Hardware basic service component test system

Abstract

The invention discloses a hardware basic service component test system, which comprises a test management module, a hardware simulation module, an automatic test module, a data acquisition module, a data analysis module, a report generation module and a feedback adjustment module, the hardware simulation module is used for simulating hardware environments under different load conditions; the automatic test module is used for executing predetermined test tasks; the data acquisition module is used for monitoring hardware states and performance data in real time; the data analysis module is used for analyzing the acquired data; abnormal behaviors are identified and performance is evaluated, a report generation module generates a test report, and a feedback adjustment module dynamically adjusts test parameters and resource allocation according to an analysis result. The hardware basic service component testing efficiency, accuracy and comprehensiveness are improved, and the method can be applied to the technical field of hardware testing.

Description

Technical Field

[0001] The present invention relates to the technical field of hardware testing, and in particular to a hardware basic service component testing system. Background Art

[0002] With the increasing complexity of hardware infrastructure and the diversification of application environments, the performance and stability of hardware components play a vital role in the normal operation of the system. In order to ensure that hardware components can withstand various loads and working conditions in actual operation, system developers and testers need to conduct comprehensive hardware testing, including functional testing, performance testing, and exception handling testing. Modern test systems usually use automated testing tools and real-time monitoring equipment to evaluate the status parameters and operating performance of hardware to detect the performance of hardware components under different workloads and ensure their stability and reliability in complex environments.

[0003] However, the existing technology still has many technical problems when testing hardware-based service components. First, traditional testing systems lack flexibility in resource allocation and cannot dynamically adjust the priority and resource usage of test tasks according to the importance and performance of hardware components, resulting in insufficient testing of key components and unreasonable resource allocation. Secondly, existing testing systems often lag behind in processing real-time feedback and are unable to adjust test parameters in a timely manner based on hardware performance fluctuations and abnormal detection results, resulting in insufficient accuracy and coverage of test results. In addition, the existing technology does not monitor abnormal behaviors comprehensively and cannot provide an effective dynamic optimization mechanism, resulting in poor flexibility and adaptability of the test process in complex test scenarios, affecting the efficiency and accuracy of the test. Summary of the invention

[0004] The purpose of the present invention is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0005] To this end, an object of an embodiment of the present invention is to provide a hardware basic service component testing system, which improves the efficiency, accuracy and comprehensiveness of hardware basic service component testing.

[0006] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present invention include:

[0007] The embodiment of the present invention provides a hardware basic service component testing system, including a test management module, a hardware simulation module, an automated testing module, a data acquisition module, a data analysis module, a report generation module and a feedback adjustment module, wherein:

[0008] The test management module is used to manage and schedule various test tasks. The test management module includes a task scheduling unit and a priority setting unit. The priority setting unit is used to allocate test resources according to the type, importance and performance of hardware components in historical test data. The task scheduling unit is used to automatically allocate and adjust resources according to the test plan and dynamically adjust the priority and task order according to real-time feedback;

[0009] The hardware simulation module is used to simulate the operating environment of the hardware basic service component and simulate the working state of the hardware component under different faults or high loads;

[0010] The automated testing module is used to execute predetermined test procedures, conduct comprehensive tests on hardware components through pre-written scripts, and dynamically adjust the test process based on real-time test feedback;

[0011] The data acquisition module is used to monitor and collect test data of the hardware components during the test process in real time, and the test data includes hardware status data, performance data, feedback data, abnormal data and behavior data;

[0012] The data analysis module is used to analyze and process the collected test data. The data analysis module includes an anomaly detection unit and a performance evaluation unit. The anomaly detection unit is used to analyze the hardware status data, performance data, feedback data and anomaly data collected during the test and identify abnormal behavior. The performance evaluation unit is used to analyze the performance of the hardware components and evaluate the performance indicators under different loads. The performance indicators include response time and throughput;

[0013] The report generation module is used to generate a test report based on the test data. The report generation module includes a data aggregation unit and a report output unit. The data aggregation unit is used to integrate the operation data of each module during the test process. The report output unit is used to automatically generate a test report containing performance analysis, abnormal statistics and optimization suggestions based on the operation data of each module;

[0014] The feedback adjustment module is used to dynamically adjust the test process according to the test results. The feedback adjustment module includes a parameter adjustment unit and a task reallocation unit. The parameter adjustment unit is used to adjust the test parameters according to the performance evaluation and anomaly detection results, and trigger parameter adjustment or task reallocation when the hardware performance or anomaly detection exceeds the set threshold. The task reallocation unit is used to reallocate test resources and tasks according to the feedback results.

[0015] Further, in one embodiment of the present invention, the allocating of test resources according to the type and importance of the hardware components and the performance in the historical test data specifically includes:

[0016] Classify the hardware components to obtain component types, where the component type is one of a processor, a memory, and an I / O interface. The hardware components of different component types correspond to different test requirements, and classify the type weights of various hardware components using predefined type weight rules;

[0017] Assign importance weights to hardware components based on their functions in the system, dependencies, and importance to the overall system;

[0018] Calculate the performance weights of hardware components based on performance indicators in historical test data;

[0019] The type weight, importance weight and performance weight are weighted to obtain the total priority of each hardware component, and the test resources are preliminarily allocated according to the total priority.

[0020] Further, in one embodiment of the present invention, the automatic allocation and adjustment of resources according to the test plan and the dynamic adjustment of priorities and task sequences according to real-time feedback specifically include:

[0021] Allocate resources to each test task based on the hardware components and overall priority specified in the test plan;

[0022] Trigger dynamic adjustments by monitoring the operating status of hardware components and the progress of test tasks;

[0023] After the dynamic adjustment is triggered, the priorities of the hardware components are re-evaluated and dynamically adjusted;

[0024] Based on the re-evaluated priorities, the execution order of the test tasks is adjusted.

[0025] Furthermore, in one embodiment of the present invention, the hardware simulation module specifically includes:

[0026] Virtual Processor Unit, which is used to simulate a multi-core processing environment, create a virtual multi-core system based on the architecture of a real processor, and generate instruction sets and cache behaviors similar to actual hardware to test the response time and load handling capabilities of the hardware in complex tasks;

[0027] Memory simulation unit, used to simulate the memory allocation and access mode of hardware, test the impact of different memory allocation strategies on component performance, and support fault injection during memory simulation to test the recovery ability of components under abnormal memory conditions;

[0028] I / O interface simulation unit, used to simulate the external communication interface of hardware components, test data transmission rate and delay, support simulation of multiple data transmission protocols, and test the stability of hardware in different communication environments;

[0029] The abnormal situation injection unit is used to simulate the working state of hardware components under fault or high load. The injected faults include overload, power outage and network interruption.

[0030] Furthermore, in one embodiment of the present invention, the automated testing module specifically includes:

[0031] The test script generation unit is used to automatically generate standardized test scripts according to the type, task and configuration of hardware components. The test scripts include instruction sets, resource calls, load test steps and input and output processes of test data. The test scripts support parallel operation and multi-task allocation, and can be tested on multiple hardware components at the same time.

[0032] The automated execution unit is used to automatically execute tests according to the generated test scripts, monitor the execution process in real time, and record errors, exceptions, and performance data during test execution;

[0033] The dynamic adjustment test unit is used to dynamically adjust the test process and reallocate tasks and resources according to the feedback data collected by the data acquisition module.

[0034] Furthermore, in one embodiment of the present invention, the data acquisition module specifically includes:

[0035] A hardware status data acquisition unit, used to acquire hardware status data of hardware components in real time, wherein the hardware status data includes temperature, voltage and processing speed;

[0036] A performance data collection unit, used to collect performance data of hardware components, wherein the performance data includes response time, throughput and I / O bandwidth;

[0037] A feedback data collection unit is used to collect feedback data by monitoring the load, resource usage and task progress during the test process;

[0038] Abnormal data acquisition unit, used to automatically monitor abnormal events of hardware components during the test, including system crashes, task timeouts, signal loss, and hardware failures. When a hardware component fails, an error log is automatically generated to record the time, location, and error information of the abnormality.

[0039] The behavior data acquisition unit is used to collect the switching of hardware components between different states, record the time of state switching, related resource consumption, and the number of tasks processed by the data acquisition module during the test, the completion rate and task allocation;

[0040] The data storage and management unit is used to store all collected hardware status data, performance data, feedback data, abnormal data and behavior data in chronological order.

[0041] Further, in one embodiment of the present invention, the hardware status data, performance data, feedback data and abnormal data collected during the test are analyzed to identify abnormal behavior, which specifically includes:

[0042] De-noise and standardize the collected test data to eliminate the impact of noise data, and sort the data using timestamps;

[0043] Define the criteria for abnormal behavior based on preset thresholds and rules;

[0044] Monitor the operating status of hardware components in real time and record abnormal behavior when test data exceeds preset thresholds;

[0045] The recorded abnormal behavior is written into the abnormal log, which includes the abnormal type, time, component number, specific manifestation of the abnormality and related performance data.

[0046] Further, in one embodiment of the present invention, the performance of the hardware components is analyzed to evaluate the performance indicators under different loads, which specifically includes:

[0047] Classify and sort the performance data collected by the data collection module to obtain response time data, throughput data, and CPU / memory usage data, and divide them by time period or task type;

[0048] Use the collected response time data to analyze the responsiveness of hardware components under different loads;

[0049] Identify performance bottlenecks or excessive load based on response time changes under different load conditions;

[0050] Analyze throughput trends based on throughput data, evaluate the system's data processing capabilities under different load conditions, and identify bandwidth bottlenecks or data transmission delays;

[0051] Generate a performance score for each hardware component based on the responsiveness analysis results and the throughput analysis results.

[0052] Further, in one embodiment of the present invention, the data aggregation unit is used to integrate data from the test management module, the automated test module, and the data acquisition module, and the aggregated data includes the performance of the hardware components, the anomaly detection results, and the task execution status;

[0053] The report output unit is used to automatically generate a test report including performance analysis, abnormal statistics and optimization suggestions based on the summary data, and the test report supports output in multiple formats.

[0054] Further, in one embodiment of the present invention, the parameter adjustment unit is used to monitor the performance of the hardware component in real time according to the performance evaluation and anomaly detection results, and trigger automatic adjustment of the test parameter when it is detected that the performance parameter exceeds a preset threshold;

[0055] The task reallocation unit is used to re-evaluate task priorities and adjust resource allocation according to real-time monitored resource usage and abnormality detection results;

[0056] Among them, the feedback adjustment module configures a feedback closed-loop mechanism, and the feedback closed-loop mechanism continuously optimizes the test strategy by analyzing the test results after parameter adjustment and task reallocation.

[0057] The advantages and beneficial effects of the present invention will be partly given in the following description, partly become apparent from the following description, or be understood through the practice of the present invention:

[0058] The present invention can reasonably allocate test resources according to the type, importance and performance of hardware components in historical test data through the coordinated work of the priority setting unit and the task scheduling unit. At the same time, it can dynamically adjust the priority and task order in combination with real-time feedback data to ensure that key hardware components have priority in obtaining resources under high load or abnormal conditions, greatly improving the utilization efficiency of test resources, reducing resource waste, and ensuring the efficient execution of test tasks; through the multi-source data acquisition of the data acquisition module and the performance evaluation and anomaly detection of the data analysis module, the state parameters such as temperature, voltage, processing speed, and performance indicators such as response time and throughput of the hardware components can be monitored and analyzed in real time. When the performance of the hardware component exceeds the set threshold or abnormal behavior occurs, the feedback adjustment module can trigger parameter adjustment and task reallocation to ensure that each component is fully tested under different working conditions, thereby improving the efficiency, accuracy and comprehensiveness of the testing of hardware basic service components. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solution in the embodiments of the present invention, the following introduction is made to the drawings required for use in the embodiments of the present invention. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solution of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 A structural block diagram of a hardware basic service component testing system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0062] In the description of the present invention, the meaning of "a plurality" is two or more than two. If there is a description of "a first" or "a second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those commonly understood by those skilled in the art.

[0063] Reference Figure 1 The embodiment of the present invention provides a hardware basic service component testing system, including a test management module, a hardware simulation module, an automated test module, a data acquisition module, a data analysis module, a report generation module and a feedback adjustment module, wherein:

[0064] The test management module is used to manage and schedule various test tasks. The test management module includes a task scheduling unit and a priority setting unit. The priority setting unit is used to allocate test resources according to the type, importance and performance of hardware components in historical test data. The task scheduling unit is used to automatically allocate and adjust resources according to the test plan and dynamically adjust the priority and task order according to real-time feedback;

[0065] The hardware simulation module is used to simulate the operating environment of the hardware basic service components and simulate the working status of the hardware components under different faults or high loads;

[0066] The automated testing module is used to execute predetermined test procedures, conduct comprehensive tests on hardware components through pre-written scripts, and dynamically adjust the test process based on real-time test feedback;

[0067] The data acquisition module is used to monitor and collect test data of hardware components in real time during the test process. The test data includes hardware status data, performance data, feedback data, abnormal data and behavior data;

[0068] The data analysis module is used to analyze and process the collected test data. The data analysis module includes an anomaly detection unit and a performance evaluation unit. The anomaly detection unit is used to analyze the hardware status data, performance data, feedback data and anomaly data collected during the test and identify abnormal behaviors. The performance evaluation unit is used to analyze the performance of hardware components and evaluate performance indicators under different loads. The performance indicators include response time and throughput.

[0069] The report generation module is used to generate a test report based on the test data. The report generation module includes a data summary unit and a report output unit. The data summary unit is used to integrate the operation data of each module during the test process. The report output unit is used to automatically generate a test report containing performance analysis, abnormal statistics and optimization suggestions based on the operation data of each module.

[0070] The feedback adjustment module is used to dynamically adjust the test process according to the test results. The feedback adjustment module includes a parameter adjustment unit and a task reallocation unit. The parameter adjustment unit is used to adjust the test parameters according to the performance evaluation and anomaly detection results, and trigger parameter adjustment or task reallocation when the hardware performance or anomaly detection exceeds the set threshold. The task reallocation unit is used to reallocate test resources and tasks according to the feedback results.

[0071] As a further optional implementation, test resources are allocated according to the type and importance of hardware components and performance in historical test data, which specifically includes:

[0072] Classify the hardware components to obtain component types, where the component type is one of a processor, a memory, and an I / O interface. Hardware components of different component types correspond to different test requirements. Classify the type weights of various hardware components using predefined type weight rules.

[0073] Assign importance weights to hardware components based on their functions in the system, dependencies, and importance to the overall system;

[0074] Calculate the performance weights of hardware components based on performance indicators in historical test data;

[0075] The type weight, importance weight and performance weight are weighted to obtain the total priority of each hardware component, and the test resources are preliminarily allocated according to the total priority.

[0076] Specifically, the priority setting unit allocates test resources according to the type and importance of the hardware components and the performance in the historical test data, including:

[0077] Type identification: The priority setting unit classifies hardware components into categories such as processors, memories, and I / O interfaces. Different types of components correspond to different test requirements. The priority setting unit uses predefined type weights W type Assign a priority to each type, expressed as:

[0078] P type =W type ×C type ;

[0079] Among them, P type is the type-based priority, Wtype is the preset type weight, C type Categorizes the value for the type of hardware component.

[0080] Importance Assessment: The priority setting unit assigns importance weights W to hardware components based on their functions, dependencies, and importance to the overall system. importance , expressed as:

[0081] P importance =W importance ×C importance ;

[0082] Among them, P importance is the priority based on importance, W importance is the importance weight, C importance Rate the importance of the component.

[0083] Performance analysis: Based on the performance indicators in the historical test data, including response time, throughput and failure rate, the priority setting unit calculates the performance priority P of the hardware components. performance , expressed as:

[0084]

[0085] Among them, P performance is the priority based on performance, W performance is the performance weight, T response is the response time of the component, F fault is the historical failure rate, S throughpur Score throughput.

[0086] Priority determination: Comprehensively weight type identification, importance assessment and performance analysis to obtain the total priority P total , expressed as:

[0087] P total =P type +P importance +P performance ;

[0088] According to the overall priority P total Make preliminary allocations of test resources, giving priority to testing high-priority hardware components.

[0089] As an optional implementation, resources are automatically allocated and adjusted according to the test plan, and priorities and task sequences are dynamically adjusted according to real-time feedback, which specifically includes:

[0090] Allocate resources to each test task based on the hardware components and overall priority specified in the test plan;

[0091] Trigger dynamic adjustments by monitoring the operating status of hardware components and the progress of test tasks;

[0092] After the dynamic adjustment is triggered, the priorities of the hardware components are re-evaluated and dynamically adjusted;

[0093] The execution order of test tasks is adjusted based on the re-evaluated priorities.

[0094] Specifically, the task scheduling unit automatically allocates and adjusts resources according to the test plan, and dynamically adjusts priorities and task sequences based on real-time feedback, including:

[0095] Initial resource allocation: The task scheduling unit allocates resources based on the hardware components and overall priority P specified in the test plan. iotal , allocate appropriate amount of resources (such as CPU, memory, I / O bandwidth) to each test task, expressed as:

[0096]

[0097] Among them, R initial is the initial resource allocation, T task is the time requirement of the test task, P total is the total priority of the corresponding component.

[0098] Real-time monitoring and feedback: The task scheduling unit monitors the operating status of hardware components and the progress of test tasks, receives feedback data collected by the data acquisition module, such as the load of hardware components, resource utilization, task completion time, etc., and triggers dynamic adjustment when one of the following situations is detected: the resource utilization of the test component exceeds the set threshold; the actual execution time of a test task significantly exceeds expectations; the performance or failure of the component is abnormal (such as prolonged response time or frequent failures).

[0099] Dynamically adjust the priority: After the dynamic adjustment is triggered, the priority setting unit re-evaluates the priority of the hardware component and makes dynamic adjustments, providing real-time feedback on the adjusted priority P adjust , expressed as:

[0100] P adjust =P total +(W real-time ×F real-time );

[0101] Among them, P adjust is the adjusted priority, W real-time is the real-time feedback weight, F real-i-me Provides real-time feedback data (such as anomaly detection, load changes).

[0102] Task order adjustment: The task scheduling unit adjusts the execution order of the test tasks according to the re-evaluated priorities to ensure that high-priority tasks are executed first when resources are limited. The rescheduling of tasks is expressed as:

[0103]

[0104] in, is the adjusted task priority order, T remaining is the remaining execution time of the task, P adjust The priority for recalculation.

[0105] If it is detected that resource utilization is too high or the execution time of a task exceeds expectations, the task scheduling unit automatically reallocates resources to ensure balanced execution of test tasks and avoid resource bottlenecks.

[0106] The embodiment of the present invention uses a comprehensive evaluation of the type, importance, and historical performance of the priority setting unit, as well as a real-time monitoring and dynamic adjustment mechanism of the task scheduling unit. The test management module can ensure the efficient use of test resources, and through dynamic priority adjustment and task sequence optimization, further improve the flexibility and execution efficiency of the test process, thereby ensuring the priority execution of key tasks.

[0107] As an optional implementation, the hardware simulation module specifically includes:

[0108] Virtual Processor Unit, which is used to simulate a multi-core processing environment, create a virtual multi-core system based on the architecture of a real processor, and generate instruction sets and cache behaviors similar to actual hardware to test the response time and load handling capabilities of the hardware in complex tasks;

[0109] Memory simulation unit, used to simulate the memory allocation and access mode of hardware, test the impact of different memory allocation strategies on component performance, and support fault injection during memory simulation to test the recovery ability of components under abnormal memory conditions;

[0110] I / O interface simulation unit, used to simulate the external communication interface of hardware components, test data transmission rate and delay, support simulation of multiple data transmission protocols, and test the stability of hardware in different communication environments;

[0111] The abnormal situation injection unit is used to simulate the working state of hardware components under fault or high load. The injected faults include overload, power outage and network interruption.

[0112] Specifically, the hardware simulation module simulates the operating environment of the hardware basic service component, including:

[0113] Virtual Processor Unit: The virtual processor unit simulates a multi-core processing environment, creates a virtual multi-core system based on the architecture of a real processor, supports concurrent processing tasks, and generates instruction sets and cache behaviors similar to actual hardware to test the response time and load handling capabilities of the hardware in complex tasks;

[0114] Memory simulation unit: The memory simulation unit simulates the memory allocation and access mode of the hardware to test the impact of different memory allocation strategies on component performance. The memory simulation process supports fault injection (such as memory leaks and access conflicts) to test the recovery ability of components under abnormal memory conditions.

[0115] I / O interface simulation unit: The I / O interface simulation unit simulates the external communication interface of the hardware component (such as network, storage, USB interface, etc.), tests the data transmission rate and delay, supports the simulation of multiple data transmission protocols (such as TCP / IP, PCIe), and tests the stability of the hardware in different communication environments;

[0116] Abnormal Situation Injection Unit: The abnormal situation injection unit simulates the working state of hardware components under fault or high load. The injected faults include overload, power failure, network interruption, and detect the performance of components under extreme conditions.

[0117] The hardware simulation module simulates complex hardware environments and injects abnormal situations to ensure the performance of hardware components under different load and fault conditions, and test their stability, robustness and response capabilities.

[0118] As an optional implementation, the automated testing module specifically includes:

[0119] The test script generation unit is used to automatically generate standardized test scripts according to the type, task and configuration of hardware components. The test scripts include instruction sets, resource calls, load test steps and input and output processes of test data. The test scripts support parallel operation and multi-task allocation, and can be tested on multiple hardware components at the same time.

[0120] The automated execution unit is used to automatically execute tests according to the generated test scripts, monitor the execution process in real time, and record errors, exceptions, and performance data during test execution;

[0121] The dynamic adjustment test unit is used to dynamically adjust the test process and reallocate tasks and resources according to the feedback data collected by the data acquisition module.

[0122] Specifically, the automated testing module executes a predetermined test procedure, including:

[0123] Test script generation: The test script generation unit automatically generates standardized test scripts based on the type, task, and configuration of hardware components. The test scripts include instruction sets, resource calls, load test steps, and the input and output processes of test data.

[0124] Automated execution: The automated execution unit automatically executes tests according to the generated test scripts. The test scripts support parallel operation and multi-task allocation to ensure that tests are performed on multiple hardware components simultaneously. The automated execution unit monitors the execution process in real time and records errors, exceptions, and performance data during test execution.

[0125] Dynamically adjust the test process: Based on the feedback data collected by the data acquisition module (such as response time, throughput, etc.), the automated testing module dynamically adjusts the test process and reallocates tasks and resources to address performance bottlenecks or anomalies found during testing;

[0126] The automated testing module ensures the automation and flexibility of the testing process by generating and executing dynamically adjusted test scripts, effectively improving the testing coverage and efficiency.

[0127] As an optional implementation, the data acquisition module specifically includes:

[0128] A hardware status data acquisition unit is used to acquire hardware status data of hardware components in real time, and the hardware status data includes temperature, voltage and processing speed;

[0129] A performance data collection unit is used to collect performance data of hardware components, including response time, throughput, and I / O bandwidth;

[0130] A feedback data collection unit is used to collect feedback data by monitoring the load, resource usage and task progress during the test process;

[0131] Abnormal data acquisition unit, used to automatically monitor abnormal events of hardware components during the test, including system crashes, task timeouts, signal loss, and hardware failures. When a hardware component fails, an error log is automatically generated to record the time, location, and error information of the abnormality.

[0132] The behavior data acquisition unit is used to collect the switching of hardware components between different states, record the time of state switching, related resource consumption, and the number of tasks processed by the data acquisition module during the test, the completion rate and task allocation;

[0133] The data storage and management unit is used to store all collected hardware status data, performance data, feedback data, abnormal data and behavior data in chronological order.

[0134] Specifically, the data acquisition module monitors and collects data from hardware components in real time, including:

[0135] Hardware status data collection: Real-time collection of hardware status data of hardware components. Hardware status data includes temperature, voltage, and processing speed, including:

[0136] Temperature: Monitor the operating temperature of hardware components in real time through built-in or external temperature sensors to ensure that the temperature operates within a safe range;

[0137] Voltage: The voltage detector is used to collect the working voltage of the hardware components and detect whether the voltage is stable and whether there is voltage fluctuation;

[0138] Processing speed: Collect the operating frequency of the hardware processor or other computing units, monitor their response speed under different loads, and ensure the stability of the hardware processing capacity;

[0139] Performance data collection: The signal monitoring unit collects performance data of hardware components. The performance data includes response time, throughput, and I / O bandwidth, among which;

[0140] Response time: records the time from input to output when a hardware component performs a task, and analyzes its response efficiency;

[0141] Throughput: monitors the amount of data processed by hardware components per unit time to evaluate their processing capabilities;

[0142] I / O bandwidth: The input / output data transmission rate of the acquisition hardware to ensure the efficiency of data transmission.

[0143] Feedback data collection: By monitoring the load, resource utilization and task progress during the test process, feedback data is collected and sent to the test management module and automated test module in real time for test resource allocation and dynamic adjustment of the test process.

[0144] Abnormal data collection: Automatically monitor abnormal events of hardware components during the test, including system crashes, task timeouts, signal loss, and hardware failures. Abnormal data is collected by the anomaly detector and synchronized to the data storage unit. When a hardware component fails, the data collection module automatically generates an error log to record the time, location, and error information of the abnormality, providing data support for subsequent fault analysis and troubleshooting.

[0145] Behavioral data collection: Collect the switching of hardware components between different states (such as idle, low load, high load, full load), record the time of state switching and related resource consumption, and the data collection module monitors the number of tasks processed by the hardware during the test, the completion rate and task allocation, to ensure a complete record of the task execution process.

[0146] Data storage and management: The data storage unit is responsible for storing all collected hardware status data, performance data, feedback data, abnormal data, and behavior data in chronological order.

[0147] The data acquisition module can efficiently collect and store hardware status data, performance data, feedback data, abnormal data and behavior data through the collaborative work of the signal monitoring unit and the data storage unit, ensuring the real-time, accuracy and completeness of data acquisition, and supporting the efficient operation and optimization decision-making of the entire test system.

[0148] As an optional implementation method, the hardware status data, performance data, feedback data and abnormal data collected during the test are analyzed to identify abnormal behaviors, which specifically includes:

[0149] De-noise and standardize the collected test data to eliminate the impact of noise data, and sort the data using timestamps;

[0150] Define the criteria for abnormal behavior based on preset thresholds and rules;

[0151] Monitor the operating status of hardware components in real time and record abnormal behavior when test data exceeds preset thresholds;

[0152] The recorded abnormal behavior is written into the abnormal log, which includes the abnormal type, time, component number, specific abnormal manifestation and related performance data.

[0153] Specifically, the anomaly detection unit analyzes the hardware status data, performance data, feedback data, and anomaly data collected during the test to identify abnormal behaviors, including:

[0154] Data preprocessing: De-noise and standardize the collected test data to eliminate the impact of noise data and ensure data quality. Use timestamps to sort the data to ensure that anomaly detection can be analyzed based on continuous time series.

[0155] Abnormal rule setting: Based on preset thresholds and rules, such as upper and lower limits of response time, temperature, voltage, and processing speed, define the judgment criteria for abnormal behavior. For example, when the response time of a hardware component exceeds a predetermined threshold, it is marked as abnormal.

[0156] Abnormal behavior detection: Real-time monitoring of the operating status of hardware components. When any data exceeds the preset threshold, abnormal behavior is recorded. Detected anomalies include over-temperature, voltage fluctuations, abnormal fluctuations in processing speed, and long response time.

[0157] Exception log recording: The recorded abnormal behavior is recorded in the exception log, which includes the exception type, time, component number, specific manifestation of the exception and related performance data.

[0158] The anomaly detection results are fed back to the test management module and feedback adjustment module in real time to dynamically adjust the priority, resource allocation and test process of test tasks to ensure that the problem components are fully tested.

[0159] As an optional implementation, the performance of the hardware components is analyzed to evaluate the performance indicators under different loads, which specifically includes:

[0160] Classify and sort the performance data collected by the data collection module to obtain response time data, throughput data, and CPU / memory usage data, and divide them by time period or task type;

[0161] Use the collected response time data to analyze the responsiveness of hardware components under different loads;

[0162] Identify performance bottlenecks or excessive load based on response time changes under different load conditions;

[0163] Analyze throughput trends based on throughput data, evaluate the system's data processing capabilities under different load conditions, and identify bandwidth bottlenecks or data transmission delays;

[0164] Generate a performance score for each hardware component based on the responsiveness analysis results and the throughput analysis results.

[0165] Specifically, the performance evaluation unit analyzes the performance of hardware components and evaluates performance indicators under different loads, including:

[0166] Performance data summary: Classify and organize the performance data collected by the data collection module, including response time, throughput, and CPU / memory usage, and divide them by time period or task type.

[0167] Response time analysis: Use the collected response time data to analyze the responsiveness of hardware components under different loads, expressed as:

[0168]

[0169] Among them, T average is the average response time, T i is the response time of the i-th task, and N is the total number of test tasks;

[0170] Identify performance bottlenecks or excessive load conditions based on how response times change under different load conditions.

[0171] Throughput analysis: The performance evaluation unit calculates the system throughput, analyzes the throughput change trend, evaluates the system's data processing capabilities under different load conditions, and identifies possible bandwidth bottlenecks or data transmission delays. The throughput calculation is expressed as:

[0172]

[0173] Among them, S throughput is the throughput, D total is the total amount of data, T total is the total time of data processing.

[0174] Performance indicator evaluation: Based on the comprehensive response time and throughput analysis results, the performance evaluation unit generates a performance score for each hardware component, expressed as:

[0175]

[0176] Among them, P performance Score the performance of hardware components, T average is the average response time, S throughput is the throughput, α and β are weight parameters, which are adjusted according to system requirements.

[0177] The performance of each component is determined based on the performance score, and a performance analysis report is generated. The performance evaluation results are fed back to the test management module and feedback adjustment module in real time to dynamically adjust the priority, resource allocation and test process of the test tasks to ensure that the problem components are fully tested.

[0178] The data analysis module can effectively identify potential problems in the test process through real-time monitoring of abnormal behaviors and comprehensive evaluation of hardware component performance, and provide important data support for system optimization and test adjustments. The flexibility and accuracy of the module ensure the efficient operation of the test system and the timely discovery of problems.

[0179] Further as an optional implementation, the data aggregation unit is used to integrate data from the test management module, the automated test module, and the data acquisition module, and the aggregated data includes the performance of the hardware components, the anomaly detection results, and the task execution status;

[0180] The report output unit is used to automatically generate a test report containing performance analysis, exception statistics and optimization suggestions based on the summary data. The test report supports output in multiple formats.

[0181] Specifically, the report generation module generates a test report based on the test data, including:

[0182] Data aggregation: The data aggregation unit integrates data from the test management module, automated test module, and data acquisition module. The aggregated data includes the performance of hardware components, anomaly detection results, and task execution status;

[0183] Automatically generate reports: The report output unit automatically generates test reports containing performance analysis, exception statistics and optimization suggestions based on the summary data. The test reports can be output in multiple formats (PDF, Excel, etc.) to meet the needs of different users.

[0184] The report generation module can provide complete test process records and performance analysis by summarizing and automatically generating reports, providing data support for the optimization of hardware testing.

[0185] As a further optional implementation, the parameter adjustment unit is used to monitor the performance of the hardware component in real time according to the performance evaluation and anomaly detection results, and trigger automatic adjustment of the test parameter when it is detected that the performance parameter exceeds a preset threshold;

[0186] The task reallocation unit is used to re-evaluate task priorities and adjust resource allocation based on real-time monitored resource usage and anomaly detection results;

[0187] Among them, the feedback adjustment module configures a feedback closed-loop mechanism, which continuously optimizes the test strategy by analyzing the test results after parameter adjustment and task redistribution.

[0188] Specifically, the feedback adjustment module dynamically adjusts the test process according to the test results, and includes a parameter adjustment unit and a task reallocation unit.

[0189] The parameter adjustment unit monitors the performance of hardware components in real time based on the performance evaluation and anomaly detection results. When it detects that the performance parameters exceed the preset threshold, it triggers the automatic adjustment of the test parameters and optimizes the test process, including:

[0190] Real-time monitoring and threshold judgment include:

[0191] (1) Obtaining feedback data: The parameter adjustment unit receives performance evaluation results and anomaly detection data from the data analysis module, including key indicators such as response time, throughput, failure rate, temperature, and voltage of hardware components;

[0192] (2) Threshold judgment: The received performance indicators are compared with the preset thresholds. If the performance or anomaly detection result of a hardware component exceeds the set threshold, the parameter adjustment process is triggered, which is expressed as:

[0193] ΔP=P current -P threshold ;

[0194] Among them, ΔP is the deviation value of the performance parameter, P current is the current hardware performance parameter, P ihreshold is the preset threshold parameter;

[0195] (3) Determine the adjustment condition: If ΔP exceeds a certain tolerance range, the parameter adjustment unit triggers the adjustment operation and modifies the parameters of the hardware component that exceeds the tolerance range;

[0196] The parameter adjustment process includes the following steps:

[0197] (1) Determine adjustment parameters: Based on the threshold deviation, the parameter adjustment unit determines the type of parameter that needs to be adjusted (such as response time, throughput, voltage, temperature, etc.):

[0198] (2) Execute parameter adjustment: adjust the test parameters using the following formula:

[0199] P new =P current -K×ΔP;

[0200] Among them, P new is the performance parameter after adjustment, K is the adjustment coefficient, which is used to control the adjustment range and prevent over-adjustment, and ΔP is the deviation value;

[0201] The adjusted parameters will be applied to the next test cycle to optimize the testing process.

[0202] The task reallocation unit re-evaluates task priorities and adjusts resource allocation based on real-time monitored resource usage and anomaly detection results, including:

[0203] (1) Task redistribution conditions include:

[0204] Monitoring resource utilization: The task redistribution unit monitors the resource usage of hardware components during the test in real time (such as CPU, memory, I / O bandwidth, etc.);

[0205] Anomaly detection triggers reallocation: When the anomaly detection unit detects frequent hardware component failures or the current resource utilization exceeds the set upper threshold, the task reallocation process is triggered;

[0206] (2) The task redistribution process includes:

[0207] Determine task priority: The task reallocation unit reallocates test tasks based on the re-evaluated priorities, giving priority to allocating resources to critical and high-failure-rate hardware components. The reallocation formula is expressed as:

[0208]

[0209] Among them, T priorityis the priority of the reallocated tasks, T remaining is the remaining execution time of the task, P adjust Adjusted priorities based on performance and feedback;

[0210] Allocate test resources: Reallocate resources according to the adjusted priorities to ensure that high-priority tasks get more CPU, memory, or I / O resources, maximizing the execution efficiency of test tasks, expressed as:

[0211] R adjust =R initial +ΔR;

[0212] Among them, R adjust is the adjusted resource allocation, R initial is the initial resource allocation, and ΔR is the resource increment calculated based on feedback and priority changes.

[0213] In addition, the feedback adjustment module is configured with a feedback closed-loop mechanism, which continuously optimizes the test strategy and improves the efficiency and coverage of the test process by analyzing the test results after parameter adjustment and task redistribution.

[0214] The feedback adjustment module can dynamically optimize the test process according to performance evaluation and anomaly detection results through real-time monitoring, parameter adjustment and task reallocation mechanisms, ensure reasonable allocation of resources, reduce performance bottlenecks, improve test efficiency and system coverage. At the same time, the feedback closed-loop mechanism enables the system to continuously optimize itself according to the test results.

[0215] It can be recognized that the present invention can reasonably allocate test resources according to the type, importance and performance of hardware components in historical test data through the coordinated work of the priority setting unit and the task scheduling unit. At the same time, it can dynamically adjust the priority and task order in combination with real-time feedback data to ensure that key hardware components have priority in obtaining resources under high load or abnormal conditions, greatly improving the utilization efficiency of test resources, reducing resource waste, and ensuring the efficient execution of test tasks; through the multi-source data acquisition of the data acquisition module and the performance evaluation and anomaly detection of the data analysis module, the state parameters such as temperature, voltage, processing speed, and performance indicators such as response time and throughput of the hardware components can be monitored and analyzed in real time. When the performance of the hardware component exceeds the set threshold or abnormal behavior occurs, the feedback adjustment module can trigger parameter adjustment and task reallocation to ensure that each component is fully tested under different working conditions, thereby improving the efficiency, accuracy and comprehensiveness of the testing of hardware basic service components.

[0216] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0217] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0218] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A hardware basic service component testing system, characterized in that: It includes test management module, hardware simulation module, automated test module, data acquisition module, data analysis module, report generation module and feedback adjustment module, among which: The test management module is used to manage and schedule various test tasks. The test management module includes a task scheduling unit and a priority setting unit. The priority setting unit is used to allocate test resources according to the type, importance and performance of hardware components in historical test data. The task scheduling unit is used to automatically allocate and adjust resources according to the test plan and dynamically adjust the priority and task order according to real-time feedback; The hardware simulation module is used to simulate the operating environment of the hardware basic service component and simulate the working state of the hardware component under different faults or high loads; The automated testing module is used to execute predetermined test procedures, conduct comprehensive tests on hardware components through pre-written scripts, and dynamically adjust the test process based on real-time test feedback; The data acquisition module is used to monitor and collect test data of the hardware components during the test process in real time, and the test data includes hardware status data, performance data, feedback data, abnormal data and behavior data; The data analysis module is used to analyze and process the collected test data. The data analysis module includes an anomaly detection unit and a performance evaluation unit. The anomaly detection unit is used to analyze the hardware status data, performance data, feedback data and anomaly data collected during the test and identify abnormal behavior. The performance evaluation unit is used to analyze the performance of the hardware components and evaluate the performance indicators under different loads. The performance indicators include response time and throughput; The report generation module is used to generate a test report based on the test data. The report generation module includes a data aggregation unit and a report output unit. The data aggregation unit is used to integrate the operation data of each module during the test process. The report output unit is used to automatically generate a test report containing performance analysis, abnormal statistics and optimization suggestions based on the operation data of each module; The feedback adjustment module is used to dynamically adjust the test process according to the test results. The feedback adjustment module includes a parameter adjustment unit and a task reallocation unit. The parameter adjustment unit is used to adjust the test parameters according to the performance evaluation and anomaly detection results, and trigger parameter adjustment or task reallocation when the hardware performance or anomaly detection exceeds the set threshold. The task reallocation unit is used to reallocate test resources and tasks according to the feedback results.

2. A hardware basic service component testing system according to claim 1, characterized in that: The allocating of test resources according to the type and importance of hardware components and the performance in historical test data specifically includes: Classify the hardware components to obtain component types, where the component type is one of a processor, a memory, and an I / O interface. The hardware components of different component types correspond to different test requirements, and classify the type weights of various hardware components using predefined type weight rules; Assign importance weights to hardware components based on their functions in the system, dependencies, and importance to the overall system; Calculate the performance weights of hardware components based on performance indicators in historical test data; The type weight, importance weight and performance weight are weighted to obtain the total priority of each hardware component, and the test resources are preliminarily allocated according to the total priority.

3. A hardware basic service component testing system according to claim 1, characterized in that: The automatic allocation and adjustment of resources according to the test plan and the dynamic adjustment of priorities and task sequences according to real-time feedback specifically include: Allocate resources to each test task based on the hardware components and overall priority specified in the test plan; Trigger dynamic adjustments by monitoring the operating status of hardware components and the progress of test tasks; After the dynamic adjustment is triggered, the priorities of the hardware components are re-evaluated and dynamically adjusted; The execution order of test tasks is adjusted based on the re-evaluated priorities.

4. A hardware basic service component testing system according to claim 1, characterized in that: The hardware simulation module specifically includes: Virtual Processor Unit, which is used to simulate a multi-core processing environment, create a virtual multi-core system based on the architecture of a real processor, and generate instruction sets and cache behaviors similar to actual hardware to test the response time and load handling capabilities of the hardware in complex tasks; Memory simulation unit, used to simulate the memory allocation and access mode of hardware, test the impact of different memory allocation strategies on component performance, and support fault injection during memory simulation to test the recovery ability of components under abnormal memory conditions; I / O interface simulation unit, used to simulate the external communication interface of hardware components, test data transmission rate and delay, support simulation of multiple data transmission protocols, and test the stability of hardware in different communication environments; The abnormal situation injection unit is used to simulate the working state of hardware components under fault or high load. The injected faults include overload, power outage and network interruption.

5. A hardware basic service component testing system according to claim 1, characterized in that: The automated testing module specifically includes: The test script generation unit is used to automatically generate standardized test scripts according to the type, task and configuration of hardware components. The test scripts include instruction sets, resource calls, load test steps and input and output processes of test data. The test scripts support parallel operation and multi-task allocation, and can be tested on multiple hardware components at the same time. The automated execution unit is used to automatically execute tests according to the generated test scripts, monitor the execution process in real time, and record errors, exceptions, and performance data during test execution; The dynamic adjustment test unit is used to dynamically adjust the test process and reallocate tasks and resources according to the feedback data collected by the data acquisition module.

6. A hardware basic service component testing system according to claim 1, characterized in that: The data acquisition module specifically includes: A hardware status data acquisition unit, used to acquire hardware status data of hardware components in real time, wherein the hardware status data includes temperature, voltage and processing speed; A performance data collection unit, used to collect performance data of hardware components, wherein the performance data includes response time, throughput and I / O bandwidth; A feedback data collection unit is used to collect feedback data by monitoring the load, resource usage and task progress during the test process; Abnormal data acquisition unit, used to automatically monitor abnormal events of hardware components during the test, including system crashes, task timeouts, signal loss, and hardware failures. When a hardware component fails, an error log is automatically generated to record the time, location, and error information of the abnormality. The behavior data acquisition unit is used to collect the switching of hardware components between different states, record the state switching time, related resource consumption, and the number of tasks, completion rate and task allocation processed by the data acquisition module during the test; The data storage and management unit is used to store all collected hardware status data, performance data, feedback data, abnormal data and behavior data in chronological order.

7. A hardware basic service component testing system according to claim 1, characterized in that: The hardware status data, performance data, feedback data and abnormal data collected during the test are analyzed to identify abnormal behaviors, which specifically includes: De-noise and standardize the collected test data to eliminate the impact of noise data, and sort the data using timestamps; Define the criteria for abnormal behavior based on preset thresholds and rules; Monitor the operating status of hardware components in real time and record abnormal behavior when test data exceeds preset thresholds; The recorded abnormal behavior is written into the abnormal log, which includes the abnormal type, time, component number, specific manifestation of the abnormality and related performance data.

8. A hardware basic service component testing system according to claim 1, characterized in that: The performance of the hardware components is analyzed to evaluate the performance indicators under different loads, which specifically includes: Classify and sort the performance data collected by the data collection module to obtain response time data, throughput data, and CPU / memory usage data, and divide them by time period or task type; Use the collected response time data to analyze the responsiveness of hardware components under different loads; Identify performance bottlenecks or excessive load based on response time changes under different load conditions; Analyze throughput trends based on throughput data, evaluate the system's data processing capabilities under different load conditions, and identify bandwidth bottlenecks or data transmission delays; Generate a performance score for each hardware component based on the responsiveness analysis results and the throughput analysis results.

9. A hardware basic service component testing system according to claim 1, characterized in that: The data aggregation unit is used to integrate data from the test management module, the automated test module, and the data acquisition module. The aggregated data includes the performance of hardware components, anomaly detection results, and task execution status; The report output unit is used to automatically generate a test report including performance analysis, abnormal statistics and optimization suggestions based on the summary data, and the test report supports output in multiple formats.

10. A hardware basic service component testing system according to any one of claims 1 to 9, characterized in that: The parameter adjustment unit is used to monitor the performance of the hardware components in real time according to the performance evaluation and anomaly detection results, and trigger automatic adjustment of the test parameters when it is detected that the performance parameters exceed the preset threshold; The task reallocation unit is used to re-evaluate task priorities and adjust resource allocation according to real-time monitored resource usage and abnormality detection results; Among them, the feedback adjustment module configures a feedback closed-loop mechanism, and the feedback closed-loop mechanism continuously optimizes the test strategy by analyzing the test results after parameter adjustment and task reallocation.

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