WO2025232323A1 - System anomaly diagnosis method and apparatus, storage medium, and electronic device - Google Patents

Abstract

The present application relates to the technical field of system anomaly processing, and discloses a system anomaly diagnosis method and apparatus, a storage medium, and an electronic device. Upon detecting, by means of a cross-process communication service, anomaly information sent by a target subsystem, a message processing thread is distributed; the anomaly information is received by means of the message processing thread and distributed to a corresponding subsystem agent; and anomaly joint diagnosis is performed by means of the subsystem agent in conjunction with subsystem agents of other subsystems. The present application improves the reliability of anomaly diagnosis in systems.

Description

System anomaly diagnosis methods, devices, storage media and electronic equipment

This application claims priority to Chinese Patent Application No. 202410559269.7, filed on May 7, 2024, entitled "System Anomaly Diagnosis Method, Apparatus, Storage Medium and Electronic Equipment", the entire contents of which are incorporated herein by reference.

Technical Field

This application relates to the field of system anomaly handling technology, specifically to a system anomaly diagnosis method, device, storage medium, and electronic device.

Background Technology

Taking Android as an example, the system is widely used in various industries. When anomalies occur in the system, timely and reliable detection is usually required to carry out relevant processing to ensure system stability.

Technical issues

Current methods for diagnosing system anomalies typically involve diagnosing an anomaly individually, which results in low reliability and makes it difficult to guarantee system stability.

Technical solutions

This application provides a system anomaly diagnosis scheme that enables rapid connection of subsystems within the system and joint anomaly diagnosis of multiple subsystems with low performance overhead, effectively improving the reliability of anomaly diagnosis and reliably ensuring system stability.

The embodiments of this application provide the following technical solutions:

According to one embodiment of this application, a system anomaly diagnosis method is provided. The system includes multiple subsystems and an anomaly diagnosis framework. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems. The method is applied to the anomaly diagnosis framework and includes: in response to detecting anomaly information sent by a target subsystem in the multiple subsystems through the inter-process communication service, distributing a corresponding message processing thread; receiving the anomaly information through the message processing thread and distributing the anomaly information to the subsystem agent corresponding to the target subsystem; and performing joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem, in conjunction with the subsystem agents corresponding to other subsystems in the multiple subsystems, to obtain a joint anomaly diagnosis result.

In some embodiments of this application, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain joint anomaly diagnosis results, the method further includes: making joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and performing joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy.

In some embodiments of this application, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, the method further includes: detecting whether the subsystems in the multiple subsystems have connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; if the subsystems in the multiple subsystems are detected to have connected to the abnormal diagnosis framework, creating a subsystem agent corresponding to the subsystem in the multiple subsystems.

In some embodiments of this application, the step of performing joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem, in conjunction with the subsystem agents corresponding to other subsystems in the plurality of subsystems, to obtain a joint anomaly diagnosis result includes: performing anomaly diagnosis through the subsystem agent corresponding to the target subsystem based on the anomaly information to obtain a first anomaly diagnosis result; if the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, then sending a collaborative diagnosis message to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; performing anomaly diagnosis through the subsystem agent corresponding to the first joint subsystem to obtain a second anomaly diagnosis result; and obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result.

In some embodiments of this application, obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result includes: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then sending a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; performing anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result.

In some embodiments of this application, the method further includes: transmitting anomaly-related data to a preset reporting service, the preset reporting service being used to report the anomaly-related data to a cloud server; and receiving anomaly repair content transmitted from the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device.

In some embodiments of this application, the anomaly diagnosis framework further includes a framework performance self-test module; the method further includes: acquiring anomaly diagnosis processing related data in the system; and analyzing the anomaly diagnosis processing related data through the framework performance self-test module to obtain the framework performance in the anomaly diagnosis framework.

According to one embodiment of this application, a system anomaly diagnosis device is provided. The system includes multiple subsystems and an anomaly diagnosis framework. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems. The device is applied to the anomaly diagnosis framework and includes: a connection processing module, configured to distribute a corresponding message processing thread in response to detecting anomaly information sent by a target subsystem in the multiple subsystems through the inter-process communication service; a data distribution module, configured to receive the anomaly information through the message processing thread and distribute the anomaly information to the subsystem agent corresponding to the target subsystem; and a joint diagnosis module, configured to perform joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem and in conjunction with the subsystem agents corresponding to other subsystems in the multiple subsystems, to obtain a joint anomaly diagnosis result.

In some embodiments of this application, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain joint anomaly diagnosis results, the device further includes an anomaly repair module, used to: make joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and perform joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy.

In some embodiments of this application, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, the device further includes a proxy creation module, configured to: detect whether a subsystem in the multiple subsystems has connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; if a subsystem in the multiple subsystems is detected to have connected to the abnormal diagnosis framework, create a subsystem proxy corresponding to the subsystem in the multiple subsystems.

In some embodiments of this application, the joint diagnosis module is configured to: perform anomaly diagnosis based on the anomaly information through the subsystem agent corresponding to the target subsystem to obtain a first anomaly diagnosis result; if the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the first joint subsystem to obtain a second anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result.

In some embodiments of this application, the joint diagnosis module is configured to: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result.

In some embodiments of this application, the device further includes a data reporting module, configured to: transmit anomaly-related data to a preset reporting service, the preset reporting service being configured to report the anomaly-related data to a cloud server; and receive anomaly repair content transmitted from the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device.

In some embodiments of this application, the anomaly diagnosis framework further includes a framework performance self-testing module; the framework performance self-testing module is used to: acquire anomaly diagnosis and processing related data in the system; and analyze the anomaly diagnosis and processing related data through the framework performance self-testing module to obtain the framework performance in the anomaly diagnosis framework.

According to another embodiment of this application, a storage medium stores a computer program thereon, which, when executed by a computer's processor, causes the computer to perform the methods described in the embodiments of this application.

According to another embodiment of this application, an electronic device may include: a memory storing a computer program; and a processor reading the computer program stored in the memory to execute the methods described in the embodiments of this application.

According to another embodiment of this application, a computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described in the embodiments of this application.

Beneficial effects

In the system anomaly diagnosis method of this application embodiment, the system includes multiple subsystems and an anomaly diagnosis framework. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems. The method is applied to the anomaly diagnosis framework and includes: in response to detecting anomaly information sent by a target subsystem in the multiple subsystems through the inter-process communication service, distributing a corresponding message processing thread; receiving the anomaly information through the message processing thread and distributing the anomaly information to the subsystem agent corresponding to the target subsystem; and performing joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem, in conjunction with the subsystem agents corresponding to other subsystems in the multiple subsystems, to obtain a joint anomaly diagnosis result.

In this way, an anomaly diagnosis framework is configured in the system. The framework includes an inter-process communication service and subsystem agents corresponding to each subsystem. In response to anomaly information detected by the inter-process communication service from a target subsystem in multiple subsystems, the framework quickly distributes the corresponding message processing thread to receive and distribute the anomaly information. This allows for rapid connection between the subsystems. Furthermore, through the subsystem agent corresponding to the target subsystem, it quickly links with the subsystem agents corresponding to other subsystems in multiple subsystems to perform joint anomaly diagnosis. This allows for the combined capabilities of multiple subsystems to accurately obtain joint anomaly diagnosis results. Overall, it can achieve rapid connection of subsystems in the system and joint anomaly diagnosis with multiple subsystems under low performance overhead, effectively improving the reliability of anomaly diagnosis in the system and reliably ensuring system stability.

Attached Figure Description

To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

Figure 1 shows a flowchart of a system anomaly diagnosis method according to an embodiment of this application.

Figure 2 shows a flowchart of a subsystem agent creation process according to an embodiment of this application.

Figure 3 shows a flowchart of a system anomaly joint diagnosis according to an embodiment of this application.

Figure 4 shows a block diagram of a system anomaly diagnosis device according to an embodiment of this application.

Figure 5 shows a block diagram of an electronic device according to an embodiment of this application.

Implementation methods of this application

The present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the embodiments provided herein are merely illustrative of the present disclosure and are not intended to limit the present disclosure. Furthermore, the embodiments provided below are some embodiments for implementing the present disclosure, and not all embodiments for implementing the present disclosure. Unless otherwise specified, the technical solutions described in the embodiments of the present disclosure can be implemented in any combination.

It should be noted that, in the embodiments of this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a method or apparatus that includes a list of elements includes not only the elements expressly described, but also other elements not expressly listed, or elements inherent to implementing the method or apparatus. Without further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of other related elements (e.g., steps in the method or units in the apparatus, such as portions of circuitry, processors, programs, or software, etc.) in the method or apparatus that includes that element.

For example, the system anomaly diagnosis method provided in this disclosure includes a series of steps, but the system anomaly diagnosis method provided in this disclosure is not limited to the steps described. Similarly, the system anomaly diagnosis device provided in this disclosure includes a series of units, but the device provided in this disclosure is not limited to the units explicitly described, but may also include units that need to be set up for obtaining relevant information or processing based on information.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure.

Figure 1 schematically illustrates a flowchart of a system anomaly diagnosis method according to an embodiment of this application. The subject executing this system anomaly diagnosis method can be any device with processing capabilities, such as a television, computer, mobile phone, smartwatch, and home appliance.

The device can install a system, which includes multiple subsystems and an anomaly diagnosis framework. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems. The method can be applied to the anomaly diagnosis framework.

As shown in Figure 1, the abnormal diagnosis method of this system may include steps S110 to S130.

Step S110: In response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, a corresponding message processing thread is distributed; Step S120: The abnormal information is received through the message processing thread and distributed to the subsystem agent corresponding to the target subsystem; Step S130: The subsystem agent corresponding to the target subsystem, together with the subsystem agents corresponding to other subsystems in the multiple subsystems, performs joint abnormal diagnosis to obtain a joint abnormal diagnosis result.

The system includes at least multiple subsystems and an anomaly diagnosis framework. These subsystems may include, for example, wireless network (Wi-Fi), audio, Bluetooth, multimedia, and kernel subsystems, which can reside at the native layer, system layer, or application layer. The anomaly diagnosis framework is used to jointly diagnose anomalies across these multiple subsystems; this framework can reside at the native layer.

The anomaly diagnosis framework can include pre-created or dynamically created cross-process communication services such as UnixDomainSocket Server or AIDL Service. This framework can monitor messages or data sent by multiple subsystems across processes using these services. Furthermore, in response to anomaly information detected by the cross-process communication service from a target subsystem (which can be any one of the multiple subsystems), the framework can immediately dispatch the corresponding message processing thread of the target subsystem to receive and distribute the anomaly information, thus enabling the framework to quickly connect to that target subsystem. Since the target subsystem can be any one of the multiple subsystems, the framework can quickly connect to any subsystem within the entire network.

The anomaly diagnosis framework can also create subsystem agents corresponding to each subsystem. Subsystem agents can obtain data from the corresponding subsystem and agent modules with the corresponding subsystem's anomaly repair capabilities. Subsystem agents can interact with each other through messages to collaboratively perform anomaly diagnosis.

The anomaly diagnosis framework can receive anomaly information through a message processing thread and distribute the anomaly information to the subsystem agent corresponding to the target subsystem. Through the subsystem agent corresponding to the target subsystem, it can perform joint anomaly diagnosis in conjunction with the subsystem agents corresponding to other subsystems in multiple subsystems, thereby accurately obtaining the joint anomaly diagnosis results.

In this way, based on steps S110 to S130, an anomaly diagnosis framework is configured in the system. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each subsystem. In response to anomaly information sent by a target subsystem in multiple subsystems detected through the inter-process communication service, the anomaly diagnosis framework can quickly distribute the corresponding message processing thread to receive and distribute the anomaly information, thereby quickly connecting each subsystem. Furthermore, through the subsystem agent corresponding to the target subsystem, it can quickly link with the subsystem agents corresponding to other subsystems in multiple subsystems to perform joint anomaly diagnosis. It can combine the capabilities of multiple subsystems to perform joint anomaly diagnosis and accurately obtain the joint anomaly diagnosis result. Overall, it can quickly connect the subsystems in the system and combine the capabilities of multiple subsystems to perform joint anomaly diagnosis with low performance overhead, effectively improving the reliability of anomaly diagnosis in the system and reliably ensuring system stability.

The following describes further optional embodiments of the steps performed during system anomaly diagnosis in the embodiment shown in Figure 1.

In one embodiment, referring to FIG2, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, the method further includes: step S210, detecting whether the subsystems in the multiple subsystems have connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; step S220, if it is detected that the subsystems in the multiple subsystems have connected to the abnormal diagnosis framework, creating a subsystem agent corresponding to the subsystem in the multiple subsystems.

The anomaly diagnosis framework encapsulates connection interfaces, which are used by subsystems to access the anomaly diagnosis framework. These connection interfaces are Software Development Kit (SDK) interfaces (APIs), which can include application (APP), system, and kernel SDK interfaces. Thus, each subsystem can access the anomaly diagnosis framework through these connection interfaces.

The anomaly diagnosis framework can detect whether a subsystem in multiple subsystems has connected to the anomaly diagnosis framework through an encapsulated connection interface. If a subsystem is detected to have connected to the anomaly diagnosis framework through an encapsulated connection interface, the anomaly diagnosis framework can create a subsystem agent corresponding to that subsystem. Through the subsystem agent, the data of that subsystem and its anomaly repair capabilities can be obtained.

For example, after the Media, Audio, and Wi-Fi subsystems connect to the anomaly diagnosis framework through the connection interface, the anomaly diagnosis framework can create subsystem agents corresponding to these three subsystems. The anomaly diagnosis framework can then obtain the data of these three subsystems and their anomaly repair capabilities through the subsystem agents.

In one embodiment, referring to Figure 3, the step of performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain the joint anomaly diagnosis result may specifically include:

Step S310: The subsystem agent corresponding to the target subsystem performs anomaly diagnosis based on the anomaly information to obtain a first anomaly diagnosis result; Step S320: If the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, a collaborative diagnosis message is sent to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; Step S330: The subsystem agent corresponding to the first joint subsystem performs anomaly diagnosis to obtain a second anomaly diagnosis result; Step S340: The joint anomaly diagnosis result is obtained based on the first anomaly diagnosis result and the second anomaly diagnosis result.

First, the subsystem agent corresponding to the target subsystem can perform anomaly diagnosis based on the anomaly information to obtain the first anomaly diagnosis result.

For example, taking the Media subsystem as the target subsystem, when a user launches a video-on-demand (VOD) application, the Media subsystem detects buffering, playback, stuttering, and audio-visual synchronization information. When a monitoring point in the Media subsystem detects an anomaly, it sends the anomaly information to the anomaly diagnosis framework through a specific channel (a channel used by the subsystem to send anomaly information to the anomaly diagnosis framework). After the anomaly diagnosis framework detects the anomaly information sent by the target subsystem through the inter-process communication service, it can immediately dispatch the message processing thread corresponding to the target subsystem to receive the anomaly information. The message processing thread then distributes the anomaly information to the Media subsystem's corresponding Media subsystem agent, which in turn obtains the anomaly information.

Taking the abnormal information as stuttering and audio-visual desynchronization as an example, the Media subsystem agent inside the abnormal diagnosis framework can analyze and diagnose the abnormal information, and obtain the first abnormal diagnosis result as "the video axis and audio axis cannot be associated, and a data buffering problem caused by insufficient playback buffer is found".

Furthermore, the subsystem agent corresponding to the target subsystem determines whether collaborative diagnosis by other first joint subsystems is required based on the first anomaly diagnosis result. If so, a collaborative diagnosis message is sent from the subsystem agent corresponding to the target subsystem to the subsystem agent corresponding to the first joint subsystem. The first joint subsystem includes one or more subsystems from multiple subsystems within the system, excluding the target subsystem. Specifically, the subsystem agent corresponding to the target subsystem determines the first joint subsystem based on the first anomaly diagnosis result by: querying the first anomaly category corresponding to the first anomaly diagnosis result from a preset diagnosis table, and further querying the first joint subsystem corresponding to that first anomaly category from the preset diagnosis table. The preset diagnosis table may include preset anomaly categories corresponding to different anomaly diagnosis results and joint subsystems corresponding to different anomaly categories. The preset diagnosis table may be configured within the anomaly diagnosis framework, and the subsystem agent corresponding to the target subsystem can obtain the preset diagnosis table from the anomaly diagnosis framework.

Taking the first anomaly diagnosis result as "the picture axis and audio axis cannot be associated, and data caused by insufficient playback buffer is found", the Media subsystem agent of the Media subsystem can query the preset diagnosis table to find that the first anomaly category corresponding to the first anomaly diagnosis result is "Category 1". The joint subsystems corresponding to "Category 1" in the preset diagnosis table include the Wi-Fi subsystem and the Audio subsystem. Therefore, the Media subsystem agent can further determine that other first joint subsystems need to perform collaborative diagnosis, and the first joint subsystems specifically include the Wi-Fi subsystem and the Audio subsystem.

Furthermore, after receiving the collaborative diagnostic message, the subsystem agent corresponding to the first joint subsystem in the anomaly diagnosis framework can perform further anomaly diagnosis to obtain a second anomaly diagnosis result. For example, the Wi-Fi subsystem agent can combine the Wi-Fi diagnosis subsystem to diagnose the Wi-Fi situation, confirming the Wi-Fi hardware status, network connection status, network connection quality, etc., thereby obtaining the diagnostic result for the Wi-Fi module; the Audio subsystem agent can combine Media keyframe data to perform audio-visual analysis, such as analyzing Media decoding efficiency and Audio decoding efficiency, to obtain the diagnostic result for the Audio module. Therefore, the second anomaly diagnosis result can include the diagnostic results for both the Wi-Fi module and the Audio module.

Furthermore, the subsystem agent corresponding to the target subsystem in the anomaly diagnosis framework can obtain the first and second anomaly diagnosis results. The set of the first and second anomaly diagnosis results can be used as the joint anomaly diagnosis result. In this way, this joint diagnosis mechanism can quickly link multiple systems to obtain accurate joint anomaly diagnosis results, ensuring the reliability of system anomaly diagnosis. At the same time, based on the joint anomaly diagnosis result, system anomalies can be reliably repaired, ensuring system operational stability.

Furthermore, in one embodiment, obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result may include: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then sending a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; performing anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result.

If the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then a collaborative diagnosis message is sent to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem. Specifically, the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result by: querying the second anomaly category corresponding to the second anomaly diagnosis result from a preset diagnosis table, and further querying the second joint subsystem corresponding to the second anomaly category from the preset diagnosis table. The preset diagnosis table may include preset anomaly categories corresponding to different anomaly diagnosis results and joint subsystems corresponding to different anomaly categories. The preset diagnosis table may be configured in the anomaly diagnosis framework, and the subsystem agent corresponding to the first joint subsystem can obtain the preset diagnosis table from the anomaly diagnosis framework.

For example, the Wi-Fi subsystem agent can query the pre-defined diagnostic table to find that the diagnostic result of the Wi-Fi module (belonging to the second abnormal diagnostic result) corresponds to the second abnormal category "Category 2-1". If the joint subsystem corresponding to "Category 2-1" in the pre-defined diagnostic table is the kernel subsystem, then the Wi-Fi subsystem agent can determine that the second joint subsystem is the kernel subsystem. The Wi-Fi subsystem agent can further send a collaborative diagnostic message to the subsystem agent of the kernel subsystem.

After receiving the collaborative diagnostic message, the subsystem agent corresponding to the second joint subsystem performs anomaly diagnosis and obtains a third anomaly diagnosis result. For example, the subsystem agent of the kernel subsystem can check memory, CPU, and other conditions to perform diagnosis and obtain a third anomaly diagnosis result. The subsystem agent corresponding to the second joint subsystem can further feed back the third anomaly diagnosis result to the subsystem agent corresponding to the target subsystem.

Furthermore, the subsystem agent corresponding to the target subsystem in the anomaly diagnosis framework can obtain the first, second, and third anomaly diagnosis results. The set of these three results can serve as the joint anomaly diagnosis result. This joint diagnosis mechanism allows for rapid linkage of multiple systems to obtain accurate joint anomaly diagnosis results, ensuring the reliability of system anomaly diagnosis. Simultaneously, based on this joint anomaly diagnosis result, system anomalies can be reliably repaired, ensuring system operational stability. Similarly, the anomaly diagnosis framework can rapidly link multiple subsystem agents for multi-subsystem joint diagnosis.

Furthermore, in one embodiment, after performing joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem and in conjunction with the subsystem agents corresponding to other subsystems in the plurality of subsystems to obtain joint anomaly diagnosis results, the method further includes: making joint anomaly repair decisions for the plurality of subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and performing joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy.

Based on the joint diagnosis results of anomalies, a joint repair strategy for multiple subsystems is obtained by making joint repair decisions for multiple subsystems. The joint repair of anomalies in multiple subsystems based on the joint repair strategy can effectively improve the reliability of anomaly repair.

The specific method for making joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy may include: extracting abnormal issues from the joint anomaly diagnosis results; if at least two abnormal issues are extracted, prioritizing the at least two abnormal issues to obtain the anomaly handling priority for each abnormal issue, and the multi-subsystem joint repair strategy is to perform anomaly repair according to the anomaly handling priority. Specifically, the step of prioritizing the at least two abnormal issues to obtain the anomaly handling priority for each abnormal issue may include: querying the anomaly handling priority of each extracted abnormal issue from a preset priority table, wherein the preset priority table includes pre-defined anomaly handling priorities for different abnormal issues, and the preset priority table can be pre-configured in the anomaly diagnosis framework.

Specifically, an anomaly may be caused by anomalies in multiple subsystems. Without a joint anomaly repair decision for these subsystems to arrive at a multi-subsystem joint repair strategy, functional conflicts may arise from different subsystems calling the final anomaly repair capabilities, leading to inaccurate anomaly repair. For example, in one scenario, the joint anomaly diagnosis results include the Media subsystem agent detecting insufficient CPU, the Wi-Fi subsystem agent also detecting insufficient CPU, and the kernel subsystem agent detecting insufficient CPU due to I/O. Two anomalies can be extracted: "I/O problem" and "Insufficient CPU." For the "Insufficient CPU" problem, the Media and Wi-Fi subsystem agents can request CPU scheduling to repair it. However, if the "I/O problem" is not addressed first, and CPU scheduling is requested only, the lag will worsen. By making a joint anomaly repair decision based on the joint anomaly diagnosis results for multiple subsystems, a multi-subsystem joint repair strategy (which repairs anomalies according to the aforementioned anomaly handling priority) can prioritize addressing the I/O problem before requesting CPU scheduling, thereby effectively improving the reliability of anomaly repair.

In a further embodiment, the method further includes: transmitting anomaly-related data to a preset reporting service, the preset reporting service being used to report the anomaly-related data to a cloud server; and receiving anomaly repair content transmitted from the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device.

The anomaly diagnosis framework transmits anomaly-related data to a pre-defined reporting service (such as a pre-defined reporting application). This service then reports the anomaly-related data to the cloud server. The anomaly diagnosis framework resides in the native layer and transmits data to the pre-defined reporting service (such as a pre-defined reporting application) for network reporting. Because of limitations in the system layer, native layer, and app scheduling, reporting through the pre-defined reporting service bypasses these limitations and enables rapid data reporting through mechanisms such as the log system.

Furthermore, the anomaly diagnosis framework can receive anomaly repair content transmitted from the device. Specifically, this anomaly repair content can be generated by a cloud server based on anomaly-related data analysis and transmitted to the device. This anomaly repair content can be used in the anomaly diagnosis framework to make joint anomaly repair decisions, thereby further improving the reliability of anomaly repair.

In some implementations, the anomaly diagnosis framework makes joint anomaly repair decisions based on a repair knowledge graph. The anomaly diagnosis framework can further adjust the repair knowledge graph based on the received anomaly repair content, and make joint anomaly repair decisions based on the adjusted repair knowledge graph to obtain a multi-subsystem joint repair strategy.

Furthermore, the anomaly diagnosis framework also includes a framework performance self-test module; the method further includes: acquiring anomaly diagnosis and processing related data in the system; and analyzing the anomaly diagnosis and processing related data through the framework performance self-test module to obtain the framework performance in the anomaly diagnosis framework.

The anomaly diagnosis framework is configured with a framework performance self-test module. This module can acquire relevant data on anomaly diagnosis and processing in the system, analyze the data, and obtain the framework performance of the anomaly diagnosis framework. This enables the anomaly diagnosis framework to self-test its performance. Based on the test results, corresponding processing can be performed to further improve the framework performance of the anomaly diagnosis framework.

For example, the framework performance self-test module may include units such as the data entry performance test unit, the data accuracy test unit, the subsystem diagnosis test unit, and the subsystem repair test unit. In the anomaly diagnosis framework, the subsystem diagnosis test unit can self-test its anomaly diagnosis performance, and the subsystem repair test unit can self-test its anomaly repair performance.

To facilitate better implementation of the system anomaly diagnosis method provided in the embodiments of this application, the embodiments of this application also provide a system anomaly diagnosis device based on the above-described system anomaly diagnosis method. The meanings of the terms used are the same as in the above-described system anomaly diagnosis method, and specific implementation details can be found in the descriptions in the method embodiments. Figure 4 shows a block diagram of a system anomaly diagnosis device according to an embodiment of this application.

As shown in Figure 4, a system anomaly diagnosis device 400 is provided. The system includes multiple subsystems and an anomaly diagnosis framework. The anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems. The device is applied to the anomaly diagnosis framework. The system anomaly diagnosis device 400 may include: a connection processing module 410, which can be used to distribute corresponding message processing threads in response to anomaly information sent by a target subsystem in the multiple subsystems detected through the inter-process communication service; a data distribution module 420, which can be used to receive the anomaly information through the message processing threads and distribute the anomaly information to the subsystem agent corresponding to the target subsystem; and a joint diagnosis module 430, which can be used to perform joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem and in conjunction with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain a joint anomaly diagnosis result.

In some embodiments of this application, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain joint anomaly diagnosis results, the device further includes an anomaly repair module, used to: make joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and perform joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy.

In some embodiments of this application, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, the device further includes a proxy creation module, configured to: detect whether a subsystem in the multiple subsystems has connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; if a subsystem in the multiple subsystems is detected to have connected to the abnormal diagnosis framework, create a subsystem proxy corresponding to the subsystem in the multiple subsystems.

In some embodiments of this application, the joint diagnosis module is configured to: perform anomaly diagnosis based on the anomaly information through the subsystem agent corresponding to the target subsystem to obtain a first anomaly diagnosis result; if the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the first joint subsystem to obtain a second anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result.

In some embodiments of this application, the joint diagnosis module is configured to: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result.

In some embodiments of this application, the device further includes a data reporting module, configured to: transmit anomaly-related data to a preset reporting service, the preset reporting service being configured to report the anomaly-related data to a cloud server; and receive anomaly repair content transmitted from the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device.

In some embodiments of this application, the anomaly diagnosis framework further includes a framework performance self-testing module; the framework performance self-testing module is used to: acquire anomaly diagnosis and processing related data in the system; and analyze the anomaly diagnosis and processing related data through the framework performance self-testing module to obtain the framework performance in the anomaly diagnosis framework.

It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

Furthermore, this application also provides an electronic device, as shown in FIG5. FIG5 shows a block diagram of an electronic device according to an embodiment of this application, specifically:

The electronic device may include components such as a processor 501 with one or more processing cores, a memory 502 with one or more computer-readable storage media, a power supply 503, and an input unit 504. Those skilled in the art will understand that the electronic device structure shown in FIG. 5 does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

The processor 501 is the control center of the electronic device. It connects to various parts of the computer device via various interfaces and lines. By running or executing software programs and/or modules stored in the memory 502, and by calling data stored in the memory 502, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the electronic device. Optionally, the processor 501 may include one or more processing cores; preferably, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user page, and application programs, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 501.

The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 502 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 502 may also include a memory controller to provide the processor 501 with access to the memory 502.

The electronic device also includes a power supply 503 that supplies power to various components. Preferably, the power supply 503 can be logically connected to the processor 501 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 503 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

The electronic device may also include an input unit 504, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 501 in the electronic device loads the executable files corresponding to the processes of one or more computer programs into the memory 502 according to the following instructions, and the processor 501 runs the computer programs stored in the memory 502, thereby realizing the various functions in the foregoing embodiments of this application. For example, the processor 501 can perform the following steps:

In response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, a corresponding message processing thread is distributed; the abnormal information is received by the message processing thread and distributed to the subsystem agent corresponding to the target subsystem; the subsystem agent corresponding to the target subsystem, together with the subsystem agents corresponding to other subsystems in the multiple subsystems, performs joint abnormal diagnosis to obtain a joint abnormal diagnosis result.

In some embodiments of this application, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems to obtain joint anomaly diagnosis results, the method further includes: making joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and performing joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy.

In some embodiments of this application, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the inter-process communication service, the method further includes: detecting whether the subsystems in the multiple subsystems have connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; if the subsystems in the multiple subsystems are detected to have connected to the abnormal diagnosis framework, creating a subsystem agent corresponding to the subsystem in the multiple subsystems.

In some embodiments of this application, the step of performing joint anomaly diagnosis through the subsystem agent corresponding to the target subsystem, in conjunction with the subsystem agents corresponding to other subsystems in the plurality of subsystems, to obtain a joint anomaly diagnosis result includes: performing anomaly diagnosis through the subsystem agent corresponding to the target subsystem based on the anomaly information to obtain a first anomaly diagnosis result; if the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, then sending a collaborative diagnosis message to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; performing anomaly diagnosis through the subsystem agent corresponding to the first joint subsystem to obtain a second anomaly diagnosis result; and obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result.

In some embodiments of this application, obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result includes: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then sending a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; performing anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtaining the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result.

In some embodiments of this application, the method further includes: transmitting anomaly-related data to a preset reporting service, the preset reporting service being used to report the anomaly-related data to a cloud server; and receiving anomaly repair content transmitted from the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device.

In some embodiments of this application, the anomaly diagnosis framework further includes a framework performance self-test module; it also includes: acquiring anomaly diagnosis processing related data in the system; and analyzing the anomaly diagnosis processing related data through the framework performance self-test module to obtain the framework performance in the anomaly diagnosis framework.

Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a computer-readable storage medium and loaded and executed by a processor.

Therefore, embodiments of this application also provide a storage medium storing a computer program that can be loaded by a processor to execute the steps in any of the methods provided in embodiments of this application.

The storage medium can be a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

Since the computer program stored in the storage medium can execute the steps of any of the methods provided in the embodiments of this application, the beneficial effects that the methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

It should be understood that this application is not limited to the embodiments described above and shown in the accompanying drawings, but various modifications and changes can be made without departing from its scope.

Claims (20)

A system anomaly diagnosis method, wherein the system includes multiple subsystems and an anomaly diagnosis framework, the anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems, the method is applied to the anomaly diagnosis framework, and the method includes: In response to detecting abnormal information sent by the target subsystem in the multiple subsystems through the cross-process communication service, a corresponding message processing thread is distributed; The exception information is received by the message processing thread and distributed to the subsystem agent corresponding to the target subsystem. By using the subsystem agent corresponding to the target subsystem, and in conjunction with the subsystem agents corresponding to other subsystems in the multiple subsystems, anomaly joint diagnosis is performed to obtain the anomaly joint diagnosis result. According to the method of claim 1, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the plurality of subsystems to obtain the joint anomaly diagnosis result, the method further includes: Based on the joint diagnosis results of the anomalies, joint anomaly repair decisions are made for the multiple subsystems to obtain a joint repair strategy for multiple subsystems. Perform joint repair of abnormal multi-subsystems according to the aforementioned multi-subsystem joint repair strategy. According to the method of claim 1, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the plurality of subsystems through the inter-process communication service, the method further includes: Detect whether a subsystem in the multiple subsystems is connected to the anomaly diagnosis framework through the connection interface encapsulated by the anomaly diagnosis framework. If a subsystem connection is detected to enter the anomaly diagnosis framework from the multiple subsystems, a subsystem agent corresponding to the subsystem in the multiple subsystems is created. According to the method of claim 1, the step of performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the plurality of subsystems to obtain joint anomaly diagnosis results includes: The subsystem agent corresponding to the target subsystem performs anomaly diagnosis based on the anomaly information to obtain a first anomaly diagnosis result. If the subsystem agent corresponding to the target subsystem determines the first joint subsystem based on the first anomaly diagnosis result, then a collaborative diagnosis message is sent to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem. Anomaly diagnosis is performed through the subsystem agent corresponding to the first joint subsystem to obtain the second anomaly diagnosis result; The combined abnormal diagnosis result is obtained based on the first abnormal diagnosis result and the second abnormal diagnosis result. According to the method of claim 4, the step of obtaining the joint abnormal diagnosis result based on the first abnormal diagnosis result and the second abnormal diagnosis result includes: If the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then a collaborative diagnosis message is sent from the subsystem agent corresponding to the first joint subsystem to the subsystem agent corresponding to the second joint subsystem. Anomaly diagnosis is performed through the subsystem agent corresponding to the second joint subsystem to obtain the third anomaly diagnosis result; The combined abnormal diagnosis result is obtained based on the first abnormal diagnosis result, the second abnormal diagnosis result, and the third abnormal diagnosis result. The method according to claim 1, wherein the method further comprises: The abnormality-related data is transmitted to a preset reporting service, which is used to report the abnormality-related data to a cloud server. The receiving device receives anomaly repair content transmitted from the cloud server, which is generated by the cloud server based on the anomaly-related data and transmitted to the device. According to the method of claim 1, the anomaly diagnosis framework further includes a framework performance self-test module; the method further includes: Obtain relevant data on anomaly diagnosis and handling in the system; The framework performance is obtained by analyzing the anomaly diagnosis and processing related data through the framework performance self-test module. According to the method of claim 4, wherein determining the first joint subsystem based on the first abnormal diagnosis result includes: Query the first abnormal category corresponding to the first abnormal diagnosis result from the preset diagnosis table; Query the first joint subsystem corresponding to the first abnormal category from the preset diagnostic table. According to the method of claim 2, the step of making joint anomaly repair decisions for the multiple subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy includes: Extract abnormal issues from the combined abnormal diagnostic results; If at least two abnormal issues are extracted, the at least two abnormal issues are prioritized to obtain the abnormal handling priority of each abnormal issue, and the multi-subsystem joint repair strategy is to repair the abnormal issues according to the abnormal handling priority. According to the method of claim 9, the step of prioritizing the at least two abnormal issues to obtain the exception handling priority for each of the abnormal issues includes: From the preset priority table, query the exception handling priority of each exception problem extracted, wherein the preset priority table includes exception handling priorities set in advance for different exception problems. According to the method of claim 6, wherein the anomaly diagnosis framework performs joint anomaly repair decision-making based on a repair knowledge graph; after the anomaly repair content transmitted in the receiving device, the method further includes: The repair knowledge graph is adjusted based on the anomaly repair content; Anomaly joint repair decision-making is performed based on the adjusted repair knowledge graph, resulting in a multi-subsystem joint repair strategy. According to the method of claim 7, the framework performance self-test module includes a subsystem diagnostic detection unit; the step of analyzing the anomaly diagnosis processing related data through the framework performance self-test module to obtain the framework performance in the anomaly diagnosis framework includes: The subsystem diagnostic detection unit analyzes the anomaly diagnosis and processing related data to obtain the anomaly diagnosis performance of the anomaly diagnosis framework. A system anomaly diagnosis device, wherein the system includes multiple subsystems and an anomaly diagnosis framework, the anomaly diagnosis framework includes an inter-process communication service and subsystem agents corresponding to each of the subsystems, the device is applied to the anomaly diagnosis framework, and the device includes: The connection processing module is used to respond to abnormal information sent by the target subsystem in the multiple subsystems through the cross-process communication service, and to distribute the corresponding message processing thread. The data distribution module is used to receive the exception information through the message processing thread and distribute the exception information to the subsystem agent corresponding to the target subsystem. The joint diagnosis module is used to perform joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the multiple subsystems, and obtain joint anomaly diagnosis results. According to the apparatus of claim 13, after performing joint anomaly diagnosis by combining the subsystem agent corresponding to the target subsystem with the subsystem agents corresponding to other subsystems in the plurality of subsystems to obtain joint anomaly diagnosis results, the apparatus further includes an anomaly repair module, configured to: make joint anomaly repair decisions for the plurality of subsystems based on the joint anomaly diagnosis results to obtain a multi-subsystem joint repair strategy; and perform joint multi-subsystem repair of anomalies based on the multi-subsystem joint repair strategy. According to the apparatus of claim 13, before distributing the corresponding message processing thread in response to detecting abnormal information sent by the target subsystem in the plurality of subsystems through the inter-process communication service, the apparatus further includes a proxy creation module, configured to: detect whether a subsystem in the plurality of subsystems has connected to the abnormal diagnosis framework through the connection interface encapsulated by the abnormal diagnosis framework; if a subsystem in the plurality of subsystems is detected to have connected to the abnormal diagnosis framework, create a subsystem proxy corresponding to the subsystem in the plurality of subsystems. According to the apparatus of claim 13, the joint diagnosis module is configured to: perform anomaly diagnosis based on the anomaly information through the subsystem agent corresponding to the target subsystem to obtain a first anomaly diagnosis result; if the subsystem agent corresponding to the target subsystem determines a first joint subsystem based on the first anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the first joint subsystem through the subsystem agent corresponding to the target subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the first joint subsystem to obtain a second anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result and the second anomaly diagnosis result. According to the apparatus of claim 16, the joint diagnosis module is configured to: if the subsystem agent corresponding to the first joint subsystem determines the second joint subsystem based on the second anomaly diagnosis result, then send a collaborative diagnosis message to the subsystem agent corresponding to the second joint subsystem through the subsystem agent corresponding to the first joint subsystem; perform anomaly diagnosis through the subsystem agent corresponding to the second joint subsystem to obtain a third anomaly diagnosis result; and obtain the joint anomaly diagnosis result based on the first anomaly diagnosis result, the second anomaly diagnosis result, and the third anomaly diagnosis result. The apparatus according to claim 13, further comprising a data reporting module, configured to: transmit anomaly-related data to a preset reporting service, the preset reporting service being configured to report the anomaly-related data to a cloud server; and receive anomaly repair content transmitted in the device, the anomaly repair content being analyzed by the cloud server based on the anomaly-related data and transmitted to the device. A storage medium having a computer program stored thereon, which, when executed by a computer's processor, causes the computer to perform the method according to any one of claims 1 to 12. An electronic device comprising: a memory storing a computer program; and a processor for reading the computer program stored in the memory to perform the method according to any one of claims 1 to 12.