Data monitoring system and method based on low-code platform

Abstract

The invention relates to the technical field of data monitoring, in particular to a data monitoring system and method based on a low-code platform, and the system comprises a visual design module, a code editing module, an error reporting module, a data collection module, a sensitive data processing module and an exception handling module. According to the method, the exception tendency category of the to-be-developed project is determined based on the code calling characterization value, whether the core thread count is corrected or not is determined based on the exception tendency category, and sensitive data in each code is identified; the sensitive data is processed based on the sensitive data distribution characterization value, the function configuration parameters are corrected based on the grammar error report change value, the computing power resources are distributed according to the actual situation of the project, and the data management efficiency of the low-code platform is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data monitoring, in particular to a data monitoring system and method based on a low-code platform. BACKGROUND

[0002] With the deepening of enterprise digital transformation, the complexity of business processes and the diversity of data have increased dramatically, and the demand for rapid development and deployment of applications to respond to market changes is increasingly urgent. Low-code development platforms have emerged, allowing developers and ordinary business personnel to quickly build applications through "drag and drop" and configuration methods through visual graphical interfaces and pre-built components, significantly reducing the programming threshold and application development cycle.

[0003] Among various applications of low-code platforms, data monitoring systems are a key link for real-time monitoring, analysis, and early warning of massive data generated by business systems, Internet of Things devices, etc. However, existing low-code platforms have low generation efficiency due to insufficient user professional skills when building such systems.

[0004] Chinese Patent Publication No. CN120067080A discloses a data acquisition method and system based on a low-code development platform, which includes automatically identifying and adapting to the connection methods of various data sources using predefined connectors, automatically inferring the relationships between different data sources, performing data mapping and conversion, automatically defining data acquisition logic using predefined rules, including filtering conditions and sorting rules, automatically executing data acquisition operations according to plans, and triggering data acquisition operations immediately when data sources change, handling encryption and access control for sensitive data, automatically testing data after acquisition, verifying whether the data acquisition process is working properly, and automatically recording monitoring data, automatically handling exceptions and taking measures during data acquisition. It can be seen that the above technical solution has the following problems: it does not consider allocating computing resources according to the actual situation of the project, affecting the data management efficiency of the low-code platform. SUMMARY

[0005] Therefore, the present application provides a data monitoring system and method based on a low-code platform to overcome the problem in the prior art that the computing resources are not allocated according to the actual situation of the project, affecting the data management efficiency of the low-code platform.

[0006] In one aspect, the present application provides a data monitoring system based on a low-code platform, comprising: a visual design module for configuring the functions of a project to be developed; a code editing module connected to the visual design module for generating corresponding code blocks based on the functions configured by the visual design module; an error reporting module connected with the code editing module to implement syntax analysis error reporting and syntax analysis error reporting; a data collection module connected with the visual design module and the code editing module to determine the abnormal tendency category of the to-be-developed project based on code call representation values, to determine whether to modify the core thread number based on the abnormal tendency category, and to identify sensitive data in each code; a sensitive data processing module connected with the code editing module and the data collection module to process sensitive data based on sensitive data distribution representation values, including adding a function call block or determining whether to modify the function configuration parameter based on the impact data filtering rate; an exception handling module connected with the sensitive data processing module and the error reporting module to modify the function configuration parameter based on the syntax error change value, including modifying the static analysis period for syntax analysis error reporting based on the syntax error change value, or modifying the update frequency of the visual design module based on the impact data filtering rate.

[0007] Further, the data collection module is used to periodically determine the abnormal tendency category of the to-be-developed project based on code call representation values, including: to determine the code call representation value based on the configuration byte number and the added byte number; to divide the to-be-developed project into a strong abnormal tendency category if the code call representation value is greater than a preset code call representation value.

[0008] Further, the data collection module is used to divide the to-be-developed project into a weak abnormal tendency category if the code call representation value is less than or equal to a preset code call representation value.

[0009] Further, the data collection module is used to determine whether to identify sensitive data in each code, modify the core thread number based on the abnormal tendency category, including: to identify sensitive data in each code and modify the core thread number if the to-be-developed project is in the strong abnormal tendency category.

[0010] Further, the sensitive data processing module is used to process sensitive data based on sensitive data distribution representation values, including: to determine consecutive sensitive data in a preset analysis period as a single sensitive block; to determine the sensitive data distribution representation value based on the average value of the byte number of each sensitive block and the added byte number; to determine whether to modify the function configuration parameter based on the impact data filtering rate if the sensitive data distribution representation value is less than or equal to a preset sensitive distribution value; determining an impact data filtering rate based on the total number of bytes of each string in the sensitive data and the total number of bytes of the sensitive data in a preset analysis period; correcting the functional configuration parameter based on the syntax error change value on the condition that the impact data filtering rate is less than or equal to a preset impact data filtering rate.

[0011] Further, the sensitive data processing module is configured to add a functional call block on the condition that the sensitive data distribution representation value is greater than a preset sensitive distribution value. The sensitive data processing module is configured to control the visual design module to continue running with the current running parameter on the condition that the impact data filtering rate is greater than a preset impact data filtering rate.

[0012] Further, the abnormality processing module is configured to correct the functional configuration parameter based on the syntax error change value, including: drawing an error quantity time domain curve based on the error quantity of a plurality of time nodes in a preset analysis period; acquiring each wave crest in the error quantity time domain curve to determine a valid wave crest greater than the average value of the error quantity; determining the number of valid wave crests as the syntax error change value; storing the code in the preset analysis period to a change database on the condition that the syntax error change value is less than or equal to a preset syntax error change value, and correcting the update frequency of the visual design module based on the impact data filtering rate; The increase amplitude of the update frequency is negatively correlated with the impact data filtering rate.

[0013] Further, the abnormality processing module is configured to correct the static analysis period for syntax analysis error on the condition that the syntax error change value is greater than a preset syntax error change value. The decrease amplitude of the static analysis period is positively correlated with the syntax error change value.

[0014] Further, the data collection module is configured to control the visual design module to continue running with the current running parameter on the condition that the to-be-developed project is a weak abnormality tendency category.

[0015] In another aspect, the present application also provides a data monitoring method using the above-mentioned low-code platform-based data monitoring system, including: determining a code call representation value based on the periodically acquired code of the to-be-developed project; determining the abnormality tendency category of the to-be-developed project based on the code call representation value; determining whether to identify the sensitive data in each code and correct the core thread number based on the abnormality tendency category; After the identification of sensitive data is completed, the sensitive data is processed based on the sensitive data distribution representation value, including adding a new function call block or determining whether to modify the function configuration parameter based on the influence data filtering rate; The function configuration parameter is modified based on the syntax error change value, including modifying the static analysis period for syntax analysis error based on the syntax error change value, or modifying the update frequency of the visual design module for configuring the function of the to-be-developed project based on the influence data filtering rate.

[0016] Compared with the prior art, the beneficial effects of the present application are that the data collection module periodically determines the abnormal tendency category of the to-be-developed project based on the code call representation value, and determines that the code call representation value configuration byte number determined by the configuration byte number and the new byte number represents the stable and reliable code generated by the visual design module configuration. The new byte number represents the sum of the user-defined code and the code configured by the visual design module, and the code call representation value quantifies the degree of dependence of the project on the custom code. When the code call representation value is greater than the preset code call representation value, it represents that the proportion of the code written manually by the user is larger, the uncertainty and complexity are higher, the custom logic is more, and the potential error risk and performance uncertainty are higher. The to-be-developed project in this case is divided into a strong abnormal tendency category.

[0017] Further, for the project in the strong abnormal tendency category, the code is more complex, and more real-time monitoring and computing resources are required during running, including more frequent syntax checking and logic analysis. Increasing the core thread number in this case provides computing power for high-complexity projects, reduces monitoring delay and lag, and further improves the data management efficiency of the low-code platform.

[0018] Further, the larger the code call representation value, the higher the project abnormal risk, the more monitoring and computing resources required, and the greater the increase in the core thread number. By dynamically adjusting resource allocation, simple projects and complex projects are intelligently distinguished, and the data management efficiency of the low-code platform is further improved.

[0019] Further, the sensitive data distribution representation value measures the concentration of the user-entered custom code. When the sensitive data distribution representation value is greater than the preset sensitive distribution value, the user tends to add a large block of continuous and complete custom code, and in this case, the platform lacks general function modules for the user. In this case, the repeated code is clustered and integrated into a new function call block to improve the configuration of the function. When the sensitive data distribution representation value is less than or equal to the preset sensitive distribution value, most of the user's modifications are scattered and small in scope, and in this case, the user adjusts the interface text or fine-tunes the logic. At this time, it is determined whether to modify the function configuration parameter based on the impact data filtering rate. By generating reusable function call blocks, the probability of developers repeatedly writing the same code is reduced, the low-code platform generates function call blocks that are adapted to the user, and precise data support is provided for platform function iteration, further improving the data management efficiency of the low-code platform.

[0020] Further, it is determined whether to modify the function configuration parameter based on the impact data filtering rate, which reflects the nature of the user's modifications. When the impact data filtering rate is greater than the preset impact data filtering rate, the modification is mainly a string, which belongs to user customization and does not reflect platform function defects, so the function configuration does not need to be modified. When the impact data filtering rate is less than or equal to the preset impact data filtering rate, the code logic modification is involved in this case. The user modifies the code to compensate for the lack of existing platform configuration functions. In this case, the function configuration parameter is modified based on the syntax error change value, which improves development efficiency and further improves the data management efficiency of the low-code platform.

[0021] Further, the function configuration parameter is modified based on the syntax error change value, which reflects the fluctuation of the error. When the syntax error change value is less than or equal to the preset syntax error change value, there are fewer error peaks, and in this case, the user completes the deployment of the project after supplementing part of the code due to the functional defects of the project. In this case, the code is stored and the update frequency of the visual design module is increased. When the syntax error change value is greater than the preset syntax error change value, the user frequently changes to eliminate errors. In this case, the static analysis period is reduced to give error results faster to help the user iterate quickly, further improving the data management efficiency of the low-code platform. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 A module block diagram of the data monitoring system based on the low-code platform of the embodiment of the application; Figure 2 A step flowchart of the data monitoring method based on the low-code platform of the embodiment of the application; Figure 3 A logic decision diagram for the data collection module of the embodiment of the application to determine the abnormal tendency category of the to-be-developed project based on the code call representation value; Figure 4 The logic decision diagram for the sensitive data processing module of the embodiment of the present application to process sensitive data based on sensitive data distribution representation values. DETAILED DESCRIPTION

[0023] In order to make the objects and advantages of the present application clearer, the present application will be further described below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0024] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood by those skilled in the art that the embodiments are only used to explain the technical principles of the present application and are not used to limit the protection scope of the present application.

[0025] It should be noted that, in the description of the present application, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or positional relationship shown in the drawings, which is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0026] In addition, it should also be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood in a broad sense, for example, it can be fixed connection, or detachable connection, or integrally connected; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0027] Please refer to Figure 1 Fig. 1 is a module block diagram of a data monitoring system based on a low-code platform according to an embodiment of the present application. The system described in the present application comprises: a visual design module configured to configure the functions of the project to be developed; a code editing module connected to the visual design module and configured to generate corresponding code blocks based on the functions configured by the visual design module; an error reporting module connected to the code editing module and configured to implement syntax analysis error reporting and syntax analysis error reporting; a data collection module connected to the visual design module and the code editing module respectively, configured to determine the abnormal tendency category of the project to be developed based on the code calling representation value, and to determine whether to modify the core thread number and identify the sensitive data in each code based on the abnormal tendency category; The sensitive data processing module is connected with the code editing module and the data collection module respectively, and is used for processing sensitive data based on a sensitive data distribution representation value, including adding a function call block or determining whether to modify a function configuration parameter based on an influence data filtering rate; The abnormality processing module is connected with the sensitive data processing module and the error reporting module respectively, and is used for modifying a function configuration parameter based on a syntax error change value, including modifying a static analysis period for syntax analysis error reporting based on the syntax error change value, or modifying an update frequency of a visual design module for configuring a function of the to-be-developed project based on the influence data filtering rate.

[0028] Please refer to Figure 2 As shown in the figure, it is a step flow chart of the data monitoring method based on a low-code platform according to an embodiment of the present application. The method described in the present application comprises: S1, determining a code call representation value based on periodically acquired codes of a to-be-developed project; S2, determining an abnormality tendency category of the to-be-developed project based on the code call representation value; S3, determining whether to identify sensitive data in each code and modify a core thread number based on the abnormality tendency category; After the identification of the sensitive data is completed, the sensitive data is processed based on a sensitive data distribution representation value, including adding a function call block or determining whether to modify a function configuration parameter based on an influence data filtering rate; The function configuration parameter is modified based on a syntax error change value, including modifying a static analysis period for syntax analysis error reporting based on the syntax error change value, or modifying an update frequency of a visual design module for configuring a function of the to-be-developed project based on the influence data filtering rate.

[0029] Specifically, the code block generated by the code editing module can be added, deleted or modified by the user; Specifically, the error reporting module is used to implement syntax analysis error reporting and periodic code specification checking according to a static analysis period, including: Syntax checking is triggered each time a key is pressed, and syntax analysis error reporting is triggered when the code structure does not conform to the language specification; When the error reporting module completes a single static analysis period, a dead loop structure is identified, and a logical error is triggered after the dead loop structure is identified to analyze the code logic.

[0030] Please refer to Figure 3 As shown in the figure, it is a logic decision diagram for the data collection module to determine an abnormality tendency category of a to-be-developed project based on a code call representation value according to an embodiment of the present application. The data collection module described in the present application is used to periodically determine an abnormality tendency category of a to-be-developed project based on a code call representation value, including: determining the number of bytes of the configuration code of the visual design module in the identified preset analysis period as the configuration byte number; determining the total number of bytes of the newly added code in the code editing module in the identified preset analysis period as the added byte number; calculating the ratio of the configuration byte number and the added byte number to obtain the configuration proportion; calculating the difference between 1 and the configuration proportion to obtain the code calling representation value; if the code calling representation value is less than or equal to the preset code calling representation value, the to-be-developed project is divided into a weak abnormal tendency category; if the code calling representation value is greater than the preset code calling representation value, the to-be-developed project is divided into a strong abnormal tendency category.

[0031] Specifically, the preset code calling representation value is selected in the interval [0.3, 0.4], and a person skilled in the art can select the preset code calling representation value. The preset code calling representation value can be determined by analyzing historical project data. The code calling representation values and abnormal occurrence situations of multiple projects are collected, and the critical value at which the abnormal occurrence situation significantly increases is determined as the code calling representation value. In the present embodiment, preferably, the preset code calling representation value is 0.4.

[0032] Specifically, the data collection module is configured to determine whether to identify sensitive data in each code and correct the core number of threads based on the abnormal tendency category, comprising: if the to-be-developed project is in the weak abnormal tendency category, the visual design module is controlled to continue running with the current running parameters; if the to-be-developed project is in the strong abnormal tendency category, sensitive data in each code is identified and the core number of threads is corrected.

[0033] Specifically, the data collection module periodically determines the abnormal tendency category of the to-be-developed project based on the code calling representation value. The configuration byte number and the added byte number are used to determine the code calling representation value. The configuration byte number represents the stable and reliable code generated by the visual design module configuration. The added byte number represents the sum of the user-defined code and the code configured by the visual design module. The code calling representation value quantifies the degree of dependence of the project on the user-defined code. When the code calling representation value is greater than the preset code calling representation value, it represents that the proportion of the code written manually by the user, which has higher uncertainty and complexity, is large, and the more user-defined logic, the higher the potential error risk and performance uncertainty. The to-be-developed project in this case is divided into a strong abnormal tendency category.

[0034] Specifically, for the project of strong abnormal tendency category, the code is more complex, and more real-time monitoring and computing resources are required during running, including more frequent syntax checking and logic analysis. Increasing the core thread number in this case provides computing power for high complexity projects, while reducing monitoring delay and lag, further improving the data management efficiency of the low-code platform.

[0035] Specifically, the code in the new code other than the configuration code is determined as sensitive data.

[0036] Specifically, the data collection module is used to correct the core thread number based on the code call representation value, wherein, The increase range of the core thread number is positively correlated with the code call representation value.

[0037] In this embodiment, optionally, The code call representation value is compared with a preset thread correction comparison value; If the code call representation value is less than or equal to the preset thread correction comparison value, the core thread number is corrected to the initial core thread number plus one; If the code call representation value is greater than the preset thread correction comparison value, the core thread number is corrected to the initial core thread number plus two; The preset thread correction comparison value is 0.45.

[0038] Specifically, the larger the code call representation value, the higher the project abnormal risk, the more monitoring and computing resources required, and the larger the increase range of the core thread number. By dynamically adjusting resource allocation, simple and complex projects are intelligently distinguished, further improving the data management efficiency of the low-code platform.

[0039] Please refer to Figure 4 As shown in the figure, it is a logic judgment diagram for the sensitive data processing module of the embodiment of the application to process sensitive data based on the sensitive data distribution representation value. The sensitive data processing module described in the application is used to process sensitive data based on the sensitive data distribution representation value, including: To determine the continuous sensitive data in a preset analysis period as a single sensitive block; To determine the ratio of the average value of the byte number of each sensitive block to the new byte number as the sensitive data distribution representation value; If the sensitive data distribution representation value is less than or equal to the preset sensitive distribution value, whether to correct the function configuration parameter is determined based on the influence data screening rate; If the sensitive data distribution representation value is greater than the preset sensitive distribution value, a new function call block is added.

[0040] Specifically, the preset sensitive distribution value is selected in the interval [0.11, 0.13], and those skilled in the art can select the preset sensitive distribution value by themselves, which can be determined based on historical code analysis. Statistical analysis can be abstracted as the number of bytes of sensitive blocks of reusable modules. It can be understood that the division of the data amount of the code contained in each sensitive block can be implemented to determine whether it can be integrated into a general function. In the embodiment, preferably, the preset sensitive distribution value is 0.11.

[0041] Specifically, the sensitive data distribution representation value measures the concentration of the user's custom code. When the sensitive data distribution representation value is greater than the preset sensitive distribution value, the user tends to add a large number of continuous and complete custom code blocks. In this case, the platform lacks general function modules for the user. In this case, the repeated code is clustered and integrated into a new function call block to improve the configuration of the function. When the sensitive data distribution representation value is less than or equal to the preset sensitive distribution value, the user mostly makes scattered and small-range modifications. In this case, the user adjusts the interface text or fine-tunes the logic. At this time, it is determined whether to modify the function configuration parameter based on the influence data filtering rate. By generating reusable function call blocks, the probability of developers repeatedly writing the same code is reduced, the low-code platform generates function call blocks that adapt to the user, and accurate data support is provided for platform function iteration, further improving the data management efficiency of the low-code platform.

[0042] Specifically, the sensitive data processing module is used to add a function call block, which includes: Obtain each sensitive block in the historical data; Divide each sensitive block into a plurality of sensitive classes; Determine the sensitive class with the largest number of sensitive blocks as a new sensitive class, and the number of sensitive blocks is the total number of each sensitive block in a single sensitive class; Obtain the same code of each sensitive block in the new sensitive class, and integrate the same code into a new function call block.

[0043] Specifically, the new call block can be named according to the preset regulation or modified by the user.

[0044] Specifically, the sensitive data processing module is used to divide each sensitive block into a plurality of sensitive classes, which includes: For a single sensitive block, compare the code of the single sensitive block with the code of each of the remaining sensitive blocks one by one; Determine the ratio of the number of bytes of the same statement in the single sensitive block to the total number of bytes of the single sensitive block as the code similarity of the two sensitive blocks; Divide the remaining sensitive blocks with a code similarity greater than a preset code similarity from the single sensitive block into a single sensitive class; If the sensitive blocks included in the two sensitive classes are the same, any one of the sensitive classes is deleted.

[0045] Specifically, the preset code similarity is selected in the interval [0.89, 0.92], and the person skilled in the art can select and determine the preset code similarity. The greater the preset code similarity, the more accurate the identification of the new function call block. In the present embodiment, the preset code similarity is preferably 0.92.

[0046] Specifically, the sensitive data processing module is used to determine whether to modify the function configuration parameter based on the influence data filtering rate, comprising: Obtain the ratio of the total number of bytes of each string in the sensitive data to the total number of bytes of the sensitive data in the preset analysis period to obtain the influence data filtering rate; If the influence data filtering rate is greater than the preset influence data filtering rate, the visual design module is controlled to continue to run using the current running parameter; If the influence data filtering rate is less than or equal to the preset influence data filtering rate, the function configuration parameter is modified based on the syntax error change value.

[0047] Specifically, the function configuration parameter is determined based on the influence data filtering rate. The influence data filtering rate reflects the nature of user modification. When the influence data filtering rate is greater than the preset influence data filtering rate, the modification is mainly the string, which belongs to user individual customization and does not reflect the platform function defect, so the function configuration does not need to be modified. When the influence data filtering rate is less than or equal to the preset influence data filtering rate, code logic modification is involved in this case. The user modifies the code to compensate for the insufficient platform configuration function, and the function configuration parameter is modified based on the syntax error change value in this case, which improves the development efficiency and further improves the data management efficiency of the low-code platform.

[0048] Specifically, the preset influence data filtering rate is selected in the interval [0.78, 0.85], and the person skilled in the art can select the preset influence data filtering rate. It can be determined by analyzing the code change type: it can be understood that the division of whether the modification involves structural changes can be achieved. In the present embodiment, the preset influence data filtering rate is preferably 0.8.

[0049] Specifically, the abnormality processing module is used to modify the function configuration parameter based on the syntax error change value, comprising: Draw an error quantity time domain curve based on the obtained error quantity of a plurality of time nodes in the preset analysis period; Obtain the wave crest in the error quantity time domain curve, and determine the effective wave crest which is greater than the average value of the error quantity; The number of effective wave crests is determined as the syntax error change value; If the syntax error change value is less than or equal to the preset syntax error change value, the code in the preset analysis period is stored in the change database, and the update frequency of the visual design module is corrected based on the impact data filtering rate; If the syntax error change value is greater than the preset syntax error change value, the static analysis period for syntax analysis error is corrected based on the syntax error change value.

[0050] Specifically, the preset syntax error change value is selected in the interval [3, 4], which can be selected by those skilled in the art. The average value of the number of effective wave peaks in each preset analysis period in normal development can be determined based on the development cycle simulation analysis to determine the preset syntax error change value. In this embodiment, preferably, the preset syntax error change value is 3.

[0051] Specifically, the syntax error change value is used to correct the functional configuration parameter. The syntax error change value reflects the fluctuation of the error. When the syntax error change value is less than or equal to the preset syntax error change value, the error wave peak is less. In this case, the user completes the deployment of the project after supplementing part of the code due to the functional defects of the project. In this case, the code is stored and the update frequency of the visual design module is increased. When the syntax error change value is greater than the preset syntax error change value, it means that the user frequently changes to eliminate the error. In this case, the static analysis period is reduced to give the error result faster, helping the user to iterate quickly, and further improving the data management efficiency of the low-code platform.

[0052] Specifically, those skilled in the art can develop an updated version of the visual design module based on the code data in the change database, which is prior art and will not be described in detail.

[0053] Specifically, the abnormality processing module is used to correct the update frequency of the version of the visual design module based on the impact data filtering rate, wherein, The increase range of the update frequency is negatively correlated with the impact data filtering rate.

[0054] In this embodiment, optionally, The impact data filtering rate is compared with the first filtering rate and the second filtering rate. If the impact data filtering rate is less than or equal to the first filtering rate, the update frequency of the version of the visual design module is adjusted to 1.28 times of the initial update frequency. If the impact data filtering rate is less than or equal to the second filtering rate and greater than the first filtering rate, the update frequency of the version of the visual design module is adjusted to 1.16 times of the initial update frequency. If the impact data filtering rate is greater than the second filtering rate, the update frequency of the version of the visual design module is adjusted to 1.06 times of the initial update frequency. The first filtering rate is 0.4, and the second filtering rate is 0.6.

[0055] Specifically, the abnormality processing module is used to correct a static analysis period for syntax analysis error based on a syntax error change value, wherein, The reduction range of the static analysis period is positively correlated with the syntax error change value.

[0056] In the embodiment, optionally, In the embodiment, optionally, The syntax error change value is compared with a first preset syntax error change value and a second preset syntax error change value. If the syntax error change value is less than or equal to the first preset syntax error change value, the static analysis period for syntax analysis error is adjusted to 0.93 times of the initial static analysis period. If the syntax error change value is less than or equal to the second preset syntax error change value and greater than the first preset syntax error change value, the static analysis period for syntax analysis error is adjusted to 0.88 times of the initial static analysis period. If the syntax error change value is greater than the second preset syntax error change value, the static analysis period for syntax analysis error is adjusted to 0.83 times of the initial static analysis period. The first preset syntax error change value is 5, and the second preset syntax error change value is 7.

[0057] Specifically, the greater the syntax error change value, the more frequent the user changes, and the faster feedback cycle the user needs. Shortening the static analysis period to give error results faster helps the user to iterate quickly.

[0058] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the present application, and the technical solutions after these changes or replacements will fall within the protection scope of the present application.

[0059] The above description is only the preferred embodiments of the present application and is not intended to limit the present application; for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A data monitoring system based on a low-code platform, characterized in that, include: The visual design module is used to configure the functionality of the project to be developed. A code editing module, which is connected to the visual design module, is used to generate corresponding code blocks based on the functions configured in the visual design module; An error reporting module, which is connected to the code editing module, is used to implement syntax analysis error reporting and syntax analysis error reporting; The data collection module, which is connected to the visualization design module and the code editing module respectively, is used to determine the abnormal tendency category of the project to be developed based on the code call characterization value, and to determine whether to correct the core thread count and identify sensitive data in each code based on the abnormal tendency category. A sensitive data processing module, which is connected to the code editing module and the data collection module respectively, is used to process sensitive data based on the sensitive data distribution characterization value, including adding a new function call block or determining whether to modify the function configuration parameters based on the data filtering rate. An exception handling module is connected to the sensitive data processing module and the error reporting module, respectively, and is used to configure parameters based on the syntax error change value correction function. This includes correcting the static analysis cycle for syntax analysis error reporting based on the syntax error change value correction, or correcting the update frequency of the visualization design module based on the impact on the data filtering rate.

2. The data monitoring system based on a low-code platform according to claim 1, characterized in that, The data collection module is used to periodically determine the abnormal tendency category of the project to be developed based on the code call characterization value, including: Used to determine the code call representation value based on the number of configuration bytes and the number of newly added bytes; This is used to classify projects under development into a category with a strong tendency to cause anomalies when the code call characteristic value is greater than the preset code call characteristic value.

3. The data monitoring system based on a low-code platform according to claim 2, characterized in that, The data collection module is used to classify the project to be developed into a weak anomaly tendency category when the code call characterization value is less than or equal to a preset code call characterization value.

4. The data monitoring system based on a low-code platform according to claim 3, characterized in that, The data collection module is used to determine whether to identify sensitive data in each piece of code based on the anomaly tendency category, and to correct the core identification of the number of threads in each piece of code, including: This is used to identify sensitive data in each piece of code and correct the core thread count when the project under development is classified as having a strong tendency to cause anomalies.

5. The data monitoring system based on a low-code platform according to claim 4, characterized in that, The sensitive data processing module is used to process sensitive data based on the sensitive data distribution representation value, including: Used to identify consecutive sensitive data within a preset analysis period as a single sensitive block; Used to determine the sensitive data distribution characterization value based on the average number of bytes in each sensitive block and the number of newly added bytes; Used to determine whether to correct the function configuration parameters based on the data screening rate when the sensitive data distribution characterization value is less than or equal to the preset sensitive distribution value; Used to determine the data filtering rate based on the total number of bytes of each string in the sensitive data and the total number of bytes of the sensitive data within the preset analysis period; This is a configuration parameter for a syntax error change value correction function when the data filtering rate is less than or equal to the preset data filtering rate.

6. The data monitoring system based on a low-code platform according to claim 5, characterized in that, The sensitive data processing module is used to add a function call block when the sensitive data distribution characterization value is greater than the preset sensitive distribution value. The sensitive data processing module is used to control the visualization design module to continue running using the current operating parameters when the data filtering rate is greater than the preset data filtering rate.

7. The data monitoring system based on a low-code platform according to claim 6, characterized in that, The exception handling module is used to configure parameters for the syntax error change value correction function, including: Used to plot the error count time-domain curve based on the number of errors at several time points within a preset analysis period; Used to obtain each peak in the error count time-domain curve, and to determine the valid peaks by identifying peaks that are greater than the average number of errors; Used to determine the number of valid peaks as the syntax error change value; Used to store code within a preset analysis period to the change database when the syntax error change value is less than or equal to the preset syntax error change value, and to adjust the update frequency of the visualization design module based on the data filtering rate. The increase in update frequency is negatively correlated with the impact on data screening rate.

8. The data monitoring system based on a low-code platform according to claim 7, characterized in that, The exception handling module is used to adjust the static analysis cycle of syntax analysis errors based on the syntax error change value when the syntax error change value is greater than the preset syntax error change value. The reduction in static analysis cycle is positively correlated with the change in syntax error rate.

9. The data monitoring system based on a low-code platform according to claim 4, characterized in that, The data collection module is used to control the visualization design module to continue running using the current operating parameters when the project to be developed is in a weak anomaly tendency category.

10. A data monitoring method using the data monitoring system based on a low-code platform as described in any one of claims 1-9, characterized in that, The code call representation value is determined based on the code of the project to be developed, which is obtained periodically. Determine the anomaly tendency category of the project to be developed based on code call characterization values; Based on the abnormal tendency category, determine whether to identify sensitive data in each piece of code and correct the core thread count; After identifying sensitive data, the sensitive data is processed based on the distribution characteristics of the sensitive data, including adding new function call blocks or determining whether to modify function configuration parameters based on the data filtering rate. Configuration parameters for the syntax error change value correction function include the static analysis cycle used for syntax analysis error correction based on syntax error change value correction, or the update frequency of the visual design module used to configure the function of the project to be developed based on the impact of data screening rate correction.

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