A comprehensive testing method, system, equipment, and media for SSD system disks.

Abstract

This application provides a comprehensive testing method, system, device, and medium for SSD system disks. The method includes: constructing an LTP test set adapted to the usage and stress characteristics of the SSD system disk as the target test object; configuring the LTP test set to cover system calls and boundary conditions of the target platform; constructing a standardized test environment to execute the LTP test set; synchronously collecting multi-dimensional data composed of the SSD system disk's operating status and the system's operating status; recording preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results; performing correlation analysis on the multi-dimensional data, test traceability data, and LTP test results to generate evaluation results reflecting the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under system call stress. This application can adapt to the real-world usage scenarios and stress characteristics of system disks, improving the accuracy and comprehensiveness of test results.

Description

Technical Field

[0001] This application belongs to the field of SSD testing technology, specifically relating to a comprehensive testing method, system, equipment, and media for SSD system disks. Background Technology

[0002] In applications such as industrial control and smart terminals that rely on SSDs (Solid State Drives) as system disks, SSDs, as system disks, need to handle complex operations such as reading and writing core system files, scheduling multiple tasks concurrently, and storing critical data. Their operational stability, performance continuity, and ability to handle abnormal scenarios directly affect the overall operational reliability of the equipment.

[0003] However, traditional testing methods rely on the general LTP (Linux Test Project) test suite, which cannot adapt to the real-world usage scenarios and stress characteristics of system disks, resulting in insufficient test coverage. At the same time, they lack targeted assessments of SSD operational stability and anomaly handling capabilities, affecting the accuracy and comprehensiveness of test results. Summary of the Invention

[0004] This application provides a comprehensive testing method, system, device, and media for SSD system disks, which can adapt to the real-world usage scenarios and stress characteristics of system disks, and improve the accuracy and comprehensiveness of test results.

[0005] To address the aforementioned technical problems, firstly, this application provides a comprehensive testing method for SSD system disks, comprising the following steps:

[0006] Using the SSD system disk as the target test object, an LTP test set adapted to its usage and stress characteristics is constructed, and the LTP test set is configured to cover the target platform system calls and boundary conditions.

[0007] A standardized testing environment was constructed to execute the LTP test set, and multi-dimensional data consisting of the SSD system disk running status and the system running status were collected simultaneously.

[0008] Record preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results;

[0009] The multi-dimensional data, test traceability data, and LTP test results are correlated and analyzed to generate evaluation results that reflect the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under system call pressure.

[0010] As a further improvement to this application, the construction of the LTP test set adapted to its usage and stress characteristics includes:

[0011] Analyze the electrical workload of the SSD system disk to determine its test range, and select the corresponding LTP test subset;

[0012] The LTP test subset includes at least one of the following tests: file system and storage related tests, process and thread management tests, memory and I / O stress tests, boundary and exception tests, and system call combination tests.

[0013] As a further improvement to this application, the construction of the LTP test set adapted to its usage and stress characteristics further includes:

[0014] Obtain the historical command characteristics and environment information of the SSD system disk;

[0015] A graph neural network is used to fuse instruction features and environmental information to generate a dependency graph for filtering and combining test cases within the LTP test subset, thus forming the LTP test set.

[0016] The instruction features include the instruction type, execution frequency, format specifications, and interaction logic corresponding to SSD system disk file reading and writing, process scheduling, memory allocation, and resource request;

[0017] The environmental information includes SSD system disk hardware parameters, operating system configuration, load fluctuation characteristics, and system resource allocation rules.

[0018] As a further improvement to this application, the configuration of the LTP test suite to cover target platform system calls and boundary conditions includes:

[0019] The LTP test set is configured with parameters, including setting the number of concurrent threads and processes to adapt to the operating load of the SSD system disk, setting the continuous runtime, enabling the error injection mechanism, and recording performance data.

[0020] The error injection mechanism is used to simulate abnormal errors such as I / O errors, permission errors, or disk fullness. The performance data includes SSD system disk running status data and system resource usage data.

[0021] As a further improvement to this application, the standardized testing environment is constructed to execute the LTP test set, and multi-dimensional data consisting of the SSD system disk operating status and the system operating status is collected simultaneously, including:

[0022] Start the test execution program corresponding to the LTP test set, record the test start time, test parameters and process configuration, synchronously collect the multi-dimensional data and ensure the stability of the SSD system disk through the monitoring mechanism;

[0023] The multi-dimensional data includes the SMART attribute of the SSD system disk, system-level I / O latency fluctuations, queue depth backlog, CPU utilization, memory utilization, disk utilization, system call exception information, kernel logs, and system response status.

[0024] The monitoring mechanism includes concurrent task simulation, exception capture, and memory monitoring.

[0025] As a further improvement to this application, the recording of preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results includes:

[0026] The preset test nodes are state-retained, and the log information associated with the test nodes is saved, as well as the abnormal event information that occurs during the test.

[0027] The status retention, log information, and abnormal event information of the preset test nodes are used to form the test traceability data.

[0028] Collect the execution pass status, failure status and corresponding error information of each test case in the LTP test set to generate the LTP test results;

[0029] The preset test nodes include test start time, test case execution time, exception occurrence time, and long-run time nodes;

[0030] The log information includes LTP running logs, system logs, SMART data snapshots, iostat periodic sampling data, and vmstat periodic sampling data.

[0031] The abnormal event information includes the time of occurrence of the abnormality, the abnormal phenomenon, the corresponding test case for the abnormality, the real-time status of the SSD system disk, and the system response status.

[0032] As a further improvement to this application, the step of performing correlation analysis on the multi-dimensional data, test traceability data, and LTP test results to generate evaluation results reflecting the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under system call pressure includes:

[0033] Based on the test case pass rate, failure status, and corresponding error information in the LTP test results, combined with the SMART attribute of the SSD system disk and the system response status in multi-dimensional data, the stability of the SSD system disk's operating status is evaluated.

[0034] Based on multi-dimensional data such as system-level I / O latency fluctuations, queue depth accumulation, CPU utilization, memory utilization, and disk utilization, the performance variation characteristics of SSD system disks under different stress scenarios are evaluated.

[0035] Based on the abnormal event information in the test traceability data and the kernel logs and system response status in the multi-dimensional data, the abnormal response characteristics of the SSD system disk under abnormal scenarios are evaluated.

[0036] Secondly, this application provides a comprehensive testing system for SSD system disks, comprising:

[0037] The configuration unit is used to build an LTP test set adapted to the usage and stress characteristics of the SSD system disk as the target test object, and configure the LTP test set to cover the target platform system calls and boundary conditions.

[0038] The execution unit is used to build a standardized test environment to execute the LTP test set and simultaneously collect multi-dimensional data composed of the SSD system disk running status and the system running status.

[0039] The data acquisition unit is used to record preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results.

[0040] The analysis unit is used to perform correlation analysis on the multi-dimensional data, test traceability data and LTP test results, and generate evaluation results that reflect the stability of the SSD system disk's operating status, performance change characteristics and anomaly response characteristics under system call pressure.

[0041] Thirdly, this application provides a computer device including a processor and a memory coupled to the processor, the memory storing a computing program, which, when executed by the processor, causes the processor to perform the steps of the comprehensive testing method for an SSD system disk described above.

[0042] Fourthly, this application provides a computer-readable storage medium storing a computer program that is executed by a processor to implement the comprehensive testing method for an SSD system disk as described above.

[0043] Compared with existing technologies, the comprehensive testing method, system, equipment, and media for SSD system disks provided in this application construct an LTP test set adapted to the usage and stress characteristics of SSDs, and configure the LTP test set to cover system calls and boundary conditions, ensuring a high degree of fit between the test scenario and the real application environment, thus avoiding the problem of insufficient test coverage caused by general LTP test sets. Tests are executed in a standardized test environment, and multi-dimensional data on the operating status of the SSD system disk and the system are collected synchronously, eliminating interference from differences in test platforms. By recording preset test nodes, associated logs, and abnormal event information, traceable test data and LTP test results are formed, enhancing the reproducibility of the testing process. Through correlation analysis of multi-dimensional data, test traceability data, and LTP test results, the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under stress can be systematically evaluated, generating accurate and reliable evaluation results. This achieves precise and comprehensive testing of the performance and stability of SSD system disks under complex system call stress. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A flowchart illustrating the comprehensive testing method for an SSD system disk provided in this application embodiment.

[0046] Figure 2 A flowchart illustrating the formation of test traceability data and LTP test results in the comprehensive testing method for SSD system disks provided in this application embodiment.

[0047] Figure 3 A flowchart illustrating the formation of test traceability data and LTP test results in the comprehensive testing method for SSD system disks provided in this application embodiment.

[0048] Figure 4 A flowchart illustrating the generation of evaluation results in the comprehensive testing method for SSD system disks provided in this application embodiment.

[0049] Figure 5 This is a schematic diagram of the structure of the comprehensive testing system for the SSD system disk provided in the embodiments of this application.

[0050] Figure 6 A schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0051] Figure 7 This is a schematic diagram of the structure of the storage medium provided in the embodiments of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings and specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of this application and are not intended to limit the embodiments of this application.

[0053] In the description of the embodiments of this application, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movement of the components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0054] To make the description of this disclosure more detailed and complete, illustrative descriptions of implementation methods and specific embodiments of the present application are provided below; however, this is not the only form of implementing or utilizing the specific embodiments of the present application. The implementation methods cover features of multiple specific embodiments and methods and steps for constructing and operating these specific embodiments, as well as their order. However, other specific embodiments may also be used to achieve the same or equivalent functions and step sequences.

[0055] In the embodiments of this application, terms such as "exemplary," "in some embodiments," and "in another embodiment" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the term "exemplary" is used to present concepts in a concrete manner.

[0056] In applications such as industrial control and smart terminals that rely on SSDs (Solid State Drives) as system disks, SSDs, as system disks, need to handle complex operations such as reading and writing core system files, scheduling multiple tasks concurrently, and storing critical data. Their operational stability, performance continuity, and ability to handle abnormal scenarios directly affect the overall operational reliability of the equipment.

[0057] However, traditional testing methods rely on the general LTP (Linux Test Project) test suite, which cannot adapt to the real-world usage scenarios and stress characteristics of system disks, resulting in insufficient test coverage. At the same time, they lack targeted assessments of SSD operational stability and anomaly handling capabilities, affecting the accuracy and comprehensiveness of test results.

[0058] In view of this, please refer to Figures 1-7 This application provides a comprehensive testing method, system, device, and medium for SSD system disks, which can adapt to the real-world usage scenarios and stress characteristics of system disks, and improve the accuracy and comprehensiveness of test results.

[0059] Please refer to Figure 1 This is a flowchart of a comprehensive testing method for an SSD system disk provided in an embodiment of this application. The testing method includes the following steps:

[0060] Step S1: Using the SSD system disk as the target test object, construct an LTP test set that adapts to its usage and stress characteristics, and configure the LTP test set to cover the target platform system calls and boundary conditions;

[0061] In this embodiment of the application, the SSD system disk is used as the target test object. Based on the actual usage scenarios and stress characteristics of the SSD system disk, an LTP test set adapted to its usage and stress characteristics is constructed. At the same time, the parameters of the LTP test set are configured to ensure that the LTP test set can cover the system calls and boundary conditions of the target platform, avoid the situation where the general LTP test set is incompatible with the SSD system disk, and improve the scenario fit of the test.

[0062] It should be noted that the target platform refers to the specific hardware device that uses the SSD as the system disk, such as industrial control equipment, smart terminals, servers, and other hardware carriers. The target platform is the actual application environment of the SSD system disk. Therefore, it is necessary to configure the LTP test suite to cover the target platform's system calls and boundary conditions to ensure that the test can reproduce the operating state of the SSD system disk in the actual application scenario.

[0063] Based on this, system calls refer to the interface instructions corresponding to operations such as file reading and writing, process scheduling, memory allocation, and resource request. Setting the LTP test set to cover the system calls of the target platform is essentially to restore the interaction logic between the SSD system disk and the operating system in actual use.

[0064] Furthermore, boundary conditions refer to the extreme, abnormal, or critical scenarios that an SSD system disk may encounter during actual operation. By covering the boundary conditions of the target platform with the LTP test set, the performance of the SSD system disk under extreme or abnormal conditions can be verified, avoiding the problem of incomplete testing caused by a general test set only covering normal scenarios.

[0065] As an optional implementation method, please refer to Figure 2 This is a flowchart illustrating the process of generating test traceability data and LTP test results in the comprehensive testing method for SSD system disks provided in this application embodiment. The aforementioned construction of an LTP test set adapted to its usage and stress characteristics includes:

[0066] Step S10: Analyze the electrical workload of the SSD system disk to determine its test range and select the corresponding LTP test subset;

[0067] The LTP test subset includes at least one of the following tests: file system and storage related tests, process and thread management tests, memory and I / O stress tests, boundary and exception tests, and system call combination tests.

[0068] In this embodiment of the application, the test range can be determined by analyzing the electrical workload of the SSD system disk. For example, by analyzing the power consumption and task load of the SSD system disk during operation, the functional range that needs to be tested can be identified, and the LTP test subset that matches the test range can be selected.

[0069] As an optional implementation method, a correspondence between power consumption changes and actual SSD operation tasks can be established. By monitoring the electrical data of the SSD system disk at each operating stage in real usage scenarios, such as power consumption fluctuations, peak power consumption, and power consumption duration, the core task types in that scenario can be deduced in reverse.

[0070] For example, if the SSD system disk is detected to have periodic high power consumption periods, and these periods are synchronized with the execution periods of tasks such as batch file reading and writing and data transfer task synchronization, it indicates that the current file system and storage-related operations are the core task types in this scenario.

[0071] If the SSD is monitored to be in a stable low-to-medium power consumption state for a long period of time, with only occasional small power fluctuations, then light-load tasks such as regular file queries and system configuration readings are the core task types in the current scenario. If frequent and irregular power consumption fluctuations are monitored, and the fluctuation rhythm matches the frequency of multi-application switching and process scheduling, then multi-task concurrent scheduling is the core task type in the current scenario.

[0072] For example, take the SSD system disk installed in industrial control equipment as an example. This equipment is in a continuous operating state for a long time and is mainly used to perform tasks such as data acquisition, command issuance, and log storage.

[0073] Monitoring its electrical data revealed that the morning and afternoon were the high-power consumption periods, which coincided with the batch upload of industrial sensor data. Therefore, file system and storage related tests, as well as memory and I / O stress tests, were identified as the core test items.

[0074] Meanwhile, the industrial equipment occasionally experiences abnormal scenarios such as sudden power outages and voltage fluctuations. Therefore, power outage recovery tests and voltage fluctuation adaptation tests can be added to the boundary and abnormal testing to cover as much of the testing range as possible.

[0075] In this way, we can clearly identify the most common task scenarios, load intensities, and corresponding core task types that SSD system disks face in actual use. Then, we can add some common basic task types to form a complete test range, ensuring that the subsequent selected LTP test subset can cover the core and common functions of SSD in actual operation.

[0076] In an optional embodiment, this application sets up an LTP test subset related to the core operation of the SSD system disk, including file system and storage-related tests, to verify the file read / write, storage protocol adaptation, and other functions of the SSD system disk.

[0077] Furthermore, the LTP test subset also includes process and thread management tests to adapt to multi-task concurrent scheduling scenarios of the SSD system disk; memory and I / O (Input / Output) stress tests to simulate high-load data transfer scenarios; boundary and anomaly tests to verify the SSD system disk's performance under extreme conditions; and system call combination tests to recreate complex call sequence scenarios, ensuring that the test scope accurately covers the key operating scenarios of the SSD.

[0078] It is understood that this application does not limit the specific test items included in the LTP test subset. Other test items that can adapt to the usage and stress characteristics of SSD system disks and cover the system calls and boundary conditions of the target platform are also feasible, as should be known by those skilled in the art.

[0079] As an optional implementation, the above-described construction of an LTP test set adapted to its usage and stress characteristics further includes:

[0080] Step S11: Obtain the historical command characteristics and environment information of the SSD system disk;

[0081] The instruction features include the instruction type, execution frequency, format specifications, and interaction logic corresponding to SSD system disk file reading and writing, process scheduling, memory allocation, and resource request;

[0082] The environmental information includes SSD system disk hardware parameters, operating system configuration, load fluctuation characteristics, and system resource allocation rules.

[0083] In this embodiment of the application, it is also necessary to obtain the instruction characteristics and environment information generated by the SSD system disk in the past actual operation process.

[0084] In an optional embodiment, the above-mentioned instruction features cover the relevant features corresponding to core operations such as file reading and writing, process scheduling, memory allocation, and resource request, including instruction type, execution frequency, format specifications, and interaction logic.

[0085] The environmental information includes the SSD's own hardware parameters, the configuration information of the operating system it is running, load fluctuation characteristics, and system resource allocation rules, providing effective data support for the accurate selection and combination of subsequent test cases.

[0086] Step S12: Use a graph neural network to fuse instruction features and environmental information to generate a dependency graph for filtering and combining test cases within the LTP test subset, thereby forming the LTP test set;

[0087] In this embodiment, a GNN (Graph Neural Network) is used to fuse the instruction features and environmental information obtained in step S11, and a dependency graph is generated through feature fusion.

[0088] Specifically, when performing feature fusion on instruction characteristics and environmental information, the GNN is used to find potential correlations between instruction characteristics such as instruction type and execution frequency and environmental information such as SSD system disk hardware parameters and load fluctuation characteristics.

[0089] Understandably, compared to traditional solutions that can only statically analyze linear relationships, the GNN provided in this application can effectively capture the complex nonlinear dependencies between instruction features and environmental information, generate dependency graphs that better reflect real and complex workloads, and improve the accuracy of the LTP test set in adapting to actual use scenarios of SSD system disks.

[0090] Furthermore, when further filtering and combining the test cases within the LTP test subset determined in step S10 based on the aforementioned dependency graph, test cases directly related to core operating scenarios such as SSD system disk file reading and writing, process scheduling, memory allocation, and high-concurrency I / O are selected according to the dependency graph. At the same time, test cases with duplicate functions, those that cannot adapt to SSD hardware parameters, and those with load fluctuation characteristics are removed to avoid wasting test resources and reducing test efficiency, ultimately forming an LTP test set that adapts to the usage and stress characteristics of the SSD system disk.

[0091] As an optional implementation, the above-described LTP test suite is configured to cover the target platform's system calls and boundary conditions, including:

[0092] Step S13: Configure the parameters of the LTP test set. The parameter configuration includes setting the number of concurrent threads and processes to adapt to the operating load of the SSD system disk, setting the continuous runtime, enabling the error injection mechanism, and recording performance data.

[0093] The error injection mechanism is used to simulate abnormal errors such as I / O errors, permission errors, or disk fullness. The performance data includes SSD system disk running status data and system resource usage data.

[0094] In this embodiment of the application, after forming an LTP test set that adapts to the usage and stress characteristics of the SSD system disk, it is necessary to configure the parameters of the LTP test set to simulate the stress scenarios and boundary abnormal scenarios of the real operation of the SSD system disk.

[0095] Specifically, it is necessary to set the number of concurrent threads and processes to match the actual operating load of the SSD system disk to ensure that the test pressure is close to reality.

[0096] Furthermore, a continuous runtime was set to verify the long-term stability of the SSD system disk.

[0097] Furthermore, an error injection mechanism is enabled to simulate abnormal errors such as I / O errors, permission errors, or disk fullness. At the same time, the performance data logging function is enabled to collect SSD system disk running status data and system resource usage data, providing data support for subsequent evaluation and ensuring that the test set can fully cover the system calls and boundary conditions of the target platform.

[0098] Step S2: Build a standardized test environment to execute the LTP test set, and simultaneously collect multi-dimensional data composed of the SSD system disk running status and the system running status;

[0099] As an optional implementation, the above-described standardized test environment is used to execute the LTP test set, simultaneously collecting multi-dimensional data consisting of the SSD system disk operating status and the system operating status, including:

[0100] Start the test execution program corresponding to the LTP test set, record the test start time, test parameters and process configuration, synchronously collect the multi-dimensional data and ensure the stability of the SSD system disk through the monitoring mechanism;

[0101] The multi-dimensional data includes the SMART attribute of the SSD system disk, system-level I / O latency fluctuations, queue depth backlog, CPU utilization, memory utilization, disk utilization, system call exception information, kernel logs, and system response status.

[0102] The monitoring mechanism includes concurrent task simulation, exception capture, and memory monitoring.

[0103] In this embodiment of the application, it is necessary to first build a standardized test environment to eliminate the interference of differences between different test environments on the test results and ensure the repeatability and consistency of the test process.

[0104] Specifically, in this standardized environment, the LTP test suite adapted to the characteristics of the SSD system disk is executed, and data acquisition is carried out in parallel, including the simultaneous acquisition of the operating status of the SSD system disk itself and the overall system operating status of the device hosting the SSD system disk.

[0105] In an optional embodiment, after the standardized test environment is built, the test execution program corresponding to the LTP test set is started, and the test start time, preset test parameters and process configuration information are accurately recorded to ensure that the test process is traceable.

[0106] During the testing process, the following data was collected: SMART (Self-Monitoring, Analysis and Reporting Technology) attributes of the SSD system disk. The SMART attribute refers to the status monitoring data of the SSD system disk itself. System-level I / O latency fluctuations were collected to reflect changes in data transmission response speed. Queue depth accumulation was collected to reflect the queuing status of I / O tasks. CPU utilization, memory utilization, and disk utilization were collected to reflect the corresponding hardware resource usage. System call exception information was used to record exceptions that occurred during system calls. Log data generated during the operation of the operating system kernel and system response status reflecting the overall operation feedback of the device were also collected.

[0107] For example, the system-level I / O latency fluctuation threshold is set to ≤10ms. If the fluctuation exceeds this threshold, it is judged as an abnormal performance fluctuation. When the number of backlogged tasks in the queue depth exceeds 12, an abnormal record is triggered. The above thresholds can be flexibly adjusted according to the target platform hardware configuration. This application does not impose further limitations on them.

[0108] Furthermore, during the testing process, monitoring mechanisms are in place to ensure the stability of the SSD system disk during testing, such as concurrent task simulation, exception capture, and memory monitoring.

[0109] Specifically, concurrent tasks can be used to simulate the simultaneous launch of 10 file read / write threads and 5 process scheduling tasks to recreate the multi-task load in a real-world scenario. Anomaly capture is used to promptly capture abnormal situations during the test to avoid test interruption, and memory monitoring is used to monitor memory resource usage in real time. All three work together to ensure the stable operation of the SSD system disk during the test and ensure the integrity and continuity of data collection.

[0110] Step S3: Record the preset test nodes, node association logs, and abnormal event information to form test traceability data and LTP test results;

[0111] In this embodiment of the application, the status of preset key test nodes, log information associated with key test nodes, and abnormal event information that occur during the test are recorded during the test process. These constitute test traceability data of the test process and LTP test results that reflect the execution status of test cases, providing a basis for subsequent correlation analysis.

[0112] As an optional implementation method, please refer to Figure 3 This is a flowchart illustrating the process of generating test traceability data and LTP test results in the comprehensive testing method for SSD system disks provided in this application embodiment. The above-mentioned recording of preset test nodes, node-related logs, and abnormal event information generates test traceability data and LTP test results, including:

[0113] Step S30: Perform status retention on the preset test node, save the log information associated with the test node, and record the abnormal event information that occurs during the test;

[0114] In this embodiment of the application, the status of preset test nodes is retained by taking screenshots, and the log information corresponding to these test nodes is saved simultaneously to ensure the correlation between the logs and the node status.

[0115] In addition, abnormal events that occur during the testing process are recorded in detail, and key information related to the abnormalities is captured to ensure the completeness and relevance of the information records.

[0116] Step S31: The status retention, log information and abnormal event information of the preset test node are used to form the test traceability data;

[0117] In an optional embodiment, the state retention files of preset test nodes, the log information associated with the nodes, and the abnormal event information during the test process are integrated according to the test sequence and logical association to form test traceability data that restores the state of key nodes from the start to the end of the test, the running logs of each stage, and the occurrence of abnormalities.

[0118] Step S32: Collect the execution pass status, failure status and corresponding error information of each test case in the LTP test set to generate the LTP test results;

[0119] In this embodiment of the application, the execution information of each test case in the LTP test set is also collected, such as whether the test passed, if it failed, the specific circumstances of the failure are specified, and the corresponding error code, error description and other error information. After summarizing and organizing this information, an LTP test result that can intuitively reflect the overall execution effect of the test cases is generated.

[0120] The preset test nodes include test start time, test case execution time, exception occurrence time, and long-run time nodes, and the state retention method is screenshot retention;

[0121] The log information includes LTP running logs, system logs, SMART data snapshots, iostat periodic sampling data, and vmstat periodic sampling data.

[0122] The abnormal event information includes the time of occurrence of the abnormality, the abnormal phenomenon, the corresponding test case for the abnormality, the real-time status of the SSD system disk, and the system response status.

[0123] In an optional embodiment, preset test nodes are set at the test start time, test case execution time, exception occurrence time, and long-term running time. The status is saved by taking screenshots to ensure the intuitiveness and authenticity of the node status.

[0124] Furthermore, the log information includes LTP runtime logs, system logs, SMART data snapshots, and periodic sampling data from iostat (Input / Output Statistics) and vmstat (Virtual Memory Statistics) to cover test run and hardware status related logs.

[0125] Thus, by recording preset test nodes, node-related logs, and abnormal event information, this application forms test traceability data and LTP test results, avoiding irrelevant information redundancy or missing key information, and ensuring the relevance and completeness of information recording.

[0126] Step S4: Perform correlation analysis on the multi-dimensional data, test traceability data and LTP test results to generate evaluation results that reflect the stability of the SSD system disk's operating status, performance change characteristics and anomaly response characteristics under system call pressure.

[0127] In this embodiment of the application, it is necessary to perform correlation analysis on the multi-dimensional data obtained in step S2, the test traceability data formed in step S3, and the LTP test results to generate an evaluation result that can reflect the stability of the SSD system disk's operating status, performance change characteristics, and anomaly response characteristics under system call pressure. This avoids the limitations of evaluation caused by single data dimension analysis and ensures the comprehensiveness and accuracy of the evaluation results.

[0128] As an optional implementation method, please refer to Figure 4 This is a flowchart illustrating the comprehensive testing method for SSD system disks provided in this application, which generates evaluation results. The above-mentioned correlation analysis of the multi-dimensional data, test traceability data, and LTP test results generates evaluation results reflecting the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under system call pressure, including:

[0129] Step S40: Based on the test case pass rate, failure status, and corresponding error information in the LTP test results, and combined with the SMART attribute of the SSD system disk and the system response status in the multi-dimensional data, evaluate the stability of the SSD system disk's operating status.

[0130] Furthermore, by using the test case pass rate, failure status, and corresponding error information in the LTP test results, and associating the SMART attribute of the SSD system disk with the system response status in multi-dimensional data, we can comprehensively judge whether the SSD system disk has problems such as functional abnormalities, hardware degradation, or unstable system linkage under long-term system call pressure, so as to evaluate the stability of the SSD system disk's operating status.

[0131] Step S41: Based on the system-level I / O latency fluctuation, queue depth backlog, CPU utilization, memory utilization, and disk utilization in the multi-dimensional data, evaluate the performance change characteristics of the SSD system disk under different stress scenarios;

[0132] In this embodiment of the application, when evaluating the performance change characteristics of the SSD system disk under different stress scenarios, the system-level I / O latency fluctuation, queue depth accumulation, CPU utilization, memory utilization and disk utilization are analyzed based on multi-dimensional data. The performance change characteristics of the SSD system disk under different stress scenarios such as low load, high concurrency and long-term operation are evaluated by analyzing the changing trends, fluctuation amplitude and peak performance of these data under different test stress scenarios.

[0133] Step S42: Based on the abnormal event information in the test traceability data and the kernel logs and system response status in the multi-dimensional data, evaluate the abnormal response characteristics of the SSD system disk in abnormal scenarios.

[0134] In an optional embodiment, when evaluating the abnormal response characteristics of the SSD system disk under abnormal scenarios, the abnormal event information in the test traceability data is used as a basis to determine the time of occurrence of the abnormal event. At the same time, the kernel logs and system response status in multi-dimensional data are correlated to analyze the processing logic and recovery speed of the SSD system disk when encountering various abnormalities.

[0135] Furthermore, by recreating the actual operating state of the SSD system disk under abnormal scenarios, a key basis is provided for judging the reliability of the SSD system disk in complex real-world scenarios.

[0136] For example, suppose that in a certain LTP test, the test case pass rate is 98%, and the two failed test cases are both high-concurrency write scenarios in memory and I / O stress testing; combined with multi-dimensional data correlation analysis, it is found that when the test case fails, the peak fluctuation of system-level I / O latency reaches 15ms, exceeding the set 10ms threshold, the write error count in the SMART attribute increases by 1, and the system response status is timeout and no response.

[0137] Based on the above correlation analysis, it can be determined that the SSD system disk has insufficient stability and significant performance degradation under the extreme pressure of high-concurrency writes. Further analysis of the kernel logs reveals that the failure was caused by the queue depth accumulating to 136 tasks, exceeding the set trigger threshold of 128, which led to I / O request blocking. Therefore, its abnormal response characteristics are characterized by the lack of a queue overflow protection mechanism. Targeted optimization of the SSD's I / O scheduling algorithm can be carried out in the future.

[0138] It is understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0139] The comprehensive testing method for SSD system disks provided in this application constructs an LTP test suite adapted to the usage and stress characteristics of SSDs, and configures the LTP test suite to cover system calls and boundary conditions, ensuring a high degree of fit between the test scenario and the real application environment, thus avoiding the problem of insufficient test coverage caused by general LTP test suites. Tests are executed in a standardized test environment, and multi-dimensional data on the SSD system disk's operating status and the system's operating status are collected synchronously, eliminating interference from differences in test platforms. By recording preset test nodes, associated logs, and abnormal event information, traceable test data and LTP test results are formed, enhancing the reproducibility of the testing process. Through correlation analysis of multi-dimensional data, test traceability data, and LTP test results, the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under stress can be systematically evaluated, generating accurate and reliable evaluation results. This achieves precise and comprehensive testing of the performance and stability of SSD system disks under complex system call stress.

[0140] Based on the comprehensive testing method for SSD system disks described above, this application provides a comprehensive testing system for SSD system disks. Please refer to [link / reference]. Figure 5 This is a schematic diagram of the structure of the comprehensive testing system for SSD system disks provided in this application embodiment. The comprehensive testing system includes a configuration unit, an execution unit, a data acquisition unit, and an analysis unit.

[0141] The configuration unit is used to construct an LTP test set adapted to the usage and stress characteristics of the SSD system disk as the target test object, and configure the LTP test set to cover the target platform system calls and boundary conditions.

[0142] The execution unit is used to build a standardized test environment to execute the LTP test set and simultaneously collect multi-dimensional data composed of the SSD system disk running status and the system running status.

[0143] The data acquisition unit is used to record preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results.

[0144] The analysis unit is used to perform correlation analysis on the multi-dimensional data, test traceability data and LTP test results, and generate evaluation results that reflect the stability of the SSD system disk's operating status, performance change characteristics and anomaly response characteristics under system call pressure.

[0145] As an optional implementation, the construction of the LTP test set adapted to its usage and stress characteristics includes:

[0146] Analyze the electrical workload of the SSD system disk to determine its test range, and select the corresponding LTP test subset;

[0147] The LTP test subset includes at least one of the following tests: file system and storage related tests, process and thread management tests, memory and I / O stress tests, boundary and exception tests, and system call combination tests.

[0148] As an optional implementation, the construction of the LTP test set adapted to its usage and stress characteristics further includes:

[0149] Obtain the historical command characteristics and environment information of the SSD system disk;

[0150] A graph neural network is used to fuse instruction features and environmental information to generate a dependency graph for filtering and combining test cases within the LTP test subset, thus forming the LTP test set.

[0151] The instruction features include the instruction type, execution frequency, format specifications, and interaction logic corresponding to SSD system disk file reading and writing, process scheduling, memory allocation, and resource request;

[0152] The environmental information includes SSD system disk hardware parameters, operating system configuration, load fluctuation characteristics, and system resource allocation rules.

[0153] As an optional implementation, the configuration of the LTP test suite to cover target platform system calls and boundary conditions includes:

[0154] The LTP test set is configured with parameters, including setting the number of concurrent threads and processes to adapt to the operating load of the SSD system disk, setting the continuous runtime, enabling the error injection mechanism, and recording performance data.

[0155] The error injection mechanism is used to simulate abnormal errors such as I / O errors, permission errors, or disk fullness. The performance data includes SSD system disk running status data and system resource usage data.

[0156] As an optional implementation, the standardized test environment is constructed to execute the LTP test set, simultaneously collecting multi-dimensional data consisting of the SSD system disk operating status and the system operating status, including:

[0157] Start the test execution program corresponding to the LTP test set, record the test start time, test parameters and process configuration, synchronously collect the multi-dimensional data and ensure the stability of the SSD system disk through the monitoring mechanism;

[0158] The multi-dimensional data includes the SMART attribute of the SSD system disk, system-level I / O latency fluctuations, queue depth backlog, CPU utilization, memory utilization, disk utilization, system call exception information, kernel logs, and system response status.

[0159] The monitoring mechanism includes concurrent task simulation, exception capture, and memory monitoring.

[0160] As an optional implementation, the recording of preset test nodes, node-related logs, and abnormal event information to form test traceability data and LTP test results includes:

[0161] The preset test nodes are state-retained, and the log information associated with the test nodes is saved, as well as the abnormal event information that occurs during the test.

[0162] The status retention, log information, and abnormal event information of the preset test nodes are used to form the test traceability data.

[0163] Collect the execution pass status, failure status and corresponding error information of each test case in the LTP test set to generate the LTP test results;

[0164] The preset test nodes include test start time, test case execution time, exception occurrence time, and long-run time nodes, and the state retention method is screenshot retention;

[0165] The log information includes LTP running logs, system logs, SMART data snapshots, iostat periodic sampling data, and vmstat periodic sampling data.

[0166] The abnormal event information includes the time of occurrence of the abnormality, the abnormal phenomenon, the corresponding test case for the abnormality, the real-time status of the SSD system disk, and the system response status.

[0167] As an optional implementation, the correlation analysis of the multi-dimensional data, test traceability data, and LTP test results to generate evaluation results reflecting the stability, performance change characteristics, and anomaly response characteristics of the SSD system disk under system call pressure includes:

[0168] Based on the test case pass rate, failure status, and corresponding error information in the LTP test results, combined with the SMART attribute of the SSD system disk and the system response status in multi-dimensional data, the stability of the SSD system disk's operating status is evaluated.

[0169] Based on multi-dimensional data such as system-level I / O latency fluctuations, queue depth accumulation, CPU utilization, memory utilization, and disk utilization, the performance variation characteristics of SSD system disks under different stress scenarios are evaluated.

[0170] Based on the abnormal event information in the test traceability data and the kernel logs and system response status in the multi-dimensional data, the abnormal response characteristics of the SSD system disk under abnormal scenarios are evaluated.

[0171] For further details regarding the implementation techniques of each unit in the comprehensive testing system for the SSD system disk provided in the above embodiments, please refer to the description in the comprehensive testing method for the SSD system disk in the above embodiments, which will not be repeated here.

[0172] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system-type embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0173] Please refer to Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. The computer device 70 includes a processor 71 and a memory 72 coupled to the processor 71.

[0174] The memory 72 stores a calculation program. When the computer program is executed by the processor 71, the processor 71 performs the steps of the comprehensive testing method for the SSD system disk in the above embodiment.

[0175] The processor 71 can also be referred to as a CPU (Central Processing Unit). The processor 71 may be an integrated circuit chip with signal processing capabilities. The processor 71 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0176] Please refer to Figure 7This is a schematic diagram of the structure of the storage medium provided in the embodiments of this application. The computer-readable storage medium of this application embodiment stores a computer program 80. The computer program 80 is executed by a processor to implement the artificial intelligence-based actuarial analysis method in the above embodiments. The computer program 80 can be stored in the storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or computer devices such as computers, servers, mobile phones, and tablets. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0178] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0179] The above embodiments are merely exemplary implementations used to illustrate the principles of the embodiments of this application; however, the embodiments of this application are not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the embodiments of this application, and these modifications and improvements are also considered to be within the protection scope of the embodiments of this application.

Claims

1. A method for comprehensive testing of an SSD system disk, characterized in that, The method comprises the following steps: The steps of taking an SSD system disk as a target test object, monitoring the electrical data of the SSD system disk in each running stage in a real use scenario, reversely deducing the core task type in the scenario, constructing an LTP test set adapted to the use characteristics and stress characteristics of the SSD system disk, and configuring the LTP test set to cover the system calls and boundary conditions of the target platform; Constructing a standardized test environment to execute the LTP test set, and synchronously collecting multi-dimensional data composed of the running state of the SSD system disk and the system running state; Recording preset test nodes, node association logs and abnormal event information to form test trace data and LTP test results; Correlation analysis is performed on the multi-dimensional data, test trace data and LTP test results to generate an evaluation result reflecting the running state stability, performance change characteristics and abnormal response characteristics of the SSD system disk under system call stress; The LTP test set adapted to the use characteristics and stress characteristics of the SSD system disk is constructed by obtaining instruction characteristics and environment information of the historical running of the SSD system disk, performing feature fusion on the instruction characteristics and environment information by using a graph neural network, generating a dependency relationship graph for screening and combining test cases in the LTP test subset, and forming the LTP test set.

2. The method of claim 1, wherein the SSD system disk is a flash memory disk. The LTP test set adapted to the use characteristics and stress characteristics of the SSD system disk is constructed by: Analyzing the electrical workload of the SSD system disk to determine its test range, and screening the corresponding LTP test subset; The LTP test subset includes at least one of file system and storage related tests, process and thread management tests, memory and I / O stress tests, boundary and abnormal tests, and system call combination tests.

3. The method of claim 2, wherein the SSD system disk is tested by using a plurality of test programs, and the test programs are executed in a test order determined by a test order table. The instruction characteristics include instruction types, execution frequencies, format specifications and interaction logic corresponding to SSD system disk file reading and writing, process scheduling, memory allocation and resource application; The environment information includes SSD system disk hardware parameters, operating system configuration, load fluctuation characteristics and system resource allocation rules.

4. The method of claim 1, wherein the SSD system disk is tested by using a plurality of test programs, and the test programs are executed in a test order determined by a test order table. The LTP test set is configured to cover the system calls and boundary conditions of the target platform, including: Parameter configuration is performed on the LTP test set, and the parameter configuration includes setting the number of concurrent threads and processes adapted to the running load of the SSD system disk, setting the duration of continuous running, enabling an error injection mechanism, and recording performance data; The error injection mechanism is used to simulate I / O errors, permission errors or abnormal errors such as full disk, and the performance data includes SSD system disk running state data and system resource occupation data.

5. The method of claim 1, wherein the SSD system disk is tested by using a plurality of test programs, and the test programs are executed in a test order determined by a test order table. The LTP test set is executed in a standardized test environment, and multi-dimensional data composed of the running state of the SSD system disk and the system running state are synchronously collected, including: Starting the test execution program corresponding to the LTP test set, recording the test start time, test parameters and process configuration, synchronously collecting the multi-dimensional data and ensuring the running stability of the SSD system disk through a monitoring mechanism; The multi-dimensional data includes SMART attributes of an SSD system disk, system-level I / O delay fluctuation, queue depth accumulation, CPU utilization, memory utilization, disk utilization, system call abnormal information, kernel log, and system response state. The monitoring mechanism includes concurrent task simulation, exception capture, and memory monitoring.

6. The comprehensive testing method for SSD system disks as described in claim 1, characterized in that, The recording includes preset test nodes, node-associated logs, and abnormal event information, forming test trace data and LTP test results, including: The state of the preset test nodes is retained, and the log information associated with the test nodes and the abnormal event information occurring during the test process are recorded; The test trace data are formed by the state retention, log information, and abnormal event information of the preset test nodes; The execution passing, failure, and corresponding error information of each test case in the LTP test set are collected to generate the LTP test results; The preset test nodes include test start time, test case execution time, abnormal time occurrence time, and long-time running time nodes. The log information includes LTP running logs, system logs, and SMART data snapshots, iostat periodic sampling data, and vmstat periodic sampling data. The abnormal event information includes abnormal occurrence time, abnormal phenomenon, corresponding test case, real-time state of the SSD system disk, and system response.

7. The comprehensive testing method for SSD system disks as described in claim 1, characterized in that, The correlation analysis of the multi-dimensional data, test trace data, and LTP test results generates evaluation results reflecting the running state stability, performance change characteristics, and abnormal response characteristics of the SSD system disk under system call pressure, including: Based on the test case passing rate, failure, and corresponding error information in the LTP test results, and in combination with the SMART attributes and system response state of the SSD system disk in the multi-dimensional data, the running state stability of the SSD system disk is evaluated; Based on the system-level I / O delay fluctuation, queue depth accumulation, CPU utilization, memory utilization, and disk utilization in the multi-dimensional data, the performance change characteristics of the SSD system disk under different pressure scenarios are evaluated; Based on the abnormal event information in the test trace data and the kernel log and system response state in the multi-dimensional data, the abnormal response characteristics of the SSD system disk under abnormal scenarios are evaluated.

8. A comprehensive test system for SSD system disks, characterized in that, The configuration unit is configured to take the SSD system disk as a target test object, monitor the electrical data of the SSD system disk in each running stage in a real use scenario, reversely deduce the core task type in the scenario, construct an LTP test set adapted to the use characteristics and pressure characteristics, and configure the LTP test set to cover the target platform system call and boundary conditions. The execution unit is configured to construct a standardized test environment to execute the LTP test set and synchronously collect multi-dimensional data composed of the running state of the SSD system disk and the system running state. The collection unit is configured to record preset test nodes, node-associated logs, and abnormal event information to form test trace data and LTP test results. ​ An analysis unit is configured to perform correlation analysis on the multidimensional data, test trace data and LTP test results, and generate evaluation results reflecting the running state stability, performance change characteristics and abnormal response characteristics of the SSD system disk under system call pressure. The LTP test set adapted to the use characteristics and pressure characteristics of the SSD system disk comprises: obtaining instruction characteristics and environment information of historical running of the SSD system disk; and performing feature fusion on the instruction characteristics and the environment information by using a graph neural network to generate a dependency graph for screening and combining test cases in an LTP test subset, so as to form the LTP test set.

9. A computer device, comprising: The computer device comprises a processor and a memory coupled to the processor, and the memory stores a computer program, which is executed by the processor to cause the processor to perform the steps of the comprehensive testing method of the SSD system disk according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, which is executed by the processor to implement the comprehensive testing method of the SSD system disk according to any one of claims 1-7.

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