Abnormity analysis method and device for embedded application, electronic equipment and storage medium

Abstract

The invention provides an anomaly analysis method and device for an embedded application, electronic equipment and a storage medium, and the method comprises the steps: obtaining a target core dump file which is from a target core dump platform and corresponds to a target embedded application; determining a target loading process according to the target core dump platform and a target visual platform needing to load the target core dump file; and according to the target loading process, loading the target core dump file to the target visual platform, so as to perform anomaly analysis on the target embedded application through the target visual platform. Through application of the method and the device, the target core dump file can be automatically loaded to the target visual platform, so that the purpose of not needing manual repeated and tedious configuration can be realized, and the technical effect of effectively reducing the manual operation intensity in embedded application exception analysis is achieved; the problem that the abnormality analysis of the embedded application is tedious in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and in particular to an abnormality analysis method and device for embedded applications, an electronic device, and a storage medium. Background Art

[0002] In embedded development, when an exception occurs during the execution of an embedded application on a development board (e.g., an illegal address access occurs in the program), the operating system will record the exception in the form of a core dump file in a designated location on the development board. Developers can use specific tools (e.g., gdb) to analyze the core dump file to locate the location and status of the exception in the application code (e.g., the line of code where the exception occurred, variable information, stack information, etc.). However, this method of operation has the following drawbacks:

[0003] 1. The core dump files of heterogeneous embedded platforms correspond to different platform debugging and analysis tools. Developers need to install the corresponding debugging and analysis tools locally or on the embedded target board. This operation process brings great inconvenience to developers' abnormal analysis work.

[0004] 2. Exception analysis involves analyzing many abnormal states (including but not limited to: abnormal code line location, disassembly view, register values, stack information, variable information); developers often need to use visual analysis tools for analysis, but the visual analysis configuration and loading process of mainstream development tools (such as VSCode\Eclipse, etc.) is relatively complex. The repetitive and tedious configuration brings great inconvenience to exception analysis work.

[0005] Therefore, the related art has the technical problem of cumbersome abnormal analysis of embedded applications. Summary of the Invention

[0006] The present application provides an embedded application exception analysis method and device, an electronic device, and a storage medium to at least solve the problem of cumbersome embedded application exception analysis existing in the related art.

[0007] According to one aspect of an embodiment of the present application, a method for analyzing anomalies in an embedded application is provided, comprising:

[0008] Obtaining a target core dump file corresponding to a target embedded application from a target core dump platform;

[0009] Determining a target loading process according to the target core dump platform and a target visualization platform that needs to load the target core dump file;

[0010] According to the target loading process, the target core dump file is loaded into the target visualization platform, so as to perform an exception analysis on the target embedded application through the target visualization platform.

[0011] Optionally, as in the aforementioned method, obtaining a target core dump file from a target core dump platform corresponding to a target embedded application includes:

[0012] Determine platform category information for indicating the target core dump file storing the target embedded application, and a file path for storing the target core dump file in the target core dump platform;

[0013] The target core dump file is obtained by loading from the target core dump platform indicated by the platform category information according to the file path.

[0014] Optionally, as in the aforementioned method, determining a target loading process according to the target core dump platform and a target visualization platform that needs to load the target core dump file includes:

[0015] Determining, according to the target core dump platform and the target visualization platform, loading process information for loading the target core dump file from the target core dump platform to the target visualization platform;

[0016] The target loading process is obtained according to all target steps indicated by the loading process information and the order between each target step.

[0017] Optionally, as in the aforementioned method, the target step includes: loading and obtaining a tool for performing anomaly analysis according to analysis tool path information.

[0018] Optionally, as in the aforementioned method, obtaining the target loading process according to all target steps indicated by the loading process information and the order between the target steps includes:

[0019] In the case where the target step is a preset step injected in advance, the preset steps corresponding to each target step are combined in the order to obtain the target loading process.

[0020] Optionally, as in the aforementioned method, the method further includes:

[0021] In the case that all the target steps include at least one new step that is not the preset step, after injecting a new preset step corresponding to the new step, the new preset step and the remaining steps are combined in the order to obtain the target loading process, wherein the remaining steps are the steps among all the preset steps that are consistent with the target step.

[0022] Optionally, as in the aforementioned method, the step of loading the target core dump file from the target core dump platform indicated by the platform category information according to the file path includes:

[0023] Loading an original core dump file from the target core dump platform according to the file path;

[0024] Determining a corresponding file conversion strategy based on the target core dump platform and the target visualization platform;

[0025] According to the file conversion strategy, the original core dump file is converted into the target core dump file suitable for the target visualization platform.

[0026] According to another aspect of an embodiment of the present application, there is also provided an abnormality analysis device for embedded applications, comprising:

[0027] An acquisition module, configured to acquire a target core dump file corresponding to a target embedded application from a target core dump platform;

[0028] A determination module, configured to determine a target loading process according to the target core dump platform and a target visualization platform on which the target core dump file needs to be loaded;

[0029] A loading module is used to load the target core dump file into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform.

[0030] According to another aspect of the embodiments of the present application, an electronic device is also provided, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; wherein the memory is used to store computer programs; and the processor is used to execute the method steps in any of the above embodiments by running the computer program stored on the memory.

[0031] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is configured to execute the method steps in any of the above embodiments when run.

[0032] In an embodiment of the present application, a target core dump file corresponding to a target embedded application is obtained from a target core dump platform; a target loading process is determined according to the target core dump platform and a target visualization platform that needs to load the target core dump file; and according to the target loading process, the target core dump file is loaded into the target visualization platform so as to perform an exception analysis on the target embedded application through the target visualization platform. Since the target core dump file can be automatically loaded into the target visualization platform through this implementation method, the purpose of eliminating the need for manual repetitive and tedious configuration can be achieved, thereby achieving the technical effect of effectively reducing the intensity of manual operation in the abnormal analysis of embedded applications, thereby solving the problem of tedious abnormal analysis of embedded applications existing in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0035] Figure 1 is a schematic diagram of a hardware environment of an optional abnormality analysis method for embedded applications according to an embodiment of the present application;

[0036] Figure 2 This is a flow chart of an optional method for analyzing anomalies in embedded applications according to an embodiment of the present application;

[0037] Figure 3 1 is a flow chart of another optional method for analyzing anomalies in embedded applications according to an embodiment of the present application;

[0038] Figure 4 1 is a flow chart of another optional method for analyzing anomalies in embedded applications according to an embodiment of the present application;

[0039] Figure 5 is a schematic diagram of the relationship between an optional automatic loading engine, a visualization platform, and a core dump platform according to an embodiment of the present application;

[0040] Figure 6 This is a structural block diagram of an optional abnormality analysis device for embedded applications according to an embodiment of the present application;

[0041] Figure 7 This is a structural block diagram of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0043] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0044] According to one aspect of the embodiment of the present application, a method for analyzing anomalies of an embedded application is provided. Optionally, in this embodiment, the above-mentioned method for analyzing anomalies of an embedded application can be applied to Figure 1 In the hardware environment shown in FIG. 1 , which is composed of a terminal 1402 and a server 1404. Figure 1 As shown, server 1404 is connected to terminal 1402 via a network, and can be used to provide services (such as game services, application services, etc.) for the terminal or the client installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 1404.

[0045] The aforementioned network may include, but is not limited to, at least one of the following: a wired network and a wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: a wide area network, a metropolitan area network, or a local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity) and Bluetooth. The terminal may be, but is not limited to, a PC, a mobile phone, a tablet computer, or the like.

[0046] The method for analyzing anomalies in embedded applications according to the embodiment of the present application may be executed by a server, a terminal, or both. The method for analyzing anomalies in embedded applications according to the embodiment of the present application may be executed by a terminal or a client installed thereon.

[0047] Taking the abnormality analysis method of the embedded application in this embodiment implemented by the automatic loading engine in the server as an example, Figure 2 An embodiment of the present invention provides an abnormality analysis method for an embedded application, comprising the following steps:

[0048] Step S202 : Acquire a target core dump file corresponding to a target embedded application from a target core dump platform.

[0049] The exception analysis method for embedded applications in this embodiment can be applied to a scenario where core dump files generated by heterogeneous platforms (for example, core dump files of X86 and ARM) are loaded into a visualization platform for exception loading analysis.

[0050] In this embodiment, the automatic loading engine can obtain the target core dump file corresponding to the target embedded application from the target core dump platform. The above-mentioned target embedded application can be any embedded application. The automatic loading engine in this embodiment and the visualization platform (i.e. Figure 5 The visual IDE shown) and the core dump platform (i.e. Figure 5 The relationship between the core dump shown in Figure 5 As shown, users can inject the information that needs to be configured into the automatic loading engine through dynamic configuration injection. For example, information including but not limited to the following types can be injected into the automatic loading engine: loading process, abnormal file path, platform category information, etc.

[0051] Step S204 : determining a target loading process according to the target core dump platform and the target visualization platform that needs to load the target core dump file.

[0052] That is to say, in this embodiment, the corresponding target loading process can be determined based on the target core dump platform and the target visualization platform that needs to load the target core dump file. The target loading process can be determined by the corresponding relationship between the platform combination relationship and the loading process. The platform combination relationship can be a combination relationship between the core dump platform and the visualization platform. For example, when the platform combination relationship is the core dump platform X86 and the visualization platform VSCode, the corresponding loading process is I; when the platform combination relationship is the core dump platform X86 and the visualization platform Eclipse, the corresponding loading process is II; when the platform combination relationship is the core dump platform ARM and the visualization platform VSCode, the corresponding loading process is III; when the platform combination relationship is the core dump platform ARM and the visualization platform Eclipse, the corresponding loading process is IV.

[0053] Step S206 : loading the target core dump file into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform.

[0054] After determining the target loading process, the target core dump file can be loaded into the target visualization platform according to the process sequence of each step in the target loading process. The target visualization platform can then use the corresponding analysis tools to perform anomaly analysis on the target embedded application. As a result, developers no longer need to worry about the platform's abnormal loading process and configuration process. The automatic loading engine will complete the loading of the target core dump file on the target visualization platform through the above method, and developers only need to focus on the anomaly analysis itself.

[0055] In an embodiment of the present application, a target core dump file corresponding to a target embedded application is obtained from a target core dump platform; a target loading process is determined according to the target core dump platform and a target visualization platform that needs to load the target core dump file; and the target core dump file is loaded into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform. Because the target core dump file can be automatically loaded into the target visualization platform through this implementation method, the purpose of eliminating the need for manual repetitive and tedious configuration can be achieved, achieving the technical effect of effectively reducing the intensity of manual operation in the abnormal analysis of embedded applications, thereby solving the problem of tedious abnormal analysis of embedded applications existing in the related art.

[0056] like Figure 3 As shown, as an optional implementation, as in the aforementioned method, the target core dump file corresponding to the target embedded application from the target core dump platform can be obtained by the following steps:

[0057] Step S302 : determining platform category information indicating the target core dump file storing the target embedded application and a file path for storing the target core dump file in the target core dump platform.

[0058] In other words, the automatic loading engine can obtain platform classification information of the core dump platform storing the target core dump file. The platform classification information can be identification information for specifically indicating the core dump platform storing the target core dump file. Based on the platform classification information, the automatic loading engine can then determine the core dump platform from which to obtain the target core dump file. Furthermore, the automatic loading engine can also obtain the file path where the target core dump file is stored on the target core dump platform.

[0059] Step S304 : obtaining a target core dump file by loading from the target core dump platform indicated by the platform category information according to the file path.

[0060] After the automatic loading engine obtains the above file path and platform category information, it can load the target core dump file from the target core dump platform indicated by the platform category information according to the file path.

[0061] Alternatively, you can obtain the above platform category information and file path through the automatic analysis command line interface shown in the following format:

[0062] dio postmortem load--except_file_path${path}--platfrom${platform}

[0063] In the above interface:

[0064] dio: Fixed, automatically load the engine tool name;

[0065] postmortem: fixed, indicating abnormal analysis class;

[0066] load: fixed, indicating automatic loading of classes;

[0067] --except_file_path: exception file path, which is set by the developer as Figure 5 The dynamic configuration injection shown is implemented as passed in;

[0068] --platform: platform category information, provided by the developer through Figure 5 The dynamic configuration injection shown is implemented as passed in.

[0069] like Figure 4As shown, as an optional implementation, as in the aforementioned method, the target loading process can be determined according to the target core dump platform and the target visualization platform that needs to load the target core dump file through the following steps:

[0070] Step S402 : Determine loading process information for loading the target core dump file from the target core dump platform to the target visualization platform according to the target core dump platform and the target visualization platform.

[0071] That is, based on the determined target core dump platform and target visualization platform, loading process information for loading the target core dump file from the target core dump platform to the target visualization platform can be determined. For example, the loading process information can be determined according to the aforementioned correspondence between the platform combination relationship and the loading process.

[0072] Step S404: Obtain a target loading process according to all target steps indicated by the loading process information and the order between each target step.

[0073] After the loading process information is determined, the corresponding target loading process can be generated according to all target steps indicated by the loading process information and the order between each target step. The target step can be a step that has been injected into the automatic loading engine.

[0074] As an optional implementation, as in the aforementioned method, the target step includes: loading and obtaining a tool for performing anomaly analysis according to the analysis tool path information.

[0075] The target loading process can be determined by the configuration specification of the configuration file, which is described in json format. The example format of the configuration file is as follows:

[0076] {

[0077] "version": "1.0", / / version number, the version number of the automatic loading engine;

[0078] "target_arch": "x86", / / The system to be adapted, that is, the target core dump platform to be adapted;

[0079] "target_platform": "eclipse", / / IDE platform to be adapted, that is, the target visualization platform to be adapted;

[0080] “tool_path”: “C: / tools / gdb / gdb_x86.exe”, / / “Analysis tool path”, that is, the path where the exception analysis tool is stored;

[0081] “load_seq”:[“load_project”,“load_tool”,“set_env”,“...”], / / Loading process (different IDE platforms correspond to different loading processes), where load_project, load_tool and set_env are all steps to implement loading, load_project is to load the project, load_tool is to load the analysis tool, and set_env is to set the environment parameters.

[0082] The above configuration file path can be obtained through the dynamic configuration injection command line interface shown below to obtain the configuration loading process information and the path of the analysis tool. The format is as follows:

[0083] dio postmorteminject--config${config_path}

[0084] In the above interface:

[0085] dio: Fixed, automatically load the engine tool name;

[0086] postmortem: fixed, indicating abnormal analysis class;

[0087] inject: fixed, identifies the configuration injection class;

[0088] --config: configuration file path, which is set by the developer through Figure 5 The dynamic configuration injection shown is implemented and the file format must comply with the automatic loading engine format specification.

[0089] It can be seen that the method of this embodiment can quickly establish a target loading process, effectively reduce the complexity of manual implementation, and improve efficiency.

[0090] As an optional implementation, as in the aforementioned method, the target loading process can be obtained by following the steps described below according to all target steps indicated by the loading process information and the order between the target steps, including:

[0091] In the case where the target step is a preset step that is pre-injected, the preset steps corresponding to each target step are combined in order to obtain the target loading process. That is to say, in the case where the target step is a preset step that is pre-injected into the automatic loading engine, the automatic loading engine can directly combine the preset steps corresponding to each target step in the automatic loading engine in the above order, so as to obtain the target loading process. For example, when the target steps include "load_project", "set_env", and "load_tool", and the order is "load_project", "load_tool", and "set_env", the automatic loading engine can combine the "load_project", "set_env", and "load_tool" that have been injected in order to obtain the target loading process in the order of "load_project", "load_tool", and "set_env".

[0092] As an optional implementation, as in the above method, the method further includes:

[0093] If all target steps contain at least one new step that is not a preset step, after injecting a new preset step corresponding to the new step, the new preset step and the remaining steps are sequentially combined to obtain the target loading process, where the remaining steps are those steps in all preset steps that are consistent with the target step. In other words, if all target steps contain at least one new step, and this new step is not a preset step pre-injected into the automatic loading engine, a new preset step corresponding to the new step needs to be injected into the automatic loading engine, and then the new preset step and the remaining steps are sequentially combined to obtain the target loading process. For example, when the target steps include "load_project", "set_env", and "load_tool", where "set_env" is a new step, and the order is "load_project", "load_tool", and "set_env", since "set_env" does not exist in the automatic loading engine, it is necessary to inject "set_env" (that is, a new preset step), and then the remaining steps "load_project" and "load_tool" that have been injected, as well as the new preset step "set_env" can be combined in order to obtain the target loading process with the order of "load_project", "load_tool", and "set_env".

[0094] As an optional implementation, as in the aforementioned method, the aforementioned step of loading the target core dump file from the target core dump platform indicated by the platform category information according to the file path may be implemented by the following steps:

[0095] The original core dump file is loaded from the target core dump platform according to the file path; based on the target core dump platform and the target visualization platform, a corresponding file conversion strategy is determined; according to the file conversion strategy, the original core dump file is converted into a target core dump file suitable for the target visualization platform.

[0096] Specifically, the original core dump file is a core dump file stored in the target core dump platform. After loading the original core dump file, the automatic loading engine can formulate an appropriate file conversion strategy based on the differences between the core dump platform and the visualization platform. The file conversion strategy can be determined by the correspondence between the platform combination relationship and the loading process. The platform combination relationship can be the combination relationship between the core dump platform and the visualization platform. For example, when the platform combination relationship is the core dump platform X86 and the visualization platform VSCode, the corresponding file conversion strategy is file conversion strategy A; when the platform combination relationship is the core dump platform X86 and the visualization platform Eclipse, the corresponding file conversion strategy is file conversion strategy B; when the platform combination relationship is the core dump platform ARM and the visualization platform VSCode, the corresponding file conversion strategy is file conversion strategy C; and when the platform combination relationship is the core dump platform ARM and the visualization platform Eclipse, the corresponding file conversion strategy is file conversion strategy D. After determining the file conversion strategy, the original core dump file can be converted into a target core dump file suitable for the target visualization platform according to the file conversion strategy. For example, the converted target core dump file needs to conform to the file format specifications of the target visualization platform; contain necessary debugging information to facilitate visualization analysis by the target visualization platform; adapt to the performance limitations of the target visualization platform (for example, the Web platform may limit the size of a single file); and, if necessary, desensitize sensitive information in the original core dump file.

[0097] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0098] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM (Read-Only Memory, Read-Only Memory) / RAM (Random Access Memory, Random Access Memory), a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0099] According to another aspect of the embodiments of the present application, an embedded application anomaly analysis device for implementing the above-mentioned embedded application anomaly analysis method is also provided. Figure 6 This is a structural block diagram of an optional embedded application exception analysis device according to an embodiment of the present application, such as Figure 6 As shown, the device may include:

[0100] An acquisition module 61 is configured to acquire a target core dump file corresponding to a target embedded application from a target core dump platform;

[0101] A determination module 62 is configured to determine a target loading process according to the target core dump platform and a target visualization platform on which the target core dump file needs to be loaded;

[0102] The loading module 63 is configured to load the target core dump file into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform.

[0103] It should be noted that the acquisition module 61 in this embodiment can be used to execute the above step S202, the determination module 62 in this embodiment can be used to execute the above step S204, and the loading module 63 in this embodiment can be used to execute the above step S206.

[0104] Through the above module, a target core dump file corresponding to a target embedded application is obtained from a target core dump platform; a target loading process is determined according to the target core dump platform and the target visualization platform on which the target core dump file is to be loaded; and according to the target loading process, the target core dump file is loaded onto the target visualization platform, so as to perform an exception analysis on the target embedded application via the target visualization platform. Because this implementation method can automatically load the target core dump file onto the target visualization platform, the purpose of eliminating the need for manual repetitive and tedious configuration is achieved, achieving the technical effect of effectively reducing the intensity of manual operation in embedded application exception analysis, thereby resolving the problem of tedious embedded application exception analysis existing in related technologies.

[0105] In addition to the above modules, the device in this embodiment may also include a module for executing any method in the embodiments of the abnormality analysis method for any embedded application as described above.

[0106] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. Figure 1 The hardware environment shown can be implemented through software or hardware, wherein the hardware environment includes a network environment.

[0107] According to another aspect of an embodiment of the present application, an electronic device for implementing the above-mentioned abnormality analysis method for embedded applications is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0108] According to another embodiment of the present application, there is also provided an electronic device, including: Figure 7 As shown, the electronic device may include: a processor 1501 , a communication interface 1502 , a memory 1503 and a communication bus 1504 , wherein the processor 1501 , the communication interface 1502 , and the memory 1503 communicate with each other via the communication bus 1504 .

[0109] Memory 1503, used for storing computer programs;

[0110] The processor 1501 is configured to execute the program stored in the memory 1503 to implement the following steps:

[0111] Step S202 : Acquire a target core dump file corresponding to a target embedded application from a target core dump platform.

[0112] Step S204 : determining a target loading process according to the target core dump platform and the target visualization platform that needs to load the target core dump file.

[0113] Step S206 : loading the target core dump file into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform.

[0114] Optionally, in this embodiment, the communication bus may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. This communication bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figure shows only one thick line, but this does not imply that there is only one bus or only one type of bus. The communication interface is used for communication between the electronic device and other devices.

[0115] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage. Alternatively, the memory may be at least one storage device located away from the processor.

[0116] As an example, the memory 1503 may include, but is not limited to, the acquisition module 61, the determination module 62, and the loading module 63 in the above-mentioned abnormality analysis device for embedded applications. In addition, it may also include, but is not limited to, other module units in the above-mentioned abnormality analysis device for embedded applications, which will not be repeated in this example.

[0117] The above-mentioned processor can be a general-purpose processor, which can include but is not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0118] An embodiment of the present application further provides a computer-readable storage medium, the storage medium including a stored program, wherein the method steps of the above method embodiment are executed when the program is run.

[0119] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media that can store program codes, such as a USB flash drive, a ROM, a RAM, a mobile hard disk, a magnetic disk, or an optical disk.

[0120] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0121] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-mentioned computer-readable storage medium. Based on this understanding, the technical solution of the present application, 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, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which can be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application.

[0122] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0124] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the purpose of the solution provided in this embodiment.

[0125] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0126] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for analyzing abnormalities in embedded applications, characterized in that: include: Obtaining a target core dump file corresponding to a target embedded application from a target core dump platform; Determining a target loading process according to the target core dump platform and a target visualization platform that needs to load the target core dump file; According to the target loading process, the target core dump file is loaded into the target visualization platform, so as to perform an exception analysis on the target embedded application through the target visualization platform.

2. The method according to claim 1, characterized in that The obtaining of a target core dump file from a target core dump platform corresponding to a target embedded application includes: Determine platform category information for indicating the target core dump file storing the target embedded application, and a file path for storing the target core dump file in the target core dump platform; The target core dump file is obtained by loading from the target core dump platform indicated by the platform category information according to the file path.

3. The method according to claim 1, characterized in that Determining a target loading process according to the target core dump platform and the target visualization platform on which the target core dump file needs to be loaded includes: Determining, according to the target core dump platform and the target visualization platform, loading process information for loading the target core dump file from the target core dump platform to the target visualization platform; The target loading process is obtained according to all target steps indicated by the loading process information and the order between each target step.

4. The method according to claim 3, characterized in that The target step includes: loading and obtaining a tool for performing anomaly analysis according to analysis tool path information.

5. The method according to claim 3, characterized in that Obtaining the target loading process according to all target steps indicated by the loading process information and the order between the target steps includes: In the case where the target step is a preset step injected in advance, the preset steps corresponding to each target step are combined in the order to obtain the target loading process.

6. The method according to claim 5, characterized in that The method further comprises: In the case that all the target steps include at least one new step that is not the preset step, after injecting a new preset step corresponding to the new step, the new preset step and the remaining steps are combined in the order to obtain the target loading process, wherein the remaining steps are the steps among all the preset steps that are consistent with the target step.

7. The method according to claim 2, characterized in that The step of loading the target core dump file from the target core dump platform indicated by the platform category information according to the file path includes: Loading an original core dump file from the target core dump platform according to the file path; Determining a corresponding file conversion strategy based on the target core dump platform and the target visualization platform; According to the file conversion strategy, the original core dump file is converted into the target core dump file suitable for the target visualization platform.

8. An abnormality analysis device for embedded applications, characterized in that: include: An acquisition module, configured to acquire a target core dump file corresponding to a target embedded application from a target core dump platform; A determination module, configured to determine a target loading process according to the target core dump platform and a target visualization platform on which the target core dump file needs to be loaded; A loading module is used to load the target core dump file into the target visualization platform according to the target loading process, so as to perform an exception analysis on the target embedded application through the target visualization platform.

9. An electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein: The processor, the communication interface and the memory communicate with each other via the communication bus, wherein: The memory is used to store computer programs; The processor is configured to execute the method according to any one of claims 1 to 7 by running the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 7 when executed on a processor.

Images