Problem closed-loop management system and method based on FRACAS

Abstract

The invention discloses a problem closed-loop management system and method based on FRACAS, and the system comprises a problem collection module, a problem analysis module, a closed-loop measure making module, a closed-loop measure implementation module and an effect evaluation module which are in communication connection, and the problem collection module is used for collecting to-be-solved problems generated when a user uses a target service; the problem analysis module is used for receiving the to-be-solved problem provided by the problem collection module and executing deep analysis of the to-be-solved problem; the closed-loop measure making module is used for determining a closed-loop measure scheme corresponding to the to-be-solved problem according to the deep analysis result of the to-be-solved problem information; the closed-loop measure implementation module is used for executing correction measures of the to-be-solved problem according to the closed-loop measure scheme corresponding to the to-be-solved problem; and the effect evaluation module is used for performing feedback evaluation on the implementation effect after the corrective measures of the to-be-solved problem are executed. The method can effectively promote a management closed loop of a problem to be solved generated in a process of using a target service.

Description

Technical Field

[0001] The present invention belongs to the field of digital business experience management, and in particular to a problem closed-loop management system and method based on FRACAS. Background Art

[0002] FRACAS (Failure Report Analysis and Corrective Action System) is a system widely used in product reliability management, also known as a closed-loop fault information management system. Through a standardized process, the system reports product failures, analyzes the causes of failures, formulates and implements effective closed-loop measures, and feeds back the root causes of failures and closed-loop measures information to the design and development process to prevent failures from recurring and improve product reliability.

[0003] However, in actual application, the above system also has some defects, resulting in unsatisfactory actual application results. For example, the working process is complicated, the actual output data is small, and it is difficult to effectively correspond the target service with the actual output data, resulting in a lack of supervision of the FRACAS process and difficulty in effectively promoting the closed-loop management. This has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of the present invention is to provide a problem closed-loop management system based on FRACAS to address the deficiencies in the prior art. It effectively promotes the management closed loop of solving problems generated in the process of using the target service through a problem collection module, a problem analysis module, a closed-loop measure formulation module, a closed-loop measure implementation module and an effect evaluation module connected by communication.

[0005] An embodiment of the present application provides a problem closed-loop management system based on FRACAS, which is applied to a software product quality and digital business experience collaborative management platform, and the system includes: Communication connection problem collection module, problem analysis module, closed-loop measures formulation module, closed-loop measures implementation module and effect evaluation module, among which, The problem collection module is used to collect unresolved issues that users have when using the target service; The problem analysis module is used to receive the problem information to be solved provided by the problem collection module, and perform in-depth analysis of the problem information to be solved; wherein, the in-depth analysis of the problem information to be solved includes: associating the R&D environment information of the target service with the application environment information of the target service to determine the correlation relationship between the environment information and the cause of the problem to be solved; The closed-loop measure formulation module is used to determine the closed-loop measure scheme corresponding to the problem to be solved according to the in-depth analysis result of the information of the problem to be solved; wherein the closed-loop measure scheme is determined according to the association relationship and the analysis feedback rule model determined by the closed-loop management rules of the problem to be solved based on FRACAS; The closed-loop measure implementation module is used to execute corrective measures for the problem to be solved according to the closed-loop measure solution corresponding to the problem to be solved; The effect evaluation module is used to provide feedback and evaluation on the implementation effect of the corrective measures to be solved after the corrective measures are completed.

[0006] Optionally, the problem collection module includes: A problem data collection unit and a problem data classification unit, wherein: The problem data collection unit is used to collect problem data from the target service monitoring device and / or user reports in real time or regularly during the use of the target service; The problem data classification unit is used to classify and preprocess the collected problem data using a predefined fault model, knowledge base and reasoning algorithm.

[0007] Optionally, the problem analysis module includes: An environmental data association unit and an environmental data analysis model unit, wherein: The environment data association unit is used to perform feature fusion of environment data information according to the environment data fusion technology, and associate the research and development environment information of the target service with the application environment information of the target service; The environmental data analysis model unit is used to process the correlation between the environmental information after feature fusion and the cause of the problem to be solved according to a preset data analysis model.

[0008] Optionally, the closed-loop measures formulation module includes: Closed-loop measures planning unit, closed-loop measures verification unit and closed-loop measures generation unit, wherein: The closed-loop measures planning unit is used to plan initial corrective measures based on the cause analysis results of the problem to be solved; The closed-loop measure verification unit is used to simulate and verify the formulated initial corrective measures and evaluate the implementation effect; The closed-loop measure generation unit is used to determine the target corrective measures after the simulation evaluation based on the analysis feedback rule model of the closed-loop management rules of the problem to be solved in FRACAS.

[0009] Optionally, the effect evaluation module includes: The feedback evaluation effect closed-loop management unit is used to obtain the evaluation effect closed-loop management test process, verify the target service through the test process, obtain the closed-loop management information of the target service, and generate a closed-loop evaluation report in a specified format based on the closed-loop management information.

[0010] Another embodiment of the present application provides a software product quality and digital business experience collaborative management platform, the platform comprising: At least one of a target service R&D management system and a target service application environment management system, and the FRACAS-based problem closed-loop management system as described above; The target service R&D management system is used to provide R&D environment information to the FRACAS-based problem closed-loop management system through a preset target service development port; The target service application environment management system is used to provide a closed-loop management test process to the effect evaluation module of the FRACAS-based problem closed-loop management system through a preset application environment management interface.

[0011] Another embodiment of the present application provides a closed-loop problem management method based on FRACAS, the method comprising: Collect unresolved issues that users have when using the target service; Correlate the R&D environment information of the target service with the application environment information of the target service, and determine the correlation between the environment information and the cause of the problem to be solved; Determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rules for the problem to be solved based on FRACAS; The problem information of the problem to be solved is input into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

[0012] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to implement the above-mentioned method when executed.

[0013] Another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the above-mentioned method.

[0014] Compared with the prior art, the present invention provides a closed-loop problem management system based on FRACAS, including a communication-connected problem collection module, a problem analysis module, a closed-loop measure formulation module, a closed-loop measure implementation module and an effect evaluation module, wherein the problem collection module is used to collect the unresolved problems generated by users in the process of using the target service; the problem analysis module is used to receive the unresolved problem information provided by the problem collection module, and perform a deep analysis of the unresolved problem information; the closed-loop measure formulation module is used to determine the closed-loop measure solution corresponding to the unresolved problem according to the deep analysis result of the unresolved problem information; the closed-loop measure implementation module is used to execute the corrective measures for the unresolved problem according to the closed-loop measure solution corresponding to the unresolved problem; and the effect evaluation module is used to provide feedback and evaluation on the implementation effect of the corrective measures for the unresolved problem after the corrective measures for the unresolved problem are executed. It can effectively promote the management closed loop of unresolved problems generated in the process of using the target service. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A structural diagram of a problem closed-loop management system based on FRACAS provided by an embodiment of the present invention; Figure 2 A hardware structure block diagram of a computer terminal for a problem closed-loop management method based on FRACAS provided by an embodiment of the present invention; Figure 3 A flowchart of a closed-loop problem management method based on FRACAS provided by an embodiment of the present invention; Figure 4 A structural schematic diagram of a problem closed-loop management device based on FRACAS provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0017] See also Figure 1 , Figure 1 A structural diagram of a problem closed-loop management system based on FRACAS provided by an embodiment of the present invention, Figure 1A problem closed-loop management system 200 based on FRACAS is shown, which is applied to the collaborative management platform of software product quality and digital business experience. The system includes: a communication-connected problem collection module 201, a problem analysis module 202, a closed-loop measure formulation module 203, a closed-loop measure implementation module 204 and an effect evaluation module 205, wherein the problem collection module 201 is used to collect unresolved problems generated by users in the process of using the target service, mainly collecting unresolved problems from user feedback, experience evaluation, and internal feedback in the actual operation of products and services. The problem analysis module 202 is used to receive the unresolved problem information provided by the problem collection module and perform in-depth analysis of the unresolved problem information; wherein the in-depth analysis of the unresolved problem information includes: associating the R&D environment information of the target service with the application environment information of the target service to determine the correlation between the environment information and the cause of the unresolved problem; or using the root cause analysis method to reverse the root cause and link of the problem, and judge the responsible parties based on this, so as to facilitate the subsequent collaborative rectification of the unresolved problems. The closed-loop measure formulation module 203 is used to determine the closed-loop measure plan corresponding to the problem to be solved based on the in-depth analysis results of the information on the problem to be solved; wherein the closed-loop measure plan is determined according to the association relationship and the analysis feedback rule model determined by the closed-loop management rules of the problem to be solved based on FRACAS; the closed-loop measure implementation module 204 is used to execute the corrective measures for the problem to be solved according to the closed-loop measure plan corresponding to the problem to be solved; the effect evaluation module 205 is used to provide feedback evaluation on the implementation effect of the corrective measures for the problem to be solved after the corrective measures for the problem to be solved are executed.

[0018] Specifically, the problem collection module 201 is the starting point of the entire process, and is responsible for collecting problems or anomalies that occur during the use of the target service from the user side. Multiple channels (such as online customer service, email, fault reporting system, etc.) can be provided for users to report problems, and the collected problems to be solved are preliminarily classified and screened to ensure that the problems are accurately recorded and passed to the next link. The problem analysis module 202 is used to deeply analyze the problem information submitted by the problem collection module 201 and try to find the root cause of the problem. For example, the R&D environment (such as code library, build configuration, etc.) and the application environment (such as server configuration, network environment, etc.) can be correlated and analyzed to find out the environmental differences that may cause the problem, and the big data analysis tools and simulation environment can be used to reproduce the problem scenario to more accurately locate the problem. The closed-loop measure formulation module 203 is used to formulate targeted closed-loop measures based on the results of the problem analysis. For example, based on the application of the FRACAS model, a fault reporting, analysis and correction system model can be introduced to ensure that the measures are formulated in accordance with a scientific fault management process. Then, according to the urgency of the problem, the scope of impact and other factors, the multiple problems to be solved are prioritized to ensure the rational allocation of resources, promote communication and collaboration between technology, products, operation and maintenance departments, and jointly develop the best solution. The closed-loop measure implementation module 204 implements specific corrective and preventive measures in accordance with the formulated closed-loop measure plan to ensure that the implementation of all measures is subject to a strict change management process to avoid the introduction of new risks. Record each step and result of the implementation of the measures to facilitate subsequent verification, and promptly inform users of the progress and results of problem solving to improve user satisfaction. The effect evaluation module 205 is used to evaluate the implementation effect of the corrective measures after they are completed to ensure that the problem is effectively solved, and then continuously optimize the problem management process based on the evaluation results to improve the efficiency and quality of problem solving.

[0019] In summary, the entire process forms a complete closed loop. From problem discovery to problem solving to effect evaluation, each link is closely linked, ensuring that problems can be effectively managed and solved.

[0020] In an optional implementation, the problem collection module 201 may include: a problem data collection unit and a problem data classification unit, wherein the problem data collection unit is used to collect problem data from target service monitoring equipment and / or user reports in real time or regularly during the use of the target service; for example, it is used to collect problem data from monitoring equipment, internal evaluation and user reports during the operation of products and services in real time or regularly. The problem data classification unit is used to classify and preprocess the collected problem data using predefined fault models, knowledge bases and reasoning algorithms.

[0021] Specifically, the problem data collection unit may be responsible for collecting problem data arising during the use of the target service from multiple sources in real time or periodically.

[0022] The data source can be through target service monitoring equipment or user reports, etc. The target service monitoring equipment can include server monitoring tools, network monitoring equipment, application performance monitoring (APM) tools, etc., which can capture key information such as system performance, abnormal events, error logs, etc. in real time. User reports can be obtained through problem reports submitted through customer service channels (such as online chat, telephone, email, fault reporting system, etc.), which usually contain detailed information such as the fault phenomenon observed by the user, the time of occurrence, and the scope of impact. For key performance indicators and emergency faults, real-time collection or regular collection can be used to ensure that problems can be discovered and handled immediately.

[0023] The problem data classification unit is used to classify and preprocess the collected problem data using predefined fault models, knowledge bases, and reasoning algorithms so that the subsequent problem analysis module can process it more efficiently. Among them, the predefined fault models can establish a series of common fault modes and corresponding processing procedures based on historical data and expert experience. These models can help the system quickly identify similar problems and give preliminary processing suggestions.

[0024] The knowledge base contains a wealth of resources such as fault cases, solutions, and technical documents, which provide strong support for problem classification and diagnosis. The reasoning algorithm can use advanced technologies such as machine learning and natural language processing (NLP) to intelligently analyze problem data, extract key information, and automatically match the most likely fault type and solution.

[0025] The specific steps of classification and preprocessing may include data cleaning, classification tagging, and data aggregation. Data cleaning is used to remove duplicate, invalid, or redundant data to ensure the accuracy of subsequent analysis. Classification tagging is used to label problem data with corresponding classification labels (such as network failure, software defect, hardware problem, etc.) based on the results of predefined fault models or reasoning algorithms. Data aggregation is used to aggregate similar or related problem data for batch processing or in-depth analysis.

[0026] Through the collaborative work of the above two units, the problem collection module 201 can efficiently collect and pre-process problem data from multiple channels, providing strong support for subsequent problem analysis, closed-loop measure formulation and implementation.

[0027] In an optional embodiment, the problem analysis module 202 may include: an environment data association unit and an environment data analysis model unit, wherein the environment data association unit is used to perform feature fusion of environment data information according to environment data fusion technology, and associate the research and development environment information of the target service with the application environment information of the target service; the environment data analysis model unit is used to process the association relationship between the environment information after feature fusion and the cause of the problem to be solved according to a preset data analysis model.

[0028] Specifically, the environment data association unit is mainly responsible for associating the R&D environment information of the target service with the application environment information of the target service, and performing feature fusion of the environment data information through the environment data fusion technology. Among them, the environment data fusion technology is a technology that integrates and uniformly processes environment data from different sources and in different formats. Through feature extraction, data conversion, data cleaning and other means, the features of the environment data are fused to form a more comprehensive and accurate description of the environment information. The environment data association associates the fused environment data with the R&D environment information and application environment information of the target service. This includes but is not limited to R&D environment information and application environment information, among which the R&D environment information includes code base version, build configuration, unit test results, etc., which are helpful to understand the status of the service in the design and development stage. The application environment information includes server configuration, network topology, operating system version, third-party service dependency, etc., which reflects the status of the service in the actual operating environment. Through the association and fusion of environment data, more abundant context information is provided for subsequent problem analysis to help quickly locate the root cause of the problem.

[0029] The environmental data analysis model unit is used to process the correlation between the environmental information after feature fusion and the cause of the problem to be solved using a preset data analysis model. The preset data analysis model can be constructed based on technologies in the fields of statistics, machine learning, data mining, etc., and is used to identify abnormal patterns, trends or association rules in environmental data.

[0030] Correlation analysis can include comparing the differences between the R&D environment and the application environment to identify environmental factors that may cause problems. It can also include analyzing key variables in environmental data to identify the factors that affect the degree of their contribution to the cause of the problem. Based on the above analysis, the root cause of the problem or the most likely point of failure is inferred. A detailed problem analysis report is generated, including a description of the problem, the analysis results of the environmental data, the root cause inference, and preliminary solution suggestions.

[0031] Through the collaborative work of these two units, the problem analysis module 202 can more deeply understand the relationship between the problem to be solved and the environmental data, and provide strong support for the subsequent closed-loop measures. This analysis method based on environmental data helps to improve the accuracy and efficiency of problem solving.

[0032] In an optional implementation, the closed-loop measure formulation module 203 may include: a closed-loop measure planning unit, a closed-loop measure verification unit and a closed-loop measure generation unit, wherein the closed-loop measure planning unit is used to plan initial corrective measures based on the cause analysis results of the problem to be solved; the closed-loop measure verification unit is used to simulate and verify the formulated initial corrective measures and evaluate the implementation effects; the closed-loop measure generation unit is used to determine the target corrective measures after the simulation evaluation based on the analysis feedback rule model of the closed-loop management rules of the problem to be solved of FRACAS.

[0033] Specifically, the closed-loop measures planning unit is responsible for planning initial corrective measures based on the cause analysis results of the problem to be solved. Receive the cause analysis report of the problem from the problem analysis module 202, including a detailed description of the problem, root cause inference, and preliminary solution suggestions, and deeply understand the nature and scope of the problem to ensure that the corrective measures can solve the problem in a targeted manner. Based on the cause of the problem, by conceiving a variety of possible corrective measures, the conceived plans are preliminarily screened according to factors such as feasibility, cost, and time, and several candidate plans are determined. Then a detailed implementation plan is formulated for the selected candidate plan, including steps, responsible persons, time nodes, etc.

[0034] The closed-loop measures verification unit is responsible for simulating and verifying the initial corrective measures and evaluating their implementation effects. The specific simulation verification steps may include building a simulation environment or using the existing test environment according to the actual operating environment of the target service, implementing initial corrective measures in the simulation environment, observing and recording the implementation process and results, analyzing the implementation results, and evaluating whether the corrective measures effectively solve the problem. The implementation effect evaluation may include collecting key data during the implementation process, such as performance indicators, user feedback, etc. Then, the data before and after implementation are compared and analyzed to evaluate the implementation effect of the corrective measures. Finally, the risks that may be brought about by the corrective measures are evaluated to ensure the safety and stability of the measures.

[0035] The closed-loop measures generation unit determines the target corrective measures after the simulation evaluation based on the analysis feedback rule model of the closed-loop management rules of the problem to be solved in FRACAS (Fault Reporting, Analysis and Corrective System). Among them, the analysis feedback rule model defines a series of analysis feedback rules according to the closed-loop management principle of FRACAS to guide the formulation and optimization of corrective measures. The results of simulation verification and implementation effect evaluation are input into the analysis feedback rule model. Through model calculation and analysis, the final target corrective measures are determined, and the final closed-loop measures plan is generated, including detailed implementation steps, expected effects, risk assessment and response measures. At the same time, the plan is submitted to the closed-loop measures implementation module for execution.

[0036] Through the collaborative work of these three units, the closed-loop measures formulation module 203 can ensure that the formulated corrective measures are both scientific and effective, providing a strong guarantee for the complete resolution of the problem.

[0037] Specifically, the closed-loop measure implementation module 204 is responsible for converting the formulated closed-loop measure plan into actual actions to correct the problem to be solved. According to the closed-loop measure plan corresponding to the problem to be solved provided by the closed-loop measure formulation module, relevant resources are organized and corrective measures are executed according to predetermined steps and time nodes.

[0038] During the implementation of corrective measures, the implementation status is monitored in real time, including progress, problems encountered, resource consumption, etc., to ensure that the implementation process is carried out according to the predetermined plan. In addition, the implementation process, key steps, problems encountered and solutions of the corrective measures are recorded in detail during the implementation of the corrective measures to provide a basis for subsequent problem review and improvement. After the corrective measures are implemented, the implementation effect is evaluated, including problem solving, system performance improvement, user feedback, etc., to verify the effectiveness of the corrective measures.

[0039] Among them, the closed-loop measures plan for the problem to be solved is received from the closed-loop measures formulation module, including detailed implementation steps, responsible persons, time nodes and other information. According to the implementation plan, the required human, material, financial and other resources are organized to ensure that the implementation of corrective measures is not limited by resources. Then, the corrective measures are implemented according to the predetermined steps and time nodes. During the implementation process, communication with all parties is maintained to coordinate and solve the problems encountered in a timely manner. The implementation of corrective measures is monitored in real time through monitoring tools or manual methods to ensure that the implementation process meets expectations. For deviations or problems found, corrective measures are taken in a timely manner. Finally, the implementation process, key steps, problems encountered and solutions of the corrective measures are recorded in detail to form a complete implementation record. After the corrective measures are implemented, relevant data and information are collected to evaluate the implementation effect. The evaluation content includes problem solving, system performance improvement, user feedback and other aspects. According to the evaluation results, it is judged whether the corrective measures are effective and the corresponding follow-up measures are prepared.

[0040] Exemplarily, the analysis feedback rule model can be expressed as: ,in, , , , , , , They represent the quality dimension and efficiency dimension in the evaluation dimension of the problem to be solved. To evaluate the feedback factor, Indicates the evaluation feedback factor to solve the closed-loop management parameters of the problem The impact of , express The number of pending issues in the database. The evaluation feedback factor can be calculated based on the linear weighting method. : in, It is an evaluation factor The weight of It is a problem to be solved In the evaluation elements In terms of building the analysis feedback rule model, you can also choose appropriate deep learning frameworks (such as TensorFlow, PyTorch, etc.) and algorithms (such as convolutional neural networks, recurrent neural networks, self-attention mechanisms, etc.) according to specific needs and scenarios. Design a multi-level neural network structure to more comprehensively determine the analysis feedback of the problem to be solved based on the closed-loop management rules of FRACAS.

[0041] Through the execution of the closed-loop measures implementation module, it can ensure that the problems to be solved are effectively corrected, while improving the efficiency and quality of problem solving. In addition, the monitoring and recording during the implementation process also provides valuable data and experience for subsequent problem review and improvement.

[0042] In an optional implementation, the effect evaluation module 205 may include: a feedback evaluation effect closed-loop management unit, used to obtain an evaluation effect closed-loop management test process, verify the target service through the test process, obtain the closed-loop management information of the target service, and generate a closed-loop evaluation report in a specified format based on the closed-loop management information.

[0043] Specifically, the feedback evaluation effect closed-loop management unit can design a test process for evaluation effect closed-loop management based on the characteristics of the target service and the closed-loop management requirements. The process can cover comprehensive verification of key functions, performance indicators, user experience, etc. of the target service.

[0044] For example, the closed-loop management evaluation table for problems to be solved based on FRACAS can be shown in Table 1 below: Table 1: Closed-loop management evaluation table for issues to be resolved based on FRACAS

[0045] Through the execution of the test process, the target service is strictly verified. During the verification process, by paying close attention to the operating status of the target service and user feedback, relevant information about closed-loop management is collected, such as problem discovery, corrective action execution, effect improvement, etc. Based on the collected closed-loop management information, professional evaluation methods and tools are used to generate a closed-loop evaluation report in a specified format.

[0046] Through the implementation of the closed-loop management unit of feedback evaluation, the effectiveness of closed-loop measures can be fully verified, while providing strong data support for the continuous improvement of target services. The generation of closed-loop evaluation reports not only helps the organization to review and summarize the problem-solving process, but also serves as an important basis for demonstrating problem-solving results to external stakeholders.

[0047] It can be seen that the present invention provides a closed-loop problem management system based on FRACAS, including a communication-connected problem collection module, a problem analysis module, a closed-loop measure formulation module, a closed-loop measure implementation module and an effect evaluation module, wherein the problem collection module is used to collect unresolved problems generated by users in the process of using the target service; the problem analysis module is used to receive the unresolved problem information provided by the problem collection module, and perform in-depth analysis of the unresolved problem information; the closed-loop measure formulation module is used to determine the closed-loop measure solution corresponding to the unresolved problem according to the in-depth analysis result of the unresolved problem information; the closed-loop measure implementation module is used to execute the corrective measures for the unresolved problem according to the closed-loop measure solution corresponding to the unresolved problem; the effect evaluation module is used to provide feedback and evaluation on the implementation effect of the corrective measures for the unresolved problem after the execution of the corrective measures for the unresolved problem is completed. It can effectively promote the management closed loop of unresolved problems generated in the process of using the target service.

[0048] An embodiment of the present invention also provides a software product quality and digital business experience collaborative management platform, the platform comprising: at least one of a target service R&D management system and a target service application environment management system, and the above-mentioned FRACAS-based problem closed-loop management system; the target service R&D management system is used to provide R&D environment information to the FRACAS-based problem closed-loop management system through a preset target service development port; the target service application environment management system is used to provide a closed-loop management test process to the effect evaluation module of the FRACAS-based problem closed-loop management system through a preset application environment management interface.

[0049] Specifically, the software product quality and digital business experience collaborative management platform integrates the target service R&D management system, the target service application environment management system, and the FRACAS-based problem closed-loop management system. Through the collaborative work of the three, it realizes the reliability analysis and management of the target service throughout its entire life cycle from R&D to application.

[0050] Among them, the target service R&D management system is responsible for the development, testing and version control of the target service. Through the preset target service development port, the system can provide R&D environment information to the FRACAS-based problem closed-loop management system. This information includes but is not limited to code base version, build configuration, unit test results, code review reports, etc., providing detailed R&D background for problem analysis.

[0051] The target service application environment management system is responsible for the deployment, monitoring and maintenance of the target service in the actual operating environment. Through the preset application environment management interface, the system can provide closed-loop management test processes to the effect evaluation module of the FRACAS-based problem closed-loop management system. These test processes should be formulated based on the actual situation of the application environment to ensure the authenticity and effectiveness of the test.

[0052] The problem closed-loop management system based on FRACAS integrates the above-mentioned problem collection module, problem analysis module, closed-loop measure formulation module, closed-loop measure implementation module and effect evaluation module, etc., to achieve comprehensive management of target service problems. It improves the problem solving efficiency and quality of target services and promotes the reliability of services. At the same time, through continuous improvement and optimization, it promotes the continuous optimization and upgrading of target services.

[0053] It can be seen that the software product quality and digital business experience collaborative management platform realizes information sharing between R&D, application environment and problem management, and improves the accuracy and real-time nature of data. Through preset interfaces and processes, it ensures seamless connection and efficient collaboration between various links. Based on comprehensive data collection and analysis, it provides strong support for decision-making and improves the scientificity and accuracy of decision-making. Through the closed-loop management mechanism, it realizes continuous tracking and improvement of problems, and promotes the continuous improvement of the reliability and stability of target services.

[0054] The embodiment of the present invention further provides a closed-loop problem management method based on FRACAS, which can be applied to electronic devices such as computer terminals, specifically ordinary computers, quantum computers, etc.

[0055] The following describes it in detail by taking running on a computer terminal as an example. Figure 2 The hardware structure block diagram of a computer terminal of a problem closed-loop management method based on FRACAS provided by an embodiment of the present invention. Figure 2As shown, the computer terminal may include one or more ( Figure 2 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the computer terminal may also include a transmission device 106 for communication functions and an input and output device 108. It can be understood by those skilled in the art that Figure 2 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 2 More or fewer components as shown, or with Figure 2 Different configurations are shown.

[0056] The memory 104 can be used to store software programs and modules of application software, such as program instructions / modules corresponding to a closed-loop problem management method based on FRACAS in an embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned system. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to a computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0057] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0058] See also Figure 3 , Figure 3 A flowchart of a closed-loop problem management method based on FRACAS is provided in an embodiment of the present invention. The method may include: S301: Collecting unresolved issues that arise when users use the target service.

[0059] Specifically, use multiple channels (such as customer support, user feedback systems, social media, user communities, surveys, etc.) to actively and passively collect user feedback to ensure that all problems encountered by users when using the target service can be discovered and recorded in a timely manner.

[0060] S302: Associating the R&D environment information of the target service with the application environment information of the target service, and determining the association relationship between the environment information and the cause of the problem to be solved.

[0061] Specifically, determining the correlation between environmental information and the cause of the problem to be solved includes: extracting R&D environment information, such as code version, development environment configuration, test report, etc. Extracting application environment information, such as server configuration, network status, third-party service dependency, user device information, etc. Using log analysis, event tracking, environment simulation and other technical means to associate R&D environment with application environment information, and find out the environmental factors that may affect the cause of the problem to be solved.

[0062] S303: Determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rules for the problem to be solved based on FRACAS.

[0063] Specifically, according to the problem cause analysis report and FRACAS process, formulate analysis process, feedback mechanism and corrective action plan for specific problems. Construct analysis feedback rule model, which can include standardized steps and rules for problem identification, analysis, solution and verification, and provide a set of efficient and systematic processing process and feedback mechanism for the problems to be solved.

[0064] S304: Input the problem information of the problem to be solved into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

[0065] Specifically, the problem information (including problem description, environmental information, user feedback, etc.) to be solved is input into the analysis feedback rule model. The model automatically or manually analyzes according to the preset rules and processes to generate preliminary problem solutions and corrective measures. Further discussion and verification are carried out based on the results of the model output to determine the final closed-loop analysis results. Through standardized analysis processes and rule models, solutions to problems can be quickly and accurately determined, and corrective measures can be implemented to solve the problems. The entire process forms a closed-loop management system, which continuously cycles from problem discovery to solution to feedback and improvement to continuously improve the reliability of the target service and user satisfaction.

[0066] It can be seen that the present invention collects the unresolved problems generated by users in the process of using the target service; then associates the R&D environment information of the target service with the application environment information of the target service to determine the correlation between the environment information and the cause of the unresolved problem; according to the correlation and the closed-loop management rules of the unresolved problems based on FRACAS, the analysis feedback rule model of the unresolved problem is determined; finally, the problem information of the unresolved problem is input into the analysis feedback rule model to determine the closed-loop analysis result of the unresolved problem. Based on this, from problem discovery to problem solving to feedback and improvement, a continuous cycle is repeated to continuously improve the reliability of the target service and user satisfaction.

[0067] See also Figure 4 , Figure 4 A schematic diagram of a problem closed-loop management device based on FRACAS is provided in an embodiment of the present invention. The device may include: The collection module 401 is used to collect unresolved issues generated by users when using the target service; The first determination module 402 is used to associate the development environment information of the target service with the application environment information of the target service, and determine the association relationship between the environment information and the cause of the problem to be solved; The second determination module 403 is used to determine the analysis feedback rule model of the problem to be solved according to the association relationship and the closed-loop management rules of the problem to be solved based on FRACAS; The third determination module 404 is used to input the problem information of the problem to be solved into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

[0068] It can be seen that the present invention collects the unresolved problems generated by users in the process of using the target service; then associates the R&D environment information of the target service with the application environment information of the target service to determine the correlation between the environment information and the cause of the unresolved problem; according to the correlation and the closed-loop management rules of the unresolved problems based on FRACAS, the analysis feedback rule model of the unresolved problem is determined; finally, the problem information of the unresolved problem is input into the analysis feedback rule model to determine the closed-loop analysis result of the unresolved problem. Based on this, from problem discovery to problem solving to feedback and improvement, a continuous cycle is repeated to continuously improve the reliability of the target service and user satisfaction.

[0069] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to implement the steps in the above method embodiment when running.

[0070] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps: S301: Collecting unresolved issues that arise when users use the target service; S302: Associating the R&D environment information of the target service with the application environment information of the target service, and determining the association relationship between the environment information and the cause of the problem to be solved; S303: Determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rule for the problem to be solved based on FRACAS; S304: Input the problem information of the problem to be solved into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

[0071] Specifically, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0072] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in the above method embodiment.

[0073] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0074] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program: S301: Collecting unresolved issues that arise when users use the target service; S302: Associating the R&D environment information of the target service with the application environment information of the target service, and determining the association relationship between the environment information and the cause of the problem to be solved; S303: Determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rule for the problem to be solved based on FRACAS; S304: Input the problem information of the problem to be solved into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

[0075] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0076] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0078] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0080] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0081] The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A closed-loop problem management system based on FRACAS, characterized in that: Applied to the software product quality and digital business experience collaborative management platform, the system includes: Communication connection problem collection module, problem analysis module, closed-loop measures formulation module, closed-loop measures implementation module and effect evaluation module, among which, The problem collection module is used to collect unresolved issues that users have when using the target service; The problem analysis module is used to receive the problem information to be solved provided by the problem collection module, and perform in-depth analysis of the problem information to be solved; wherein, the in-depth analysis of the problem information to be solved includes: associating the R&D environment information of the target service with the application environment information of the target service to determine the correlation relationship between the environment information and the cause of the problem to be solved; The closed-loop measure formulation module is used to determine the closed-loop measure scheme corresponding to the problem to be solved according to the in-depth analysis results of the problem information; wherein the closed-loop measure scheme is determined according to the association relationship and the analysis feedback rule model determined by the closed-loop management rules of the problem to be solved based on FRACAS; The closed-loop measure implementation module is used to execute corrective measures for the problem to be solved according to the closed-loop measure solution corresponding to the problem to be solved; The effect evaluation module is used to provide feedback and evaluation on the implementation effect of the corrective measures to be solved after the corrective measures are completed.

2. The problem closed-loop management system based on FRACAS according to claim 1 is characterized in that: The problem collection module includes: A problem data collection unit and a problem data classification unit, wherein: The problem data collection unit is used to collect problem data from the target service monitoring device and / or user reports in real time or regularly during the use of the target service; The problem data classification unit is used to classify and preprocess the collected problem data using a predefined fault model, knowledge base and reasoning algorithm.

3. The problem closed-loop management system based on FRACAS according to claim 2 is characterized in that: The problem analysis module comprises: An environmental data association unit and an environmental data analysis model unit, wherein: The environment data association unit is used to perform feature fusion of environment data information according to the environment data fusion technology, and associate the research and development environment information of the target service with the application environment information of the target service; The environmental data analysis model unit is used to process the correlation between the environmental information after feature fusion and the cause of the problem to be solved according to a preset data analysis model.

4. The problem closed-loop management system based on FRACAS according to claim 3 is characterized in that: The closed-loop measures formulation module includes: Closed-loop measures planning unit, closed-loop measures verification unit and closed-loop measures generation unit, wherein: The closed-loop measures planning unit is used to plan initial corrective measures based on the cause analysis results of the problem to be solved; The closed-loop measure verification unit is used to simulate and verify the formulated initial corrective measures and evaluate the implementation effect; The closed-loop measure generation unit is used to determine the target corrective measures after the simulation evaluation based on the analysis feedback rule model of the closed-loop management rules of the problem to be solved in FRACAS.

5. The problem closed-loop management system based on FRACAS according to claim 4 is characterized in that: The effect evaluation module includes: The feedback evaluation effect closed-loop management unit is used to obtain the evaluation effect closed-loop management test process, verify the target service through the test process, obtain the closed-loop management information of the target service, and generate a closed-loop evaluation report in a specified format based on the closed-loop management information.

6. A software product quality and digital business experience collaborative management platform, characterized in that: The platform includes: At least one of a target service R&D management system and a target service application environment management system, and a FRACAS-based problem closed-loop management system as claimed in any one of claims 1 to 5; The target service R&D management system is used to provide R&D environment information to the FRACAS-based problem closed-loop management system through a preset target service development port; The target service application environment management system is used to provide a closed-loop management test process to the effect evaluation module of the FRACAS-based problem closed-loop management system through a preset application environment management interface.

7. A closed-loop problem management method based on FRACAS, characterized in that: The method comprises: Collect unresolved issues that users have when using the target service; Correlate the R&D environment information of the target service with the application environment information of the target service, and determine the correlation between the environment information and the cause of the problem to be solved; Determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rules for the problem to be solved based on FRACAS; The problem information of the problem to be solved is input into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

8. A closed-loop problem management device based on FRACAS, characterized in that: The device comprises: A collection module is used to collect unresolved issues that users have when using the target service; The first determination module is used to associate the R&D environment information of the target service with the application environment information of the target service, and determine the association relationship between the environment information and the cause of the problem to be solved; A second determination module is used to determine an analysis feedback rule model for the problem to be solved according to the association relationship and the closed-loop management rules for the problem to be solved based on FRACAS; The third determination module is used to input the problem information of the problem to be solved into the analysis feedback rule model to determine the closed-loop analysis result of the problem to be solved.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to implement the method described in claim 7 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the computer program to implement the method described in claim 7.

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