confirm the code data packages that need to be uploaded to the Git repository within this association period. Based on the format standard associated with the corresponding branch of the project, process the code data packages to obtain the input data packages. The association period is a preset period. The specific method is as follows:

[0008] S11. Based on the relevant tags of this code data packet, determine the branch item to which this code data packet belongs, and then determine the format standard associated with the branch item. Different branch items correspond to different format standards, and the format standard is the spacing space between adjacent codes.

[0009] S12. Mark the relevant areas in the code data packet where there are no code symbols as empty areas. Based on the determined format standard, adjust the empty areas so that the internal layout format of the code data packet is consistent with the format of the code associated with the branch item. The format standard is the spacing between adjacent codes.

[0010] Step 2: Based on the multiple data packets confirmed within the association period, and based on the number and capacity of data packets for the same branch item, determine the entry characteristics of the corresponding branch item. Then, based on the entry characteristics of multiple branch items within the corresponding project, determine the comprehensive characteristics of the corresponding project. Finally, based on the comprehensive characteristics of the corresponding project confirmed in previous association periods and the comprehensive characteristics determined this time, generate the characteristic change curve for the corresponding project. The specific sub-steps are as follows:

[0011] S21. For a certain branch item within the association period, confirm the number of several data entry packets and label them as G. i-k Where i represents different projects, k represents different branch items, and then confirm the total amount of data Z entered from several data entry packages. i-k The total amount of data entered is the sum of the data capacities of several data entry packets, using T... i-k =G i-k ×C1+Z i-k ×C2 confirms the entry characteristics T of the corresponding branch item. i-k C1 and C2 are preset fixed coefficient factors, and the same method is used to determine the input characteristics of other branch items;

[0012] S22, Based on the different input characteristics T of different branches within the same project i-k The maximum and minimum values ​​are used to determine a range of values. Values ​​are selected within this range and labeled as the selected value Z. Values ​​greater than the selected value Z are entered using the input feature T. i-k Calibrated as TD i-k Input feature T that is less than the selected value i-k Calibrated as TX i-k, using TD i-k -Z=CD i-k Confirm TD i-k The difference between Z and Z is denoted as the elevation difference, using Z-TX. i-k =CX i-k Confirm Z and TX i-k The difference between them is marked as the low difference;

[0013] When a certain selected value Z satisfies: the sum of elevation differences = the sum of elevation differences, the sum of elevation differences is obtained by summing multiple elevation differences, and the sum of elevation differences is obtained by summing multiple elevation differences, this selected value Z is labeled as the comprehensive characteristic of this project;

[0014] S23. Based on the comprehensive characteristics confirmed in this project within the current correlation period, identify the comprehensive characteristics confirmed in the past 30 correlation periods from historical completion data, and generate the characteristic change curves belonging to this project according to the chronological order.

[0015] Step 3: Based on the confirmed characteristic change curve of the corresponding project, perform characteristic analysis on the terminal point of this characteristic change curve. Based on the change amplitude of this characteristic change curve, determine the corresponding change amplitude range, then confirm whether the numerical characteristics generated by this terminal point are abnormal, and display the signal. The specific sub-steps are as follows:

[0016] S31. Based on the end point of the characteristic change curve, confirm the line segment between the point before the end point and the initial point of the characteristic change curve, and mark it as the past historical curve.

[0017] S32. Based on the calibrated historical curves, determine the lowest and highest points of the historical curves, and define the range between the lowest and highest points as the numerical activity range. Randomly select a set of characteristic values ​​within the numerical activity range, and construct a vertical line perpendicular to these characteristic values. The vertical line divides the historical curves into upper and lower curve segments, with the upper curve segment located above the vertical line and the lower curve segment located below the vertical line. By changing the specific values ​​of the characteristic values, the vertical line is moved up and down. When the vertical line moves, record the sum of the areas of the upper curve segment and the vertical line, as well as the sum of the areas of the lower curve segment and the vertical line. Stop moving the vertical line when the sum of the areas of the upper and lower regions is equal, and define this vertical line as the standard vertical line.

[0018] S33. Based on the calibrated standard vertical line, move this standard vertical line up and down by X1 characteristic values ​​respectively to lock a set of standard ranges, where X1 is a preset value. Using the same method as in step S32 to confirm the standard vertical line from the historical curves, confirm the standard vertical line about this characteristic change curve, and identify whether this standard vertical line belongs to the standard range:

[0019] If the standard vertical line is below the standard range, it indicates that the project is in progress abnormal, and an abnormal signal will be generated and displayed directly.

[0020] If the standard vertical line falls within the standard range, it means that the progress of the corresponding project within the current associated period is normal and no action is required.

[0021] If the standard vertical line is above the standard range, then proceed with the progress trend analysis:

[0022] S331. Determine the comprehensive characteristic Z1 of the terminal point, then determine the comprehensive characteristic Z2 of the point before the terminal point, and use Z1-Z2=Bh to obtain the current change value Bh;

[0023] S332. Identify the upward-trending curve segments from historical curves, and confirm the change in endpoint values ​​H from the identified curve segments. p Where p represents different partial curve segments, and H p =Comprehensive characteristics of the end points of a partial curve segment - Comprehensive characteristics of the initial points of a partial curve segment, from several variation values ​​H p In the middle, select the maximum value H p max;

[0024] S333, If Bh > H p If Bh ≤ H, then the project's progress trend is abnormally high, and an abnormally high signal will be generated and displayed. p max×α represents the progress improvement of the corresponding project within the current associated period, and a progress improvement signal is generated and displayed.

[0025] This invention provides a data processing method for Git repository management. Compared with existing technologies, it has the following advantages:

[0026] This invention monitors and confirms the code entry data of each branch item within each project, and then, based on the confirmed association features of the corresponding branch item, locks the comprehensive features belonging to the corresponding project, thereby reflecting the association progress of the corresponding project. By using this feature to determine and reflect the corresponding association progress, the progress monitoring effect of the corresponding project can be effectively achieved, making it convenient for relevant operators to review.

[0027] Subsequently, based on the comprehensive characteristics of the project determined at the current moment, we will identify whether there are any anomalies in the project's progress. The specific anomaly identification criteria are based on the data characteristics generated by the project in the past cycle, so as to quickly and effectively identify abnormal progress. Based on the identified abnormal progress, we will display the signals for external relevant personnel to view, so as to take timely countermeasures and ensure that each different project can complete its relevant work within a controllable schedule. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0029] Figure 2 This is a schematic diagram of the process for anomaly detection based on associated vertical lines according to the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] First Embodiment

[0032] Please see Figure 1 This application provides a data processing method in Git repository management, including the following steps:

[0033] Step 1: Define the associated monitoring period. Confirm the code data packets that need to be uploaded to the Git repository within this associated period. Based on the format standard associated with the corresponding branch of the project, process the code data packets to obtain the input data packets. The associated period is a preset period, which is determined in advance by relevant operators based on experience. Specifically, the Git repository is used to manage the input of real-time generated code. Different projects are set up in this repository. Each project has multiple different branches. Each branch needs to input the associated code data to promote the normal implementation of the entire project. At the same time, based on the code input progress of different branches of the corresponding project, the overall completion progress of the corresponding project can be confirmed and the signal can be displayed to facilitate management.

[0034] The specific method for formatting the code data package is as follows:

[0035] S11. Based on the relevant tags of this code data packet, determine the branch item to which this code data packet belongs. The relevant tags are prepared in advance by the operator. Then determine the format standard associated with the branch item. The format standard is also set in advance by the operator. Different branch items correspond to different format standards. The format standard is the spacing between adjacent codes.

[0036] S12. Areas within the code data packet that do not contain code symbols are marked as empty areas. Based on the determined format standard, these empty areas are adjusted to ensure that the internal layout of the code data packet is consistent with the format of the code associated with the branch item. The format standard is the spacing between adjacent codes. Since different branch items have different format requirements, some only require a two-character spacing, while others require blank lines. Therefore, the internal layout of the code data packet is adjusted according to the determined format standard to ensure that the code data entered by the corresponding branch item has a consistent format.

[0037] Step 2: Based on the multiple data entry packets confirmed within the associated cycle, and based on the number and capacity of data entry packets for the same branch item, determine the entry characteristics of the corresponding branch item. Then, based on the entry characteristics of multiple branch items within the corresponding project, determine the comprehensive characteristics of the corresponding project. Finally, based on the comprehensive characteristics of the corresponding project confirmed in previous associated cycles and the comprehensive characteristics determined this time, generate a characteristic change curve for the corresponding project (its characteristic change can also be understood as the progress change within each cycle; the larger the characteristic value, the faster the progress in this cycle; the smaller the characteristic value, the slower the progress in this cycle). The specific sub-steps for generating the characteristic change curve for the corresponding project are as follows:

[0038] S21. For a certain branch item within the association period, confirm the number of several data entry packets (including one) and label them as G. i-k Where i represents different projects, k represents different branch items, and then confirm the total amount of data Z entered from several data entry packages. i-k The total amount of data entered is the sum of the data capacities of several data entry packets, using T... i-k =G i-k ×C1+Z i-k ×C2 confirms the entry characteristics T of the corresponding branch item. i-k C1 and C2 are preset fixed coefficient factors, whose specific values ​​are determined by the operator based on experience, and the same method is used to determine the input characteristics of other branch items.

[0039] S22, Based on the different input characteristics T of different branches within the same project i-k The maximum and minimum values ​​are used to determine a range of values. Values ​​are selected within this range and labeled as the selected value Z. Values ​​greater than the selected value Z are entered using the input feature T. i-k Calibrated as TD i-k Input feature T that is less than the selected value i-k Calibrated as TX i-k , using TD i-k -Z=CD i-k Confirm TDi-k The difference between Z and Z is denoted as the elevation difference, using Z-TX. i-k =CX i-k Confirm Z and TX i-k The difference between them is marked as the low difference;

[0040] When a certain selected value Z satisfies: the sum of elevation differences = the sum of elevation differences, the sum of elevation differences is obtained by summing multiple elevation differences, and the sum of elevation differences is obtained by summing multiple elevation differences, this selected value Z is labeled as the comprehensive characteristic of this project;

[0041] S23. Based on the comprehensive characteristics confirmed in this project during this associated period, identify the comprehensive characteristics confirmed in the past 30 associated periods from historical completion data. Based on the chronological order, generate a characteristic change curve (or progress change curve) for this project. The horizontal axis of this curve is the time line, and its vertical axis is the corresponding characteristic parameter.

[0042] Specifically, since a corresponding association period has been defined, when the current association period ends, the next association period will be generated. If there are data packets that have not been fully entered within the association period, the data capacity entered will be used as the calculation basis (that is, if 30M of code data is entered out of 50M, then the 30M will be used for the specific calculation of the sum of the subsequent data capacities). When the corresponding branch item enters data, there are corresponding numbers of entries and entry capacity, so the entry characteristics of the corresponding branch item can be locked. In order to identify and confirm the total feature progress data of the corresponding project, it is necessary to lock the features from the entry features of several branch items to select and confirm the comprehensive features of the corresponding project.

[0043] Second Embodiment

[0044] In the specific implementation process, compared with the above embodiments, this embodiment mainly focuses on the numerical analysis process of the characteristic change curve to assess whether there is any progress abnormality in the corresponding project and to issue timely warnings.

[0045] Step 3: Based on the confirmed characteristic change curve of the corresponding project, perform characteristic analysis on the terminal point of this characteristic change curve. Based on the change range of this characteristic change curve, determine the corresponding change range. Then, confirm whether the numerical characteristics generated by this terminal point are abnormal and display the signal. The specific sub-steps for confirming whether the numerical characteristics generated by this terminal point are abnormal are as follows:

[0046] S31. Based on the end point of the feature change curve, confirm the line segment between the point before the end point (that is, the point corresponding to the 30th comprehensive feature, whose end point is the 31st point appearing in this curve) and the initial point of the feature change curve, and mark it as the past historical curve.

[0047] S32. Based on the calibrated historical curves, determine the lowest and highest points of the historical curves, and define the range between the lowest and highest points as the numerical activity range. Within this range, randomly select a set of characteristic values ​​and construct a perpendicular line to these characteristic values. This perpendicular line divides the historical curves into upper and lower curve segments, with the upper segment above the perpendicular line and the lower segment below it. By changing the specific values ​​of the characteristic values, the perpendicular line is moved up and down. During this movement, the sum of the areas of the upper curve segment and the perpendicular line is recorded. The area of ​​the lower curve segment and the associated vertical line is calculated, and the associated vertical line is moved until the sum of the areas of the upper and lower regions is equal. This associated vertical line is then marked as the standard vertical line. Specifically, the method for confirming the sum of the corresponding area is as follows: After the associated vertical line is confirmed, based on the two previous and previous endpoints of the historical curve, two vertical lines are constructed between the two previous and previous endpoints and the associated vertical line. This will confirm the corresponding upper and lower regions. After the upper and lower regions are confirmed, the total area of ​​the upper and lower regions can be confirmed based on the up and down movement of the associated vertical line. Therefore, when the associated vertical line moves, it can effectively make the total area of ​​the upper and lower regions equal.

[0048] S33. Based on the calibrated standard vertical line, move this standard vertical line up and down by X1 characteristic values ​​respectively to lock a set of standard ranges, where X1 is a preset value, the specific value of which is determined by the operator based on experience. Using the method in step S32 of confirming that the standard vertical line is the same as that found in historical curves, confirm the standard vertical line for this characteristic change curve, and combine it with... Figure 2 To determine whether this standard vertical line falls within the standard range:

[0049] If the standard vertical line falls within the standard range, it means that the progress of the corresponding project within the current associated period is normal and no action is required.

[0050] If the standard vertical line is below the standard range, it indicates that the project is in progress abnormal, and an abnormal signal will be generated and displayed directly for external personnel to view. Based on the generated abnormal signal, external personnel can comprehensively manage the actual progress of such projects to achieve better project progress control.

[0051] If the standard vertical line is above the standard range, then proceed with the progress trend analysis:

[0052] S331. Determine the comprehensive feature Z1 of the terminal point, and then determine the comprehensive feature Z2 of the point before the terminal point (that is, the point corresponding to the 30th comprehensive feature, whose terminal point is the 31st point appearing in this curve). Use Z1-Z2=Bh to obtain the current change value Bh (because the standard vertical line is above the standard range, the comprehensive feature confirmed by the subsequent terminal point is definitely higher than the comprehensive feature of the previous point).

[0053] S332. Identify the upward-trending curve segments from historical curves, and confirm the change in endpoint values ​​H from the identified curve segments. p Where p represents different partial curve segments, and H p =Comprehensive characteristics of the end points of a partial curve segment - Comprehensive characteristics of the initial points of a partial curve segment, from several variation values ​​H p In the middle, select the maximum value H p max;

[0054] S333, If Bh > H p max×α, where α is a preset value determined by the operator based on experience, generally taken as 2.5, which represents an abnormally high change in the progress trend of this project, and generates an abnormally high signal for display, which is then viewed by external personnel.

[0055] If Bh≤H p max×α represents the progress improvement of the corresponding project within the current associated period, and a progress improvement signal is generated and displayed for external personnel to view.

[0056] Third Embodiment

[0057] In its specific implementation, this embodiment includes all the implementation processes of the two sets of embodiments described above.

[0058] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0059] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A data processing method in Git repository management, characterized by, Comprise the following steps: Step one, limit the association cycle of monitoring, confirm the code data package in the association cycle which needs to be uploaded to the Git repository, and process the code data package based on the format standard associated with the corresponding project corresponding branch item to obtain the entry data package; Step two, based on the multiple entry data packages confirmed in the association cycle, based on the number and capacity of the branch item entry data package, determine the entry characteristics of the corresponding branch item, and based on the entry characteristics of the multiple branch items in the corresponding project, determine the comprehensive characteristics of the corresponding project, and based on the comprehensive characteristics of the corresponding project confirmed in the past association cycle and the comprehensive characteristics determined this time, generate the feature change curve belonging to the corresponding project, the specific sub-steps are: S21, confirming a number of the several entered data packets of the certain branch item in the correlation period and marking the number as G i-k , wherein i represents different items, k represents different branch items, and the total amount Z of the entered data of the several entered data packets is further confirmed i-k , the total amount of the entered data of which is the sum of the data capacities of the several entered data packets, and T i-k i-k =G i-k ×C1+Z i-k ×C2 is confirmed, wherein C1 and C2 are preset fixed coefficient factors, and the entered characteristics of other branch items are determined in the same manner;​ S22, again based on different entry features T of different sub-branch items in the same project i-k The maximum and minimum values are confirmed, a range of numerical values is determined within which the numerical values are selected, and the selected numerical values are marked as selected values Z. The entry features T greater than the selected values Z are marked as TD i-k i-k The entry features T less than the selected values are marked as TX i-k i-k TD i-k -Z=CD i-k The difference between TD i-k and Z is confirmed and marked as a height difference, and Z-TX i-k =CX i-k The difference between Z and TX i-k is confirmed and marked as a low difference.​​ When a selected value Z satisfies: the total difference sum = the total difference sum, the total difference sum is obtained by summing a plurality of high differences, and the total difference sum is obtained by summing a plurality of low differences, the selected value Z is determined as the comprehensive characteristics of the project; S23, based on the comprehensive characteristics of the project confirmed in the association cycle, identify the comprehensive characteristics of the project confirmed in the past 30 groups of association cycles from the historical completion data, and generate the feature change curve belonging to the project according to the relationship of time arrangement; Step three, based on the feature change curve of the corresponding project, analyze the characteristics of the end point of the feature change curve, determine the corresponding change range based on the change range of the feature change curve, and confirm whether the numerical characteristics generated by the end point are abnormal and perform signal display.

2. The data processing method in the Git repository management according to claim 1, wherein, In step one, the specific way of processing the code data package is: S11, based on the relevant mark of the code data package, determine the branch item to which the code data package belongs, and then determine the format standard associated with the branch item, different branch items correspond to different format standards, and the format standard is the interval space between adjacent codes; S12, mark the relevant area in the code data package that does not exist code symbol as empty area, adjust the empty area based on the determined format standard, so that the internal arrangement format of the code data package is consistent with the format of the code associated with the branch item, and the format standard is the interval space between adjacent codes.

3. The data processing method in the Git repository management according to claim 1, wherein, The association cycle in step one is a preset period.

4. The data processing method in the Git repository management according to claim 1, characterized in that, In step three, the specific sub-steps for confirming whether the numerical characteristics generated by the end point are abnormal are: S31, based on the end point of the feature change curve, confirm the line segment between the point before the end point and the initial point of the feature change curve, and mark it as the past history curve; S32, based on the calibrated past history curve, determine the lowest point and the highest point of the past history curve, and mark the range between the lowest point and the highest point as a numerical activity range, randomly select a group of characteristic values in the numerical activity range, and construct an associated vertical line perpendicular to the characteristic values, and the associated vertical line divides the past history curve into upper and lower curve segments, the upper curve segment is above the associated vertical line, and the lower curve segment is below the associated vertical line, by changing the specific value of the characteristic value, the associated vertical line moves up and down, when the associated vertical line moves, record the area sum of the upper curve segment and the associated vertical line and the area sum of the lower curve segment and the associated vertical line, stop when the area sum of the upper and lower regions is equal, and mark the associated vertical line as a standard vertical line; S33, based on the calibrated standard vertical line, move the standard vertical line up and down by X1 characteristic value to lock a group of standard ranges, wherein X1 is a preset value, confirm the standard vertical line of the characteristic change curve in the same way as step S32 confirms the standard vertical line from the past history curve, and identify whether the standard vertical line belongs to the standard range: If the standard vertical line is below the standard range, it represents that the progress of the project is abnormal, and an abnormal signal is generated to directly display.

5. The data processing method in the Git repository management according to claim 4, wherein, The step S33 further comprises: If the standard vertical line belongs to the standard range, it represents that the progress of the corresponding project in the current associated period is normal, and no further processing is required.

6. The data processing method in the Git repository management according to claim 4, wherein, The step S33 further comprises: If the standard vertical line is above the standard range, proceed to analyze the progress trend: S331, determine the comprehensive characteristic Z1 of the end point, and then determine the comprehensive characteristic Z2 of the point before the end point, and obtain the current change value Bh by using Z1-Z2=Bh; S332, identifying a part curve segment from the past history curve that goes upward, confirming a change value H of an end point value from the identified part curve segment p where p represents different part curve segments, where H p = the comprehensive feature of the end point of the part curve segment - the comprehensive feature of the initial point of the part curve segment, from several change values H p , selecting the maximum value H p max; S333, if Bh>H p max x a, where a is a preset value, it represents that the progress trend of the item is abnormally high, and an abnormally high signal is generated and displayed.

7. The data processing method in the Git repository management according to claim 6, wherein, In the step S333, if Bh≤H p max x a, it represents the progress promotion of the corresponding item in the current association period, and a progress promotion signal is generated for display.

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