CN-121996451-A - Data backtracking method, device, storage medium and program product

CN121996451ACN 121996451 ACN121996451 ACN 121996451ACN-121996451-A

Abstract

The application provides a data backtracking method, equipment, a storage medium and a program product, wherein the method comprises the steps of collecting and storing CAN data of a vehicle and middleware data generated when service logic is executed by using the CAN data; if the execution process of the business logic is abnormal, backtracking analysis is carried out on the execution process of the business logic according to the business logic, the CAN data and the middleware data to obtain a backtracking result, and the backtracking result is analyzed according to a preset rule to determine the reason of the abnormal execution process of the business logic. According to the embodiment of the application, the CAN data and the middleware data generated when the service logic is executed by utilizing the CAN data are collected and stored in real time, so that backtracking analysis CAN be directly carried out according to the reliable CAN data and the middleware data, and the efficiency and the accuracy of the service logic anomaly analysis are obviously improved.

Inventors

WU QIMENG
XIANG JIAYONG
YANG JIAWEI
YANG SIYUAN
GUO YI

Assignees

联通智网科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20251215

Claims (10)

1. A data backtracking method, comprising: Collecting and storing CAN data of a vehicle and middleware data generated when service logic is executed by using the CAN data; if the execution process of the business logic is abnormal, performing backtracking analysis on the execution process of the business logic according to the business logic, the CAN data and the middleware data to obtain a backtracking result; And analyzing the backtracking result according to a preset rule, and determining the reason for the abnormality in the execution process of the business logic.
2. The method of claim 1, wherein the method comprises the steps of, The data structure of the CAN data comprises a vehicle identification field, a time stamp field and a data content field; The data structure of the middleware data includes a vehicle identification field, a time stamp field, and a data content field.
3. The method of claim 1, wherein the performing backtracking analysis on the execution of the service logic according to the service logic, the CAN data and the middleware data to obtain a backtracking result comprises: acquiring a logic entity list corresponding to the business logic, and middleware access entities and variable entities corresponding to each logic entity in the logic entity list; And carrying out backtracking analysis on the execution process of the business logic according to the logic entity list, the middleware access entity and variable entity corresponding to each logic entity in the logic entity list, the CAN data and the middleware data to obtain a backtracking result.
4. The method of claim 3, wherein the obtaining the logical entity list corresponding to the service logic includes: acquiring a first logic entity corresponding to the business logic; determining a second logic entity according to the prepositions of the first logic entity; And combining the first logic entity with the second logic entity to obtain a logic entity list corresponding to the service logic.
5. The method of claim 3, wherein obtaining the middleware access entity and the variable entity corresponding to each logical entity in the logical entity list comprises: Acquiring middleware access entities and variable entities corresponding to each logic entity in the logic entity list according to the dependency relationship of each logic entity in the logic entity list; and acquiring a variable entity corresponding to each logic entity in the logic entity list according to the inclusion relation of each logic entity in the logic entity list.
6. The method of claim 3, wherein performing backtracking analysis on the execution process of the service logic according to the service logic, the CAN data and the middleware data to obtain a backtracking result comprises: Generating a backtracking script according to the logic entity list, the middleware access entity corresponding to each logic entity in the logic entity list and the variable entity; Filling the backtracking script according to the CAN data and the middleware data to generate an executable backtracking script; And running the executable backtracking script to obtain a backtracking result.
7. The method of claim 1, wherein the analyzing the backtracking result according to the preset rule to determine the cause of the abnormality in the execution process of the business logic includes: And inputting the backtracking result into a large language model, analyzing the backtracking result by the large language model according to the preset rule, and outputting the reason of the abnormality in the execution process of the business logic.
8. An electronic device, comprising: A processor; A memory; And a computer program, wherein the computer program is stored in the memory, which when executed by the processor, causes the electronic device to perform the method of any one of claims 1 to 7.
9. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 7.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method of any one of claims 1 to 7.

Description

Data backtracking method, device, storage medium and program product Technical Field The present application relates to the field of data processing technologies, and in particular, to a data backtracking method, device, storage medium, and program product. Background With the rapid development of the internet of vehicles technology, remote real-time monitoring, fault diagnosis and data management of vehicles have become keys for guaranteeing the running safety of the vehicles and improving the running and maintenance efficiency. In practical application, the vehicle-mounted remote processing terminal (such as TBox) is used as a bridge between the vehicle and the cloud platform, is responsible for collecting operation data of the vehicle bottom layer through a controller area network (Controller Area Network, CAN) protocol, and sends the operation data to the remote monitoring platform (Remote Telemetry Monitoring, RTM) through the wireless communication module. The RTM platform is responsible for performing service logic processing (such as parsing, processing, storing, forwarding, etc.) on the collected CAN data, so as to implement functions such as vehicle status monitoring, fault early warning, and remote diagnosis. In the related art, when the abnormality such as message loss, unrecognized alarm, failure in data analysis and the like occurs in the monitoring process, CAN data of a target vehicle is usually screened from a history log to check the integrity and the effectiveness of data acquisition, and meanwhile, middleware data when a monitoring platform executes service logic by using the CAN data is also required to be called to accurately judge the cause of the abnormality. However, the middleware data is continuously updated in the execution process of the service logic, when one service logic is executed, the middleware data corresponding to the CAN data triggering the logic is likely to be covered by the subsequent service request, and only the middleware data CAN be reversely pushed in the process of exception analysis, so that the reliability is lower, and the accuracy and the efficiency of exception analysis are seriously affected. It should be noted that the information disclosed in the background section of the present application is only for enhancement of understanding of the general background of the present application and should not be taken as an admission or any form of suggestion that this information forms the prior art that is well known to a person skilled in the art. Disclosure of Invention The application provides a data backtracking method, equipment, a storage medium and a program product, which are beneficial to solving the problems of lower accuracy and efficiency in business logic anomaly analysis caused by lack of reliable middleware data in the prior art. In a first aspect, an embodiment of the present application provides a data backtracking method, including: Collecting and storing CAN data of a vehicle and middleware data generated when service logic is executed by using the CAN data; if the execution process of the business logic is abnormal, performing backtracking analysis on the execution process of the business logic according to the business logic, the CAN data and the middleware data to obtain a backtracking result; And analyzing the backtracking result according to a preset rule, and determining the reason for the abnormality in the execution process of the business logic. In one possible implementation of the present invention, The data structure of the CAN data comprises a vehicle identification field, a time stamp field and a data content field; The data structure of the middleware data includes a vehicle identification field, a time stamp field, and a data content field. In one possible implementation manner, the performing backtracking analysis on the execution process of the service logic according to the service logic, the CAN data and the middleware data to obtain a backtracking result includes: acquiring a logic entity list corresponding to the business logic, and middleware access entities and variable entities corresponding to each logic entity in the logic entity list; And carrying out backtracking analysis on the execution process of the business logic according to the logic entity list, the middleware access entity and variable entity corresponding to each logic entity in the logic entity list, the CAN data and the middleware data to obtain a backtracking result. In one possible implementation manner, the obtaining the logical entity list corresponding to the service logic includes: acquiring a first logic entity corresponding to the business logic; determining a second logic entity according to the prepositions of the first logic entity; And combining the first logic entity with the second logic entity to obtain a logic entity list corresponding to the service logic. In one possible implementation manner, obtaining the middleware access entity a