Real-time conflict-free application system full-link generation method and related system

Abstract

The invention discloses a real-time conflict-free application system full-link generation method and system, electronic equipment and a storage medium, and relates to the technical field of application development, and the method comprises the steps: capturing operation information of a target object in an application system, and forming an operation sequence according to the operation information; analyzing the operation sequence, and determining a frequent operation sequence and an abnormal operation sequence; identifying defect points according to the frequent operation sequence and the abnormal operation sequence; calling an optimization rule base according to the defect points, and generating optimization suggestions; and pushing the optimization suggestion to a configuration interface, and when the target object confirms the optimization suggestion, optimizing the configuration of the application system according to the optimization suggestion. According to the method, the defects of the application system can be optimized in time, and the defect identification efficiency and accuracy can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of application development, and in particular to a real-time conflict-free application system full-link generation method and system, electronic equipment and storage medium. BACKGROUND

[0002] In the field of application development, existing application system generation tools often use static configuration mode, lack of dynamic perception of user's actual operation behavior, resulting in many defects in the generated wizard. Users frequently encounter field modification, process lag and other problems in the use process, but it is difficult to get timely optimization. Moreover, the traditional wizard optimization relies on manual feedback and experience judgment, which has lag and subjectivity, seriously affecting the defect identification efficiency and accuracy. Therefore, how to solve the above technical defects has become a technical problem to be solved by the technical personnel in the field. SUMMARY

[0003] The purpose of the present application is to provide a real-time conflict-free application system full-link generation method, system, electronic equipment and storage medium, which can timely optimize the defects existing in the application system, and can improve the defect identification efficiency and accuracy.

[0004] To solve the above technical problems, the present application provides a real-time conflict-free application system full-link generation method, comprising:

[0005] Capture the operation information of the target object in the application system, and form an operation sequence according to the operation information;

[0006] Analyze the operation sequence to determine frequent operation sequences and abnormal operation sequences;

[0007] According to the frequent operation sequence and the abnormal operation sequence, identify defect points;

[0008] According to the defect points, call the optimization rule library to generate optimization suggestions;

[0009] Push the optimization suggestions to the configuration interface, and when the target object confirms the optimization suggestions, optimize the configuration of the application system according to the optimization suggestions.

[0010] In some embodiments, analyzing the operation sequence to determine frequent operation sequences and abnormal operation sequences comprises:

[0011] Calculate the support and confidence of the operation sequence; the support is used to measure the frequency of the operation sequence; the confidence is used to measure the driving probability of the previous operation on the subsequent operation in the operation sequence;

[0012] According to the support and confidence, filter out frequent operation sequences and abnormal operation sequences.

[0013] In some embodiments, the filtering of the frequent operation sequence and the abnormal operation sequence according to the support degree and the confidence degree comprises:

[0014] If the support degree is greater than a first preset threshold and the confidence degree is greater than a second preset threshold, the operation sequence is a frequent operation sequence.

[0015] If the support degree is less than or equal to a third preset threshold and the confidence degree is less than or equal to a fourth preset threshold, the operation sequence is an abnormal operation sequence.

[0016] In some embodiments, the generating of the optimization suggestion according to the defect point and the optimization rule library comprises:

[0017] determining a defect severity of the defect point;

[0018] determining a priority of the defect point according to the defect severity;

[0019] generating the optimization suggestion according to the defect point and the optimization rule library according to the priority.

[0020] In some embodiments, the determining of the defect severity of the defect point comprises:

[0021] determining an operation failure frequency and an operation blocking degree;

[0022] determining the defect severity of the defect point according to the operation failure frequency and the operation blocking degree.

[0023] In some embodiments, the method further comprises:

[0024] detecting whether there is a ring dependency in a configuration item dependency graph;

[0025] if there is, determining that there is a dependency conflict and prompting the target object to modify;

[0026] if there is not, determining that there is no dependency conflict and that the configuration verification is passed.

[0027] In some embodiments, the method further comprises:

[0028] when the configuration verification is passed, deploying the configuration to an application system;

[0029] collecting a running index of the application system and evaluating an optimization effect according to the running index;

[0030] if the optimization effect does not reach an expectation, re-optimizing the configuration of the application system.

[0031] To solve the above technical problems, the application further provides a real-time conflict-free application full-link generation system, comprising:

[0032] An operation sequence generation module is configured to capture operation information of a target object in an application system and form operation sequences according to the operation information;

[0033] An operation sequence analysis module is configured to analyze the operation sequences and determine frequent operation sequences and abnormal operation sequences;

[0034] A defect point identification module is configured to identify defect points according to the frequent operation sequences and the abnormal operation sequences;

[0035] An optimization suggestion generation module is configured to call an optimization rule library according to the defect points and generate optimization suggestions;

[0036] A configuration optimization module is configured to push the optimization suggestions to a configuration interface and optimize the configuration of the application system according to the optimization suggestions when the target object confirms the optimization suggestions.

[0037] To solve the above technical problems, the application further provides an electronic device, which comprises:

[0038] A memory is configured to store a computer program;

[0039] A processor is configured to execute the computer program to implement the steps of the real-time conflict-free application system full-link generation method.

[0040] To solve the above technical problems, the application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the real-time conflict-free application system full-link generation method.

[0041] The real-time conflict-free application system full-link generation method provided by the application comprises the following steps: operation information of a target object in an application system is captured, and operation sequences are formed according to the operation information; the operation sequences are analyzed, and frequent operation sequences and abnormal operation sequences are determined; defect points are identified according to the frequent operation sequences and the abnormal operation sequences; an optimization rule library is called according to the defect points, and optimization suggestions are generated; the optimization suggestions are pushed to a configuration interface, and the configuration of the application system is optimized according to the optimization suggestions when the target object confirms the optimization suggestions.

[0042] It can be seen that the real-time conflict-free application system full-link generation method provided in the application can track and collect data of user operation in the whole process, form an operation sequence, and automatically analyze the operation sequence, so as to objectively and accurately identify defect points, greatly improve the efficiency and accuracy of defect identification, and timely optimize defects existing in the application system. The real-time conflict-free application system full-link generation method provided in the application builds a complete closed loop of configuration-use-optimization, realizes continuous automatic optimization of the application system, and enables the application system to adapt to changes in user demand.

[0043] The real-time conflict-free application full-link generation system, the electronic device and the computer readable storage medium provided in the application all have the above technical effects. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the application, the drawings needed in the prior art and the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 A flowchart of a real-time conflict-free application system full-link generation method provided in an embodiment of the application;

[0046] Figure 2 An operation sequence analysis flowchart provided in an embodiment of the application;

[0047] Figure 3 A system interaction diagram provided in an embodiment of the application;

[0048] Figure 4 A full-link closed loop diagram provided in an embodiment of the application;

[0049] Figure 5 A real-time conflict-free application full-link generation system provided in an embodiment of the application;

[0050] Figure 6 A schematic diagram of an electronic device provided in an embodiment of the application. DETAILED DESCRIPTION

[0051] The core of the application is to provide a real-time conflict-free application system full-link generation method, system, electronic device and storage medium, which can timely optimize defects existing in the application system, and improve the defect identification efficiency and accuracy.

[0052] To make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0053] Reference is made to Figure 1 , Figure 1 A flowchart of a real-time conflict-free application system full-link generation method provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the method comprises the following steps. Figure 1

[0054] S101: Capture operation information of a target object in an application system, and form an operation sequence according to the operation information.

[0055] The execution subject of the embodiments of the present application is a real-time conflict-free application full-link generation system. The target object can be a user. The real-time conflict-free application full-link generation system captures interactive data of the user in real time, collects various operation behaviors of the user in the use process of the application system, including field modification, process jump, function call, and other operation behaviors and corresponding time stamps, operation results, and other information, by using a burying point technology and a log recording mechanism, to provide a data basis for subsequent analysis.

[0056] Specifically, a burying point component is deployed into the generated application system to bury points at key nodes of user operations. When the user performs field modification, process operation, and other behaviors, the burying point component captures operation information in real time, including an operation type O, an operation object O_id, an operation time t, and an operation result R, to form an operation record O_rec=(O, O_id, t, R). The operation record is transmitted to a data storage center in real time for storage. Meanwhile, a log backup mechanism is set to ensure the integrity and security of the operation data.

[0057] For example, in an e-commerce order processing system, the user frequently performs operation rollback when submitting an order, from the selection of goods to the filling of a delivery address link, with an average of 3 return modification operations per order. The real-time conflict-free application full-link generation system records these operation information, such as operation time and page node before rollback, to provide a detailed data basis for subsequent analysis.

[0058] The real-time conflict-free application full-link generation system extracts the operation record from the data storage center, and arranges it into an operation sequence according to the user identifier and time sequence .

[0059] S102: Analyze the operation sequence to determine frequent operation sequences and abnormal operation sequences. ​

[0060] The operation sequences are analyzed by using a sequential pattern mining algorithm to determine frequent operation sequences and abnormal operation sequences.

[0061] In some embodiments, analyzing the operation sequences to determine frequent operation sequences and abnormal operation sequences comprises:

[0062] calculating support and confidence of the operation sequences; the support is used to measure the frequency of occurrence of the operation sequences; and the confidence is used to measure the driving probability of the preceding operation on the subsequent operation in the operation sequences;

[0063] screening frequent operation sequences and abnormal operation sequences according to the support and the confidence.

[0064] Screening frequent operation sequences and abnormal operation sequences according to the support and the confidence comprises:

[0065] if the support is greater than a first preset threshold and the confidence is greater than a second preset threshold, the operation sequence is a frequent operation sequence;

[0066] if the support is less than or equal to a third preset threshold and the confidence is less than or equal to a fourth preset threshold, the operation sequence is an abnormal operation sequence.

[0067] Reference Figure 2 As shown in the figure, the support and the confidence are calculated. The support is used to measure the frequency of occurrence of an operation sequence (the frequency of occurrence of an operation sequence can be equal to the proportion of the number of occurrences of the operation sequence to the total number of operation sequences).

[0068] The confidence is used to measure the driving probability of the preceding operation on the subsequent operation in the operation sequences (for example, the confidence of "operation A→operation B" = the number of times that B appears after A / the total number of times that A appears).

[0069] The support calculation formula is: Support( )= (the number of sequences containing and followed by ) / total sequence number; and the confidence calculation formula is: Confidence( )= (the number of sequences containing and followed by ) / the number of sequences containing .

[0070] The threshold corresponding to the support degree is set as a first preset threshold and a third preset threshold, and the threshold corresponding to the confidence degree is set as a second preset threshold and a fourth preset threshold. The threshold corresponding to the frequent operation sequence is set to pay more attention to "high frequency" and "logical coherence", and is used to identify the user's regular demand that is not covered by the guide. The threshold corresponding to the abnormal operation sequence is set to pay more attention to "low frequency" and "logical chaos", and is used to identify the step defects (such as missing dependency relationship and insufficient prompt) of the guide. The two achieve accurate classification of the operation sequence through the significant difference of the threshold, and provide a clear direction for guide optimization. If the support degree is greater than the first preset threshold and the confidence degree is greater than the second preset threshold, the operation sequence is considered as a frequent operation sequence. If the support degree is less than or equal to the third preset threshold and the confidence degree is less than or equal to the fourth preset threshold, the operation sequence is an abnormal operation sequence.

[0071] For example, in the inventory configuration scenario of an e-commerce system, when the user configures the inventory of a product, the user needs to set parameters such as "initial inventory", "inventory warning threshold", "replenishment trigger condition" and the like through the guide.

[0072] Operation sequence: the user frequently performs "modify 'inventory warning threshold' -> modify'replenishment trigger condition'" (this operation sequence is denoted as sequence S1).

[0073] Data statistics: there are 1000 total operation sequences, and sequence S1 appears 180 times. Among them, the number of times of "modify inventory warning threshold" followed by "modify replenishment trigger condition" is 162 times.

[0074] Threshold setting: the first preset threshold is 15%, and the second preset threshold is 70%.

[0075] The support degree threshold is greater than or equal to 15% (180 / 1000=18%>15%), which indicates that the operation sequence appears frequently.

[0076] The confidence degree threshold is greater than or equal to 70% (162 / 180=90%>70%), which indicates that "modify warning threshold" will probably adjust "replenishment condition" with high probability, and the logic is coherent.

[0077] Therefore, it is determined that S1 is a frequent operation mode, which indicates that the guide may not associate the two configuration items, and needs to be optimized (for example, a linkage configuration entry is added).

[0078] Operation sequence: the user occasionally performs "modify 'initial inventory' -> delete 'inventory warning threshold' -> re-add 'initial inventory'" (this operation sequence is denoted as sequence S1').

[0079] Data statistics: S1' appears only 25 times; the number of times of "delete warning threshold" followed by re-adding "initial inventory" is 8 times.

[0080] Threshold setting: the third preset threshold is 5%, and the fourth preset threshold is 30%.

[0081] Support threshold ≤ 5% (25 / 1000 = 2.5% ≤ 5%), indicating that the operation sequence is rare.

[0082] Confidence threshold ≤ 30% (8 / 25 = 32% ≈ 30%), indicating that the operation logic is chaotic (adding randomly after deleting).

[0083] It is determined that S1' is an abnormal operation sequence, which may be caused by the user's misoperation due to the guide not prompting the "dependence relationship between initial inventory and early warning threshold".

[0084] S103: According to the frequent operation sequence and the abnormal operation sequence, identifying defect points.

[0085] Based on the obtained frequent operation sequence and abnormal operation sequence, combined with the preset business rules and function indicators of the application system, the defect points are identified. A defect point identification model is constructed to identify the defect points. For the same field modification operation that frequently appears, it is determined that the field design is unreasonable. For the operation sequence with failed operation result and repeated attempts, it is determined that there is an obstacle in the process guide, and the domain knowledge graph of the dynamic domain closed-loop application system intelligent generation system can be called to correct the domain weight of the defect points.

[0086] Traditional operation sequence analysis algorithms mostly use simple statistical methods, such as frequency statistics, which can only identify high-frequency operations and cannot mine the association relationships and potential patterns between operations, and have weak recognition ability for abnormal operations. The algorithm process is usually: collecting operation data → statistical operation frequency → outputting high-frequency operation list.

[0087] The operation sequence analysis algorithm provided in the present application is an operation sequence analysis and defect identification algorithm based on sequence pattern mining and machine learning. This algorithm not only can count high-frequency operations, but also can identify the association rules between operations through sequence pattern mining, and identify abnormal operation sequences through machine learning model, and then accurately locate the defect points.

[0088] By calculating the support and confidence of the operation sequence, the hidden association between operations is mined, such as the pattern of "modify A field and then modify B field", which cannot be realized by traditional frequency statistical algorithm. At the same time, a machine learning model (such as isolated forest algorithm) is introduced for anomaly detection, which identifies normal operation patterns through model training, and then finds abnormal operation sequences deviating from the normal patterns, improving the accuracy of defect identification.

[0089] In the priority ranking of defect points, multiple factors such as operation failure frequency and user blocking degree are considered, and the defect severity is calculated by weighted calculation, so that the priority ranking is more scientific and reasonable, while the traditional algorithm often only sorts according to the operation frequency, ignoring other important factors.

[0090] The operation sequence analysis algorithm provided in the application combines operation sequence analysis and defect identification organically to form a complete analysis-identification process, and provides accurate basis for dynamic optimization suggestion generation. The traditional algorithm can only provide scattered operation statistical data, which is difficult to be directly used for system optimization.

[0091] S104: calling an optimization rule library according to the defect point to generate an optimization suggestion.

[0092] Based on the defect point obtained by analysis, the optimization rule library is constructed in combination with the application system function architecture and business requirements, and the targeted guide step optimization suggestion is automatically generated through the rule matching and reasoning engine, such as adding a configuration item, adjusting the process order, simplifying the operation steps, etc.

[0093] In some embodiments, calling the optimization rule library according to the defect point to generate an optimization suggestion includes:

[0094] determining the defect severity of the defect point;

[0095] determining the priority of the defect point according to the defect severity;

[0096] according to the priority, calling the optimization rule library according to the defect point to generate an optimization suggestion.

[0097] In some embodiments, determining the defect severity of the defect point includes:

[0098] determining the operation failure frequency and the operation blocking degree;

[0099] determining the defect severity of the defect point according to the operation failure frequency and the operation blocking degree.

[0100] The operation failure frequency is determined based on the occurrence frequency of the operation marked as failure in the operation sequence, and is used to reflect the defect of the guide in supporting the user operation.

[0101] The determination process of the operation failure frequency includes:

[0102] defining the failure operation type:

[0103] the following operations are marked as “failure operation” through system log marking rules:

[0104] the operation returns an error code (such as returning 400 for field format verification failure);

[0105] the operation is forcibly terminated by the system (such as being rejected because the submitted content does not meet the business rules);

[0106] the user actively triggers the operation to be cancelled (such as clicking “cancel” “return” and not completing the target process).

[0107] Data sampling and statistics:

[0108] Statistics from operation sequences within a target time window (e.g., 24 hours) extracted from the application system runtime:

[0109] Total operation times (T): The total number of operation records of users in the functional module within the target time window.

[0110] Failed operation times (F_total): The total number of failed operations that meet the above definition.

[0111] Frequency calculation:

[0112] The operation failure frequency formula is:

[0113] F=F_total / T x 100%. The result is rounded to two decimal places, with a value range of 0~100%.

[0114] For example, in the "mobile phone number input" function of the customer information management system, the total operation times T=500 times within 24 hours, and the operation F_total=120 times rejected due to format errors, then: operation failure frequency F=120 / 500 x 100%=24.00%.

[0115] Operation blocking degree, i.e., user blocking degree, is determined based on user behavior characteristics (such as repeated operations, pause time, process jump) when the operation is blocked, which is used to quantify the degree of operation obstacles caused by system defects.

[0116] The operation blocking degree determination process includes:

[0117] Define blocking behavior indicators:

[0118] Extract 3 types of key blocking features from operation sequences, and assign weights to each feature (ω_1=0.4, ω_2=0.3, ω_3=0.3).

[0119] Repeated operation rate (R): The number of consecutive failed operations of the same operation / total operation times;

[0120] Abnormal pause time (S): The number of operation intervals exceeding 3 times the average response time / total operation times;

[0121] Process jump rate (J): The number of unexpected cross-step jumps / total process steps.

[0122] Feature quantification and normalization:

[0123] Standardize each feature to 0~1 (the higher the value, the more severe the blocking):

[0124] Repetition rate: R_"norm"=min(Rx2,1) (recorded as 1 if the repetition rate exceeds 50%);

[0125] Abnormal pause time: S_"norm"=min(Sx3,1) (recorded as 1 if the pause rate exceeds 33%);

[0126] Flow jump rate: J_"norm"=min(Jx2,1) (recorded as 1 if the jump rate exceeds 50%).

[0127] Operation blocking degree calculation:

[0128] Operation blocking degree formula:

[0129] E=ω_1×R_"norm"+ω_2×S_"norm"+ω_3×J_"norm". The result is rounded to two decimal places, with a value range of 0~1.

[0130] For example, in the "time selection" function of the customer reservation system:

[0131] Repetition rate R=30%→R_"norm"=0.3x2=0.6;

[0132] Abnormal pause time S=20%→S_"norm"=0.2x3=0.6;

[0133] Flow jump rate J=10%→J_"norm"=0.1x2=0.2;

[0134] Then: E=0.4x0.6+0.3x0.6+0.3x0.2=0.24+0.18+0.06=0.48.

[0135] Calculate defect severity D=αxF+βxE (where F is the operation failure frequency, E is the operation blocking degree, and α, β are weight coefficients). According to the defect severity, determine the priority of the defect point, and then generate optimization suggestions according to the priority order.

[0136] Based on the operation failure frequency and the operation blocking degree, the defect severity is calculated by weighting, which makes the priority ranking more reasonable.

[0137] For example, in the customer reservation system, when the user selects the reservation period, the operation of "selecting the period → prompting that the period is full → returning to reselect" repeatedly occurs, and on average, 4 similar backtracking occurs for each reservation operation. The operation sequence support degree reaches 0.75, and the confidence degree is 0.82. The defect point identification model combines the system business rules to determine that there is a defect in the period display mechanism in the reservation process, and the defect severity D=0.6x4+0.4x0.8=2.72 is calculated, which is listed as a medium-high priority defect.

[0138] The real-time conflict-free application full-link generation system calls an optimization rule library according to the identified defects and priorities. According to the defect analysis result, the dependent rules of the zero-conflict autonomous healing application full-stack generation system are corrected. The rule library includes various rules such as configuration item addition, process adjustment, interface optimization, etc. For example, for the case of frequent modification of inventory warning value in the inventory management system, the "high-frequency modification field -> add configuration item" rule is matched, and the optimization suggestion of "adding 'inventory warning threshold' configuration item" is automatically generated; for the case of process blocking, the suggestion of adjusting the process steps or adding prompt instructions is generated. After the optimization suggestion is generated, the defect analysis basis and the expected optimization effect are attached.

[0139] For example, in the customer reservation system, the user frequently appears the operation sequence of "selecting a reservation time -> checking the remaining number -> returning to reselect", and the analysis shows that the support degree of this sequence is 0.78 and the confidence degree is 0.83. The dynamic optimization suggestion generation module matches the "repetitive operation caused by cumbersome process -> simplify process steps" rule, and automatically generates the optimization suggestion of "real-time display of the remaining number on the reservation time selection page", and attaches the analysis basis of the user's multiple operations caused by information opacity, which is expected to reduce the user's invalid operation by more than 50%.

[0140] S105: Push the optimization suggestion to the configuration interface, and when the target object confirms the optimization suggestion, optimize the configuration of the application system according to the optimization suggestion.

[0141] The generated optimization suggestion is pushed to the configuration interface, and after the user confirms it, the real-time conflict-free application full-link generation system updates the configuration of the application system according to the optimization suggestion.

[0142] In some embodiments, it further includes:

[0143] Detecting whether there is a circular dependency in the configuration item dependency graph;

[0144] If there is, it is determined that there is a dependency conflict, and the target object is prompted to modify;

[0145] If not, it is determined that there is no dependency conflict, and the configuration verification is passed.

[0146] In some embodiments, it further includes:

[0147] When the configuration verification is passed, deploy the configuration to the application system;

[0148] Collect the running indicators of the application system, and evaluate the optimization effect according to the running indicators;

[0149] If the optimization effect does not meet the expectation, re-optimize the configuration of the application system.

[0150] The real-time conflict-free application full-link generation system updates the configuration of the application system according to the optimization suggestion, and at the same time, the real-time conflict-free verification mechanism is started, and the dependency topology graph construction algorithm of the zero-conflict autonomous healing type application full-stack generation system uses the adjacency matrix storage module to store the dependency relationship. The configuration item dependency graph G=(V, E) is constructed, where V is the configuration item node, and E is the dependency relationship edge. It is detected whether there is a ring dependency in the graph, and if there is a ring dependency, it is judged that there is a dependency conflict and the AI resolution engine is triggered to prompt the user to modify.

[0151] For example, in the customer reservation system, after the user confirms the optimization suggestion of "displaying the remaining number of seats in real time on the reservation time selection page", the automatic engine updates the application system configuration. The real-time conflict-free verification mechanism is started immediately, and the dependency relationship graph is constructed between the newly added remaining number of seats display function and the original reservation time selection, user information submission and other configuration items. No dependency conflict is found after detection, ensuring that the configuration is updated without conflict between the system function modules.

[0152] After the configuration verification is passed, the configuration is converted into executable code and the system is deployed. Real-time collection of application system running indicators such as response time, error rate, resource occupation, etc., combined with user operation feedback data, to evaluate the optimization effect. If the optimization effect is not as expected, a new round of optimization cycle is started.

[0153] For example, after the customer service system is deployed, it is found that the average time for users to submit a work order is still relatively long, and the error submission rate has not decreased significantly. After analyzing these data combined with operation behavior data, it is found that users still have some repeated operations, so a new round of optimization cycle is started to further improve the performance of the application system.

[0154] During the configuration process of the application system, a real-time dependency relationship detection algorithm can be introduced to instantly check the configuration items input by the user, identify potential dependency conflicts by constructing a dependency relationship graph, and intercept dependency errors in the configuration phase to ensure the effectiveness of the configuration.

[0155] Among them, the real-time conflict-free application full-link generation system can include a dynamic domain driving engine. Reference Figure 3As shown, the dynamic domain driving engine receives the domain configuration stream (including domain ID, core module constraint) output by the dynamic domain closed-loop application system intelligent generation system, and automatically loads the preset conflict detection rule library according to the domain characteristics. The dynamic domain closed-loop application system intelligent generation system extracts the related business process and functional module from the domain knowledge graph according to the keywords input by the user, such as the domain type, and outputs the domain configuration stream. In addition, the real-time conflict-free application full-link generation system can include an autonomous healing feedback channel. Through the autonomous healing feedback channel, the operation behavior data and conflict early warning data of the application system during running are synchronized to the zero-conflict autonomous healing application full-stack generation system, and the running time optimization instructions fed back by the zero-conflict autonomous healing application full-stack generation system are received.

[0156] In addition, with reference to Figure 4 As shown, a full-link management process from requirement description, configuration generation, system running, operation feedback to optimization iteration can be constructed, and the data of each link such as requirement analysis, development configuration, test verification and operation monitoring is connected to form a complete closed-loop management system.

[0157] By using a declarative configuration language, a user can complete system configuration by describing business requirements instead of writing code, and the declarative configuration is converted into executable system components by combining an automatic engine, so that the rapid generation and deployment of an application system are realized.

[0158] The real-time conflict-free application system full-link generation method provided by the embodiments of the present application can be applied in a cross-border medical material scheduling system.

[0159] By using multi-dimensional data modeling and feature extraction technology, the business characteristics of the "medical logistics" field are accurately identified, the automatic loading process of the temperature control transportation module is triggered, and the dynamic control and compliance guarantee of the temperature parameter in the whole-link transportation process of medical materials are realized.

[0160] Relying on the zero-conflict autonomous healing application full-stack generation system, a multi-modal conflict detection model including power management, data interface and other dimensions is constructed, systematic compatibility verification of the temperature control module and the GPS positioning module is carried out, and through the power load balancing algorithm and the resource scheduling strategy, the stability and reliability of system running are guaranteed.

[0161] The system operation log is deeply mined, the high-frequency feature of the operation sequence of "temperature parameter configuration → geographic coordinate update" is identified, and the support degree reaches 0.88, which provides a quantitative basis for system interaction process optimization.

[0162] A cold chain equipment power consumption parameter dynamic configuration module is introduced in the system configuration layer, and the energy management strategy optimization in different operation scenarios is realized through an adaptive algorithm.

[0163] The power distribution middleware is deployed, and a real-time monitoring and intelligent solution system for power conflicts between modules is constructed based on a priority scheduling mechanism and a resource isolation technology.

[0164] Based on the optimization scheme provided in the embodiments of the present application, the temperature control parameter setting guide logic is reconfigured, and the user operation efficiency and system availability are improved by reducing the operation level and redundant prompts.

[0165] Through the technical practice in the cross-border medical material dispatching system, the technical feasibility and engineering practicability of the real-time conflict-free application system full-link generation method provided in the embodiments of the present application in a complex business scenario are fully verified.

[0166] The real-time conflict-free application system full-link generation method provided in the above embodiments of the present application has the following technical innovations:

[0167] The traditional scheme adopts a static configuration mode and lacks real-time perception ability for user operation behavior, while the embodiments of the present application realize full-process tracking and data collection of user operation through the runtime operation behavior collection module, providing real-time and comprehensive data support for subsequent analysis.

[0168] The traditional scheme relies on manual testing and user feedback, which has a lag and subjectivity. The embodiments of the present application introduce an operation sequence analysis algorithm and a machine learning model, which can objectively and accurately identify guide defects through automatic analysis of massive operation data, greatly improving the efficiency and accuracy of defect identification.

[0169] The traditional scheme does not form an effective optimization closed loop, and system optimization is mostly a passive response. The embodiments of the present application construct a complete closed loop of configuration-use-optimization, realize the continuous automatic optimization of the system through dynamic optimization suggestion generation and full-link management, and make the system adaptive to user demand changes.

[0170] In the traditional scheme, conflict detection is mostly performed after the system is generated. The embodiments of the present application front-load the verification link to the configuration period, intercept dependency errors in advance through the construction of a dependency graph and real-time detection algorithm, and solve the problem of high conflict repair cost in the traditional scheme.

[0171] In addition, the traditional technology generates a system relying on imperative programming, which has poor flexibility. The method combines declarative configuration with an automation engine, so that users do not need to focus on technical details and only need to describe business requirements, improving the flexibility and ease of use of system generation.

[0172] In the traditional application system generation scenario, users need to have strong technical background, and the configuration process is complicated and long, which is difficult to quickly respond to changes in business requirements. The scheme provided in the embodiments of the present application reduces the technical threshold, so that non-technical personnel can also quickly generate an application system through declarative configuration.

[0173] In a system usage scenario, the traditional system wizard is fixed and unchangeable, and the user needs to adapt to the system design passively. When the user's needs change, the system is difficult to adjust quickly. The scheme provided by the embodiments of the present application can dynamically optimize the wizard according to the user's real-time operation behavior, is suitable for scenarios where user operation habits are diverse and business process changes frequently, such as e-commerce promotion activity systems, project management systems, etc., and can greatly improve user experience and system applicability.

[0174] In a traditional scenario, system generation is disconnected from operation and maintenance monitoring, and operation and maintenance problems are difficult to feed back to system optimization in time. The full-link closed-loop scenario of the scheme provided by the embodiments of the present application includes operation and maintenance monitoring data into the optimization cycle, is suitable for scenarios where system stability and reliability are required, such as financial transaction systems, medical information systems, etc., can discover and solve problems in operation and maintenance in time, and ensures stable operation of the system.

[0175] In a multi-team collaboration scenario, the traditional method is prone to configuration conflicts and poor communication. The real-time conflict-free verification and full-link management provided by the embodiments of the present application enable multiple teams to discover conflicts in real time and solve them collaboratively during the configuration process, and is suitable for scenarios where large enterprises develop systems in collaboration with multiple departments, improving team collaboration efficiency.

[0176] For example, a cross-border e-commerce system has a payment timeout problem after deployment: 1. The "payment interface call→failure retry" high-frequency operation sequence (confidence 0.92) is monitored through the full-link generation method; 2. Trigger domain process reconstruction and add payment risk control configuration steps; 3. Call the interface compatibility detection of the zero-conflict autonomous healing type application full-stack generation system to find SSL protocol conflicts; 4. The AI resolution engine generates a TLS protocol upgrade scheme. The system optimization cycle is shortened from 14 days to 3 hours through the above steps, achieving a significant improvement in efficiency.

[0177] In summary, the real-time conflict-free application system full-link generation method provided by the present application tracks and collects data throughout the user's operation, forms an operation sequence, and automatically analyzes the operation sequence, which can objectively and accurately identify defect points, greatly improving the efficiency and accuracy of defect identification and optimizing defects in the application system in time. The real-time conflict-free application system full-link generation method provided by the present application builds a complete closed loop of configuration-use-optimization, realizes the continuous automatic optimization of the application system, and makes the application system adaptive to changes in user needs.

[0178] The present application also provides a real-time conflict-free application full-link generation system. The system described below can be mutually corresponding with the method described above. Please refer to Figure 5 , Figure 5 A schematic diagram of a real-time conflict-free application full-link generation system provided by the embodiments of the present application is shown in FIG. 1.Figure 5 The system comprises:

[0179] An operation sequence generation module 10 is configured to capture operation information of a target object in an application system and form operation sequences according to the operation information.

[0180] An operation sequence analysis module 20 is configured to analyze the operation sequences and determine frequent operation sequences and abnormal operation sequences.

[0181] A defect point identification module 30 is configured to identify defect points according to the frequent operation sequences and the abnormal operation sequences.

[0182] An optimization suggestion generation module 40 is configured to call an optimization rule library according to the defect points and generate optimization suggestions.

[0183] A configuration optimization module 50 is configured to push the optimization suggestions to a configuration interface and optimize the configuration of the application system according to the optimization suggestions when the target object confirms the optimization suggestions.

[0184] In the above embodiment, as a specific implementation, the operation sequence analysis module 20 comprises:

[0185] A calculation unit is configured to calculate the support and confidence of the operation sequences; the support is used to measure the frequency of the operation sequences; and the confidence is used to measure the driving probability of the previous operation on the subsequent operation in the operation sequences.

[0186] A screening unit is configured to screen the frequent operation sequences and the abnormal operation sequences according to the support and the confidence.

[0187] In the above embodiment, as a specific implementation, the screening unit is configured to:

[0188] If the support is greater than a first preset threshold and the confidence is greater than a second preset threshold, the operation sequence is a frequent operation sequence.

[0189] If the support is less than or equal to a third preset threshold and the confidence is less than or equal to a fourth preset threshold, the operation sequence is an abnormal operation sequence.

[0190] In the above embodiment, as a specific implementation, the optimization suggestion generation module 40 comprises:

[0191] A defect severity determination unit is configured to determine the defect severity of the defect points.

[0192] A priority determination unit is configured to determine the priority of the defect points according to the defect severity.

[0193] An optimization suggestion generation unit is configured to generate optimization suggestions according to the defect points by invoking an optimization rule library according to the priorities.

[0194] In the above embodiments, as a specific implementation, the defect severity determination unit is configured to:

[0195] determine the operation failure frequency and the operation blocking degree;

[0196] determine the defect severity of the defect points according to the operation failure frequency and the operation blocking degree.

[0197] In the above embodiments, as a specific implementation, the method further comprises:

[0198] a conflict detection module configured to detect whether there is a circular dependency in the configuration item dependency graph;

[0199] a modification prompt module configured to, if there is, determine that there is a dependency conflict and prompt the target object to modify; and if there is not, determine that there is no dependency conflict and the configuration verification is passed.

[0200] In the above embodiments, as a specific implementation, the method further comprises:

[0201] a deployment module configured to, when the configuration verification is passed, deploy the configuration to an application system;

[0202] an evaluation module configured to collect running indexes of the application system and evaluate optimization effects according to the running indexes;

[0203] a re-optimization module configured to, if the optimization effects do not reach expectations, re-optimize the configuration of the application system.

[0204] The application also provides an electronic device, as shown in Figure 6 The device comprises a memory 1 and a processor 2.

[0205] The memory 1 is configured to store a computer program.

[0206] The processor 2 is configured to execute the computer program to implement the following steps:

[0207] capture operation information of a target object in an application system and form operation sequences according to the operation information;

[0208] analyze the operation sequences to determine frequent operation sequences and abnormal operation sequences;

[0209] identify defect points according to the frequent operation sequences and the abnormal operation sequences;

[0210] According to the defect point, an optimization rule library is called to generate an optimization suggestion;

[0211] The optimization suggestion is pushed to a configuration interface, and when the target object confirms the optimization suggestion, the configuration of the application system is optimized according to the optimization suggestion.

[0212] For the device provided in the present application, refer to the method embodiments described above, which will not be repeated here.

[0213] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0214] Operation information of a target object in an application system is captured, and an operation sequence is formed according to the operation information;

[0215] The operation sequence is analyzed to determine a frequent operation sequence and an abnormal operation sequence;

[0216] According to the frequent operation sequence and the abnormal operation sequence, a defect point is identified;

[0217] According to the defect point, an optimization rule library is called to generate an optimization suggestion;

[0218] The optimization suggestion is pushed to a configuration interface, and when the target object confirms the optimization suggestion, the configuration of the application system is optimized according to the optimization suggestion.

[0219] The computer readable storage medium can include a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0220] For the computer readable storage medium provided in the present application, refer to the method embodiments described above, which will not be repeated here.

[0221] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the device, equipment and computer readable storage medium disclosed in the embodiments, since they correspond to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0222] Those skilled in the art will further realize that the mere conception of the examples described herein is not a limitation as to the scope or application of this application. The steps of a method or algorithm described in connection with the examples disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM, flash memory, ROM, electrically programmable ROM (EPROM or EEPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, hardwired circuitry can be used in place of or in combination with software modules. The application deems that any method or algorithm for completing the described functions is within the scope of the application.

[0223] Those skilled in the art will further realize that the mere conception of the examples described herein is not a limitation as to the scope or application of this application. The steps of a method or algorithm described in connection with the examples disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM, flash memory, ROM, electrically programmable ROM (EPROM or EEPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, hardwired circuitry can be used in place of or in combination with software modules. The application deems that any method or algorithm for completing the described functions is within the scope of the application.

[0224] The real-time conflict-free application system full-link generation method, system, electronic device and storage medium provided by the application are described in detail above. The principles and implementation manners of the application are described by applying specific examples in the present disclosure. The above description of the examples is only used to help understand the method of the application and its core idea. It should be noted that, for those skilled in the art, without departing from the principles of the application, some improvements and modifications can be made to the application, and these improvements and modifications also fall within the protection scope of the claims of the application.

Claims

1. A real-time non-collision application system full-link generation method, characterized in that, The method comprises the following steps: capturing operation information of a target object in an application system, and forming operation sequences according to the operation information; analyzing the operation sequences to determine frequent operation sequences and abnormal operation sequences; identifying defect points according to the frequent operation sequences and the abnormal operation sequences; calling an optimization rule library according to the defect points to generate optimization suggestions; pushing the optimization suggestions to a configuration interface, and optimizing the configuration of the application system according to the optimization suggestions after the target object confirms the optimization suggestions.

2. The real-time non-conflicting application system full link generation method according to claim 1, characterized in that, The step of analyzing the operation sequences to determine frequent operation sequences and abnormal operation sequences comprises the following steps: calculating the support degree and the confidence degree of the operation sequences; the support degree is used to measure the frequency of the occurrence of the operation sequences; and the confidence degree is used to measure the driving probability of the previous operation on the subsequent operation in the operation sequences; screening the frequent operation sequences and the abnormal operation sequences according to the support degree and the confidence degree.

3. The real-time non-conflicting application system full-link generation method according to claim 2, characterized in that, The step of screening the frequent operation sequences and the abnormal operation sequences according to the support degree and the confidence degree comprises the following steps: if the support degree is greater than a first preset threshold and the confidence degree is greater than a second preset threshold, the operation sequence is a frequent operation sequence; if the support degree is less than or equal to a third preset threshold and the confidence degree is less than or equal to a fourth preset threshold, the operation sequence is an abnormal operation sequence.

4. The real-time non-conflicting application system full link generation method according to claim 1, characterized in that, The step of calling the optimization rule library according to the defect points to generate optimization suggestions comprises the following steps: determining the defect severity of the defect points; determining the priority of the defect points according to the defect severity; generating optimization suggestions according to the optimization rule library according to the defect points in the order of the priority.

5. The real-time non-conflicting application system full link generation method according to claim 4, characterized in that, The step of determining the defect severity of the defect points comprises the following steps: determining the operation failure frequency and the operation blocking degree; determining the defect severity of the defect points according to the operation failure frequency and the operation blocking degree.

6. The real-time non-conflicting application system full link generation method according to claim 1, characterized in that, The method further comprises the following steps: detecting whether there is a ring-shaped dependency in a configuration item dependency graph; if there is, determining that there is a dependency conflict, and prompting the target object to modify; if there is not, determining that there is no dependency conflict, and the configuration verification is passed.

7. The real-time non-conflicting application system full link generation method according to claim 4, characterized in that, The method further comprises the following steps: deploying the configuration to the application system when the configuration verification is passed; collecting the running indexes of the application system, and evaluating the optimization effect according to the running indexes; if the optimization effect does not reach the expectation, re-optimizing the configuration of the application system.

8. A real-time conflict-free application full-link generation system, characterized by, The method comprises the following steps: an operation sequence generation module is configured to capture operation information of a target object in an application system, and form operation sequences according to the operation information; an operation sequence analysis module is configured to analyze the operation sequences to determine frequent operation sequences and abnormal operation sequences; a defect point identification module is configured to identify defect points according to the frequent operation sequences and the abnormal operation sequences; an optimization suggestion generation module is configured to call an optimization rule library according to the defect points to generate optimization suggestions; a configuration optimization module is configured to push the optimization suggestions to a configuration interface, and optimize the configuration of the application system according to the optimization suggestions after the target object confirms the optimization suggestions.

9. An electronic device, comprising: The method comprises the following steps: a memory is configured to store a computer program; A processor for implementing the steps of the real-time non-conflict application system full link generation method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, A computer readable storage medium having stored thereon a computer program, the computer program being executed by a processor to implement the steps of the real-time non-conflict application system full link generation method according to any one of claims 1 to 7.

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