Core board cross-platform function testing and verification method

Abstract

The present invention relates to the technical field of core board testing, and specifically relates to a method for cross-platform function testing and verification of a core board, including the following steps: building a test environment for multiple operating systems and hardware platforms through virtualization technology or actual hardware, automatically generating cross-platform compatible test scripts based on the functional requirements of the core board, supporting multi-platform operation, parallelly executing the test scripts on each platform, recording and analyzing the running logs and output results; verifying the functional consistency on different platforms through a hash comparison algorithm to ensure that the core board has the same functional performance in a multi-platform environment, performing performance testing on each platform, identifying performance bottlenecks, and optimizing through a tuning tool; finally, verifying the effect of the repair through fault location and regression testing, and automatically generating a test report. The present invention improves the efficiency of cross-platform testing of the core board, the accuracy of function verification, and the effect of performance tuning, and is applicable to the testing and optimization scenarios of the core board in a complex multi-platform environment.

Description

Technical Field

[0001] The present invention relates to the technical field of core board testing, and particularly to a cross-platform function testing and verification method for core boards. Background Art

[0002] With the wide application of embedded systems, Internet of Things devices, and intelligent terminals, as the core component of these devices, the functional stability and performance of the core board directly affect the operation effect of the entire system. In a multi-platform environment, the core board needs to support different operating systems (such as Linux, Windows, Android) and hardware architectures (such as ARM, x86) to meet the requirements of different application scenarios. To ensure the functional consistency and performance optimization of the core board on multiple platforms, cross-platform function testing and performance tuning have become key links in product development.

[0003] Existing cross-platform testing solutions have many deficiencies in handling the environment setup of multiple operating systems and multiple hardware architectures, automatic script generation, and verification of test result consistency. First, the configuration of the test environment is complex and difficult to ensure consistency, and the manually built environment is easily interfered by human factors. Second, existing automated test scripts are difficult to adapt to the differences between different platforms, resulting in poor script portability and unable to ensure consistent operation on different platforms. In addition, existing function verification is mostly based on simple result comparison, lacking an efficient verification method, especially lacking accurate verification means for the consistency of cross-platform output data. At the same time, performance testing and tuning are usually only carried out for a single platform, lacking a unified optimization means for performance bottlenecks under multiple platforms and unable to comprehensively improve the performance of the system in a multi-platform environment. Summary of the Invention

[0004] The present invention provides a cross-platform function testing and verification method for core boards.

[0005] The cross-platform function testing and verification method for core boards includes the following steps:

[0006] S1, Initialization of the multi-platform environment: Create a test environment for multiple operating systems and hardware platforms through virtualization technology or actual hardware. The multiple operating systems include Linux, Windows, and Android, and the hardware platforms include ARM and x86 architectures. Create and destroy the platform environment through a unified interface management.

[0007] S2, Automatic generation of test scripts: Based on the functional requirements of the core board, use a script generation engine to automatically generate cross-platform compatible test scripts, and the script language supports multi-platform operation.

[0008] S3, Multi-platform Function Test Execution: Execute the generated test scripts in parallel on each test platform, record the running logs and result outputs of each platform during the test, monitor the function execution of each platform in real time through a log analysis tool, and generate a function execution report for each platform;

[0009] S4, Function Consistency Verification: Compare and analyze the test results of different platforms to verify whether the function performance of the core board is consistent on different platforms, and use a hash comparison algorithm to verify the consistency of the output data;

[0010] S5, Performance Testing and Tuning: Based on the function test, test the performance of each platform, including CPU occupancy, memory usage, and response time, and analyze and optimize the performance bottlenecks through a performance tuning tool;

[0011] S6, Fault Location and Regression Testing: Use the method of regression testing to reproduce the function or performance problems found during the test, combine a fault location tool to locate the problems, and verify whether the problems are completely solved through regression testing after fixing the problems;

[0012] S7, Automatic Report Generation of Test Results: Summarize and analyze the test results of all platforms through a test management platform to generate a cross-platform function test and verification report, which includes function test results, performance test results, and fault analysis reports.

[0013] Optionally, the S1 specifically includes:

[0014] S11, Build a virtualization environment for multiple operating systems through virtualization technology. The operating systems include Linux, Windows, and Android, and the virtualization tools support KVM, VMware, VirtualBox, etc.;

[0015] S12, Build test platforms based on different hardware architectures through actual hardware devices. The hardware architectures include ARM and x86, and the specific devices are such as Raspberry Pi (ARM architecture) and Intel / AMD (x86 architecture);

[0016] S13, Through a unified interface management system, automatically create and destroy the test environments of each virtual machine instance or actual hardware to ensure the consistency and repeatability of each test environment. The unified interface is implemented based on Docker or Kubernetes;

[0017] S14: In the created test environment, install and configure the dependency libraries and driver programs required for the test to ensure that the test environment is consistent with the target actual environment.

[0018] Optionally, S2 specifically includes:

[0019] S21. Input the test case specification into the script generation engine based on the functional requirements of the core board, and analyze the functional requirement characteristics of the core board.

[0020] S22. The script generation engine automatically generates scripts compatible with different platforms according to the differences of different platforms, such as file path formats, API call methods, and hardware resource access methods.

[0021] S23. Select a script language that supports multi-platform operation, such as Python, Bash, Powershell, etc., to ensure that the same set of scripts can run on Linux, Windows, and Android platforms.

[0022] S24: The generated test script contains a platform difference processing module, and uses conditional branching or preprocessing mechanisms to automatically adapt to the system characteristics of different platforms.

[0023] S25: Simulate user operations or functional operations of the core board through the script, and automatically generate test data and expected results.

[0024] Optionally, S3 specifically includes:

[0025] S31. Deploy the automatically generated test script to the test environments of each operating system (Linux, Windows, and Android) and hardware platforms to ensure that the same script version is used on each platform.

[0026] S32. Execute the test script in parallel on different hardware platforms, use multi-threading or multi-process technology to improve the test efficiency, and record the test logs of each hardware platform, including script execution time, error logs, and output results.

[0027] S33. Use a log collection tool to centralize the log files of each platform on a unified log analysis platform, and monitor the functional execution status of each hardware platform in real time.

[0028] S34. Generate a preliminary test report, recording the functional execution results and abnormal situations of each hardware platform.

[0029] Optionally, S4 specifically includes:

[0030] S41. Format the test output results of each hardware platform to ensure that the result data types and output formats of different hardware platforms are consistent.

[0031] S42. Perform consistency verification on the output data based on the hash comparison algorithm.

[0032] S43. If the hash values are the same, it indicates that the output data is the same. If the hash values are different, it is marked as a functional inconsistency, and the reason for the difference is analyzed.

[0033] S44. Generate a functional consistency verification report, record the verification results of each hardware platform, and perform a difference analysis based on the results of the hash comparison algorithm.

[0034] Optionally, the S5 specifically includes:

[0035] S51. While performing functional tests on each hardware platform, use performance monitoring tools (such as Prometheus, Grafana) to monitor the system resource usage in real time, including CPU occupancy, memory usage, and I / O response time.

[0036] S52. Calculate the performance bottleneck based on the performance data of different hardware platforms.

[0037] S53. Use performance tuning tools to optimize the platforms with performance bottlenecks, such as adjusting the number of threads, optimizing the memory allocation strategy, etc.

[0038] S54. Record the results of performance tests and tuning, and generate a performance test report.

[0039] Optionally, the S6 specifically includes:

[0040] S61. Analyze the abnormal logs found during the functional or performance tests through a log analysis tool to locate the specific fault points.

[0041] S62. Use a problem reproduction tool to repeat the test scenarios with problems to ensure the reproducibility of the problems.

[0042] S63. Repair the located functional or performance problems, and re-execute the corresponding test cases for regression testing to verify whether the problems are solved.

[0043] S64. Compare the results of the regression testing with the initial test results to ensure that other functions are not affected after the problems are repaired.

[0044] Optionally, the S7 specifically includes:

[0045] S71. Summarize the test results of functional tests, performance tests, and fault location of all hardware platforms through a test management platform.

[0046] S72. Automatically analyze the summarized data to generate functional test results, performance test results, and fault analysis reports.

[0047] S73. Automatically generate a cross-platform functional test and verification report, including detailed test data, test results, anomaly analysis, and optimization suggestions;

[0048] S74. Output the report in PDF or HTML format for easy viewing and sharing.

[0049] Optionally, in S53, use a performance tuning tool to optimize the platform with performance bottlenecks, specifically including:

[0050] Determine the performance bottleneck: Use a performance monitoring tool (such as Prometheus, Grafana, top, htop, perf, etc.) to identify the parts of the system with abnormal resource consumption and determine possible performance bottlenecks;

[0051] CPU bottleneck: For the CPU bottleneck, analyze the number of threads and CPU binding issues;

[0052] Memory bottleneck: For the memory bottleneck, analyze the memory allocation efficiency and memory leak issues;

[0053] I / O bottleneck: For the I / O bottleneck, analyze the disk read / write performance and network transmission performance;

[0054] CPU optimization: Adjust the number of threads and use multiple cores to balance the CPU load and improve utilization;

[0055] Memory optimization: Optimize the memory allocation strategy, reduce garbage collection pauses, and fix memory leak issues;

[0056] I / O optimization: Optimize I / O performance through asynchronous I / O operations and increase I / O throughput;

[0057] Network optimization: Adjust network parameters and use load balancing to reduce network latency and improve network performance;

[0058] Verification optimization: Rerun the test, observe the performance after optimization, ensure the effectiveness of the optimization plan, and verify whether the performance of the optimized system meets the expectations;

[0059] Generate a report: Generate a performance tuning report, recording the changes in various indicators before and after optimization, such as the shortening of response time and the reduction of CPU usage, etc.

[0060] Advantages of the present invention:

[0061] The present invention combines virtualization technology with actual hardware to construct a test environment for multiple platforms, supporting Linux, Windows, and Android operating systems as well as ARM and x86 architectures. The creation and destruction of the platform environment are managed through a unified interface, ensuring the consistency and repeatability of the test environment for each platform. This solution supports automation in environment setup, reduces the complexity of manually configuring the test environment, improves the flexibility of the test environment, and facilitates the rapid deployment and reuse of the test environment on multiple platforms.

[0062] The present invention adopts the method of automatic script generation and parallel test execution, enabling the rapid and efficient verification of the functional tests of the core board on different platforms. The consistency of the output data is verified through a hash comparison algorithm, ensuring the consistency of the core functions in a cross-platform environment. At the same time, with the help of performance tuning tools, real-time performance monitoring and analysis are carried out on each platform to discover and optimize performance bottlenecks, especially targeted tuning in aspects such as CPU, memory, and I / O, ensuring the performance stability and optimal state of each platform under different resource consumption conditions.

[0063] The present invention automatically generates cross-platform functional and performance test reports through a test management platform, covering functional test results, performance tuning analysis, and fault diagnosis reports, forming a complete test data tracking and analysis link. The combination of fault location and regression testing constructs a closed-loop mechanism for problem discovery, location, repair, and verification, effectively ensuring the stability of the system's functions and performance after problem repair. At the same time, the generation of automated reports further improves the visualization, sharing, and management efficiency of test results, optimizing the transparency and feedback speed of the cross-platform test process. Description of the Drawings

[0064] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0065] Figure 1 It is a schematic diagram of the method flow of the embodiment of the present invention;

[0066] Figure 2 It is a schematic diagram of the S2 process of the embodiment of the present invention. Detailed Embodiments

[0067] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, the accompanying drawings are only for more specifically describing the embodiments and are not intended to specifically limit the present invention.

[0068] It should be noted that in the specification, when referring to "an embodiment", "embodiment", "exemplary embodiment", "some embodiments", etc., it indicates that the described embodiment may include specific features, structures or characteristics, but not necessarily every embodiment includes such specific features, structures or characteristics. Additionally, when combining embodiments to describe specific features, structures or characteristics, implementing such features, structures or characteristics in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

[0069] Generally, terms can be understood at least in part from their use in context. For example, at least in part depending on the context, the term "one or more" used herein can be used to describe any feature, structure or characteristic in a singular sense, or can be used to describe a combination of features, structures or characteristics in a plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey a set of exclusive factors, but rather, at least in part depending on the context, can allow for the existence of other factors that may not be explicitly described.

[0070] As Figure 1 - Figure 2 shown, the core board cross-platform function test and verification method includes the following steps:

[0071] S1, Initialization of multi-platform environment: Build a test environment for multiple operating systems and hardware platforms through virtualization technology or actual hardware. The multiple operating systems include Linux, Windows, and Android, and the hardware platforms include ARM and x86 architectures. Create and destroy the platform environment through a unified interface to ensure the consistency of the test environment under different platforms.

[0072] S2, Automatic generation of test scripts: Based on the core board function requirements, use a script generation engine to automatically generate cross-platform compatible test scripts. The script language supports multi-platform operation, and the script generation process takes into account the differences between different platforms to ensure that the test cases can run consistently on different platforms.

[0073] S3, Execution of multi-platform function tests: Execute the generated test scripts in parallel on each test platform, record the running logs and result outputs of each platform during the test, use a log analysis tool to monitor the function execution of each platform in real time, and generate a function execution report for each platform.

[0074] S4, Functional Consistency Verification: Compare and analyze the test results of different platforms to verify whether the functional performance of the core board is consistent on different platforms. Use the hash comparison algorithm to verify the consistency of the output data to ensure the functional consistency of the core board in a multi-platform environment;

[0075] S5, Performance Testing and Tuning: Based on the functional testing, test the performance of each platform, including CPU occupancy, memory usage, and response time. Analyze and optimize the performance bottlenecks through performance tuning tools;

[0076] S6, Fault Location and Regression Testing: Use the regression testing method to reproduce the functional or performance problems found during the testing process. Combine the fault location tool to locate the problems, and verify whether the problems are completely solved through the regression testing after fixing the problems;

[0077] S7, Automated Report Generation of Test Results: Summarize and analyze the test results of all platforms through the test management platform to generate a cross-platform functional test and verification report. The report includes functional test results, performance test results, and fault analysis reports.

[0078] S1 specifically includes:

[0079] S11, Build a virtualization environment for multiple operating systems through virtualization technology. The operating systems include Linux, Windows, and Android, and the virtualization tools support KVM, VMware, VirtualBox, etc.;

[0080] S12, Build a test platform based on different hardware architectures through actual hardware devices. The hardware architectures include ARM and x86, and the specific devices are such as Raspberry Pi (ARM architecture) and Intel / AMD (x86 architecture);

[0081] S13, Through a unified interface management system, automatically create and destroy the test environments of each virtual machine instance or actual hardware to ensure the consistency and repeatability of each test environment. The unified interface is implemented based on Docker or Kubernetes;

[0082] S14: In the created test environment, install and configure the dependency libraries and driver programs required for testing to ensure that the test environment is consistent with the target actual environment;

[0083] Through the initialization of the multi-platform environment, ensure that a consistent test environment is built on different operating systems and hardware platforms. The combination of virtualization technology and actual hardware improves the flexibility and reusability of the test environment.

[0084] S2 specifically includes:

[0085] S21. Input the test case specification into the script generation engine based on the functional requirements of the core board, and analyze the functional requirement characteristics of the core board.

[0086] S22. The script generation engine automatically generates scripts compatible with different platforms according to the differences of different platforms, such as file path formats, API call methods, and hardware resource access methods.

[0087] S23. Select a script language that supports multi-platform operation, such as Python, Bash, Powershell, etc., to ensure that the same set of scripts can run on Linux, Windows, and Android platforms.

[0088] S24: The generated test scripts contain a platform difference processing module, which automatically adapts to the system characteristics of different platforms by using conditional branches or preprocessing mechanisms.

[0089] S25: Simulate user operations or functional operations of the core board through scripts, and automatically generate test data and expected results to ensure the consistency of test cases.

[0090] By automatically generating test scripts compatible with different platforms, the workload of manually writing scripts is reduced, and at the same time, the consistency and portability among platforms are ensured.

[0091] S3 specifically includes:

[0092] S31. Deploy the automatically generated test scripts to the test environments of each operating system (Linux, Windows, and Android) and hardware platforms to ensure that the same script version is used on each platform.

[0093] S32. Execute the test scripts in parallel on different hardware platforms, use multi-threaded or multi-process technologies to improve the test efficiency, and record the test logs of each hardware platform, including script execution time, error logs, and output results.

[0094] S33. Through the log collection tool, collect the log files of each platform on a unified log analysis platform to monitor the functional execution status of each hardware platform in real time.

[0095] S34. Generate a preliminary test report, recording the functional execution results and abnormal situations of each hardware platform.

[0096] By executing the test scripts in parallel on different platforms, the test efficiency is improved, the functional execution status of each platform is ensured to be monitored in real time, and the complexity of cross-platform testing is reduced.

[0097] S4 specifically includes:

[0098] S41. Format the test output results of each hardware platform to ensure that the result data types and output formats of different hardware platforms are consistent;

[0099] S42. Perform consistency verification on the output data based on the hash comparison algorithm. Calculate the hash values of the output results of each platform using the MD5 or SHA256 hash function;

[0100] Let the output data of each platform be D i , where i represents different platforms (such as Linux, Windows, Android, etc.). The calculation formula for the hash value is expressed as:

[0101] H i = H(D i );

[0102] Among them, H i represents the hash value of the output data D i on the i-th platform. H is the hash function used (such as MD5 or SHA-256), and D i represents the output data generated on the i-th platform;

[0103] To verify whether the output data on each platform is consistent, it is necessary to compare the hash values of different platforms. The formula for consistency verification is expressed as:

[0104]

[0105] That is, if the hash values H i and H j are equal, then the output data D i and D j of platform i and platform j are considered to be consistent. If the hash values are not equal, it is considered that there are differences in the output data;

[0106] Among them, D i is the output data generated by the i-th platform, usually the result data of the core board function test or performance test, which can be a log file, operation output, measurement data, etc. H is the hash function used to convert the output data D i into a fixed-length hash value. Commonly used hash functions include: MD5 generates a 128-bit hash value, which is suitable for fast calculation but has low security. SHA-256 generates a 256-bit hash value, which has high security and is suitable for scenarios with strict requirements for data consistency. H i is the hash value of the i-th platform, representing the fixed-length value generated after the output data D i on platform i is processed by the hash function H. i and j represent different platform numbers. For example, i = 1 represents the Linux platform and j = 2 represents the Windows platform;

[0107] S43. If the hash values are the same, it means the output data is the same. If the hash values are different, it is marked as a functional inconsistency, and the reasons for the differences are analyzed. The consistency verification process is as follows:

[0108] (1) Calculate the hash value: For the output data D of each platform i perform hash processing to generate a hash value H i ;

[0109] (2) Compare the hash values: Compare the hash value H of each platform i with the hash value H of other platforms j to determine whether they are equal;

[0110] (3) Result analysis: If the hash values of all platforms are equal (i.e., H i = H j ), the output data is consistent; otherwise, there is an inconsistency and the reasons for the differences need to be further analyzed;

[0111] S44. Generate a functional consistency verification report, record the verification results of each hardware platform, and perform a difference analysis based on the results of the hash comparison algorithm;

[0112] Through the hash comparison algorithm, it is ensured that the test results of different platforms are consistent, enhancing the accuracy and reliability of cross-platform testing.

[0113] S5 specifically includes:

[0114] S51. While performing functional tests on each hardware platform, use performance monitoring tools (such as Prometheus, Grafana) to monitor the system resource usage in real time, including CPU occupancy, memory usage, and I / O response time;

[0115] S52. Based on the performance data of different hardware platforms, calculate the performance bottlenecks. For example, evaluate the CPU occupancy through the following formula:

[0116]

[0117] where CPU Time(used) is the CPU time used by the system during a certain period, and Total CPU Time is the total CPU time of the system;

[0118] S53. Through performance tuning tools, optimize the platforms with performance bottlenecks, such as adjusting the number of threads, optimizing the memory allocation strategy, etc.;

[0119] S54. Record the results of performance testing and tuning, and generate a performance test report;

[0120] By testing and optimizing the performance of each platform, the stability and optimization of system performance are ensured beyond functional testing.

[0121] S6 specifically includes:

[0122] S61. Analyze the abnormal logs found during the functional or performance testing process through a log analysis tool to locate the specific fault points;

[0123] S62. Use a problem reproduction tool to repeat the test scenarios of the problem to ensure the reproducibility of the problem;

[0124] S63. Repair the located functional or performance problems and re - execute the corresponding test cases for regression testing to verify whether the problems are solved;

[0125] S64. Compare the results of the regression testing with the initial test results to ensure that other functions are not affected after the problems are repaired;

[0126] Through fault location and regression testing, ensure that all problems found during the testing process can be effectively repaired, and verify the consistency of the system functions and performance after repair.

[0127] S7 specifically includes:

[0128] S71. Summarize the test results of functional testing, performance testing, and fault location of all hardware platforms through the test management platform;

[0129] S72. Automatically analyze the summarized data to generate functional test results, performance test results, and fault analysis reports;

[0130] S73. Automatically generate cross - platform functional testing and verification reports, including detailed test data, test results, anomaly analysis, and optimization suggestions;

[0131] S74. Output the reports in PDF or HTML format for easy viewing and sharing;

[0132] By automatically generating test reports, the process of summarizing and analyzing test results is simplified, complete test data and analysis results are provided, and the efficiency of report generation is improved.

[0133] In S53, through a performance tuning tool, optimize the platforms with performance bottlenecks, specifically including:

[0134] Determine the performance bottleneck: Use performance monitoring tools (such as Prometheus, Grafana, top, htop, perf, etc.) to identify the parts of the system with abnormal resource consumption and determine the possible performance bottlenecks, specifically including;

[0135] Monitoring metrics include: CPU occupancy rate, memory usage, I / O response time, network bandwidth, disk I / O, etc. Pay attention to parts with high resource occupancy but low efficiency. For example, the CPU occupancy rate is close to 100% for a long time, memory frequently triggers garbage collection, and I / O operation latency, etc.;

[0136] CPU bottleneck: For CPU bottleneck, analyze the number of threads and CPU binding issues as follows:

[0137] Analysis of the number of threads: Determine whether the number of threads is too large or too small, and view the thread utilization rate through tools (such as perf or htop);

[0138] CPU binding issue: Check whether the task is bound to a specific CPU core, resulting in unbalanced load;

[0139] Memory bottleneck: For memory bottleneck, analyze memory allocation efficiency and memory leak issues as follows:

[0140] Memory allocation efficiency: Check whether the application frequently performs garbage collection (GC) or memory allocation (using valgrind, gperftools);

[0141] Memory leak: Check whether the memory is not released properly, resulting in the memory being gradually filled up;

[0142] I / O bottleneck: For I / O bottleneck, analyze disk read / write performance and network transmission performance as follows:

[0143] Disk read / write performance: Use iostat or iotop to check the I / O operation performance of the disk and analyze whether there is excessive I / O waiting;

[0144] Network transmission: Use iftop or netstat to check whether the network transmission reaches the bottleneck, especially the network latency in high-concurrency situations;

[0145] CPU optimization: Adjust the number of threads and use multiple cores to balance the CPU load and improve utilization as follows:

[0146] Adjust the number of threads: According to the CPU load and the multithreaded design of the application, by modifying the thread pool size or adjusting the number of concurrent threads, avoid excessive context switching caused by too many threads or underutilization of resources caused by too few threads. It is recommended to use 1.5 to 2 times the number of CPU cores as the thread pool size;

[0147] Use multiple cores: If the load is concentrated on a certain core, the task can be distributed to multiple cores through tools (such as taskset) to balance the load;

[0148] Memory Optimization: Optimize the memory allocation strategy to reduce garbage collection pauses and fix memory leak issues as follows:

[0149] Optimize the memory allocation strategy: Reduce unnecessary object creation, reasonably adjust the object lifecycle, reduce frequent memory allocation and deallocation, and optimize memory utilization by adjusting the garbage collection (GC) strategy to reduce GC pauses;

[0150] Memory leak check: Use tools (such as valgrind, leak sanitizer) to find and fix memory leaks to ensure that the memory allocated each time can be released properly;

[0151] I / O Optimization: Optimize I / O performance through asynchronous I / O operations and improving I / O throughput as follows:

[0152] Asynchronous I / O operations: If a large number of I / O operations cause long waiting times, the I / O operations can be changed to asynchronous processing to reduce the time of synchronous blocking, and use libraries such as epoll or libuv to implement non-blocking I / O;

[0153] Improve I / O throughput: Improve disk read and write performance by increasing the disk cache or using a RAID array, or replace traditional HDD hard drives with high-performance SSDs;

[0154] Network Optimization: Adjust network parameters and use load balancing to reduce network latency and improve network performance as follows:

[0155] Reduce network latency: Reduce network transmission latency by tuning TCP parameters (such as adjusting MTU or enabling TCP_NODELAY);

[0156] Use load balancing: In high-concurrency scenarios, use load balancing technology to distribute requests to multiple servers to avoid single-point bottlenecks;

[0157] Verification Optimization: Rerun the tests, observe the performance after optimization, ensure that the optimization plan is effective, and verify whether the performance of the optimized system meets the expectations;

[0158] Generate a report: Generate a performance tuning report, record the changes in various metrics before and after optimization, such as the shortening of response time and the reduction of CPU usage, etc.;

[0159] Using performance tuning tools can effectively identify and optimize performance bottlenecks in the system, such as by adjusting the number of threads, optimizing memory allocation, asynchronously processing I / O, improving network performance, etc., so as to ensure the efficient operation of the system on different platforms.

[0160] The present invention encompasses any alternatives, modifications, equivalent methods, and solutions that are within the spirit and scope of the present invention. For the public to have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention. However, those skilled in the art can fully understand the present invention even without the description of these details. Additionally, well-known methods, processes, procedures, components, and circuits, etc., are not described in detail to avoid unnecessary confusion with the essence of the present invention.

[0161] The above description is only a preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as within the protection scope of the present invention.

Claims

1. A method for testing and verifying the cross-platform functions of a core board, characterized in that It includes the following steps: S1, Initialization of multi-platform environment: Build a test environment for multiple operating systems and hardware platforms through virtualization technology or actual hardware. The multiple operating systems include Linux, Windows, and Android, and the hardware platforms include ARM and x86 architectures. Manage the creation and destruction of the platform environment through a unified interface. The S1 specifically includes: S11, Build a virtualization environment for multiple operating systems through virtualization technology. The operating systems include Linux, Windows, and Android. S12, Build a test platform based on different hardware architectures through actual hardware devices. The hardware architectures include ARM and x86. S13, Automatically create and destroy the test environment of each virtual machine instance or actual hardware through a unified interface management system. S14: In the created test environment, install and configure the dependency libraries and driver programs required for testing. S2, Automatic generation of test scripts: Based on the functional requirements of the core board, use a script generation engine to automatically generate cross-platform compatible test scripts. The script language supports multi-platform operation. The S2 specifically includes: S21, Based on the functional requirements of the core board, input the test case specifications into the script generation engine and analyze the functional requirement characteristics of the core board. S22, The script generation engine automatically generates scripts compatible with different platforms according to the differences between platforms. S23, Select a script language that supports multi-platform operation to ensure that the same set of scripts can run on Linux, Windows, and Android platforms. S24: The generated test scripts include a platform difference processing module, and automatically adapt to the system characteristics of different platforms using conditional branching or preprocessing mechanisms. S25: Simulate user operations or functional operations of the core board through scripts, and automatically generate test data and expected results. S3, Execution of multi-platform functional tests: Execute the generated test scripts in parallel on each test platform, record the running logs and result outputs of each platform during the test, monitor the functional execution status of each platform in real time through a log analysis tool, and generate a functional execution report for each platform. S4, Verification of functional consistency: Compare and analyze the test results of different platforms to verify whether the functional performance of the core board is consistent on different platforms. Use a hash comparison algorithm to verify the consistency of the output data. S5, Performance testing and optimization: On the basis of functional testing, test the performance of each platform, including CPU occupancy rate, memory usage rate, and response time. Analyze and optimize the performance bottlenecks through a performance optimization tool. S6, Fault location and regression testing: Use the method of regression testing to reproduce the functional or performance problems found during the test, locate the problems in combination with a fault location tool, and verify whether the problems are completely solved through regression testing after fixing the problems. S7, Automated Report Generation of Test Results: Summarize and analyze the test results of all platforms through the test management platform to generate a cross-platform functional test and verification report, which includes functional test results, performance test results, and fault analysis reports.

2. The core board cross-platform function testing and verification method according to claim 1, wherein The specific steps of S3 are as follows: S31, Deploy the automatically generated test scripts to the test environments of each operating system and hardware platform; S32, Execute the test scripts in parallel on different hardware platforms, adopt multi-thread or multi-process technology to improve the test efficiency, and record the test logs of each hardware platform, including script execution time, error logs, and output results; S33, Use a log collection tool to centralize the log files of each platform on a unified log analysis platform, and monitor the functional execution status of each hardware platform in real time; S34, Generate a preliminary test report, recording the functional execution results and abnormal situations of each hardware platform.

3. The core board cross-platform function testing and verification method according to claim 1, characterized in that The specific steps of S4 are as follows: S41, Format the test output results of each hardware platform; S42, Perform consistency verification on the output data based on the hash comparison algorithm; S43, If the hash values are the same, it means the output data is the same. If the hash values are different, mark it as function inconsistency and analyze the reasons for the differences; S44, Generate a functional consistency verification report, record the verification results of each hardware platform, and perform differential analysis according to the results of the hash comparison algorithm.

4. The core board cross-platform function testing and verification method according to claim 1, characterized in that The specific steps of S5 are as follows: S51, While performing functional tests on each hardware platform, use a performance monitoring tool to monitor the system resource usage in real time, including CPU occupancy rate, memory usage rate, and I / O response time; S52, Calculate the performance bottleneck based on the performance data of different hardware platforms; S53, Use a performance tuning tool to optimize the platforms with performance bottlenecks; S54, Record the results of performance testing and tuning, and generate a performance test report.

5. The core board cross-platform function test and verification method according to claim 1, characterized in that The specific steps of S6 are as follows: S61, Analyze the abnormal logs found during functional or performance testing through a log analysis tool to locate the fault points; S62, Use a problem reproduction tool to repeat the test scenarios with problems; S63, Repair the located functional or performance problems, and re-execute the corresponding test cases for regression testing to verify whether the problems are solved; S64, Compare the results of regression testing with the initial test results to ensure that other functions are not affected after the problems are repaired.

6. The core board cross-platform function test and verification method according to claim 1, characterized in that The specific steps of S7 are as follows: S71, Summarize the test results of functional testing, performance testing, and fault location of all hardware platforms through the test management platform; S72, Automatically analyze the summarized data to generate functional test results, performance test results, and fault analysis reports; S73, Automatically generate a cross-platform functional test and verification report, including detailed test data, test results, abnormal analysis, and optimization suggestions; S74, Output the report in PDF or HTML format for easy viewing and sharing.

7. The core board cross-platform function testing and verification method according to claim 4, wherein In S53, when using a performance tuning tool to optimize the platforms with performance bottlenecks, it specifically includes: Determine the performance bottleneck: Use a performance monitoring tool to identify the parts of the system with abnormal resource consumption and determine the performance bottleneck; CPU Bottleneck: For CPU bottleneck, analyze the number of threads and CPU binding issues; Memory Bottleneck: For memory bottleneck, analyze memory allocation efficiency and memory leak issues; I / O Bottleneck: For I / O bottleneck, analyze disk read / write performance and network transmission performance; CPU Optimization: Adjust the number of threads and use multiple cores to balance CPU load and improve utilization; Memory Optimization: Optimize memory allocation strategies, reduce garbage collection pauses, and fix memory leak issues; I / O Optimization: Optimize I / O performance through asynchronous I / O operations and increase I / O throughput; Network Optimization: Adjust network parameters and use load balancing to reduce network latency and improve network performance; Verification of Optimization: Rerun the tests, observe the performance after optimization, ensure the effectiveness of the optimization plan, and verify whether the performance of the optimized system meets expectations; Generate Report: Generate a performance tuning report and record the changes in various metrics before and after optimization.

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