Cloud testing upper computer system and testing method

Abstract

The invention discloses a clouded test upper computer system and a test method. The clouded test upper computer system comprises a cloud upper computer and at least one edge execution unit, the cloud upper computer is deployed at the cloud and comprises a user interaction module, an artificial intelligence module, a central control and task management module and a cloud database, the edge execution unit is deployed at a test site close to a tested object, and the cloud upper computer is connected with the edge execution unit through a network. And the centralized management, distributed execution and result summarization of the test tasks are cooperatively completed. According to the invention, tight coupling of traditional upper computer functions and hardware is broken through, non-real-time and compute-intensive functions are migrated to the cloud, and elastic expansion and centralized management of resources are realized.

Description

Technical Field

[0001] This invention relates to the field of automated testing technology, and in particular to a cloud-based testing host computer system and testing method. Background Technology

[0002] Traditional test host computer systems typically employ a centralized architecture, either a standalone machine or a local area network. In this architecture, the host computer software is installed on a high-performance personal computer (PC) or industrial control computer (ICC), and is physically connected to the object under test (DUT) directly through a specific hardware interface card (such as a CAN card, LIN card, serial port card, etc.).

[0003] This software is a highly integrated monolithic application, typically including all functional modules such as a graphical user interface (GUI), test script editing and debugging environment, test case library management, test execution engine, real-time data acquisition, data visualization and analysis, hardware I / O driver control, and test report generation. The user operation process is as follows: test cases are written or selected through the local GUI; the local execution engine directly calls the hardware driver to send stimulus signals to the object under test and simultaneously collects response data; finally, data analysis is completed locally and a test report is generated.

[0004] This architecture was widely used in the early stages of industrialization when the tested objects had simple functions, fixed test scenarios, and limited data volume due to its simple deployment and direct closed-loop operation. However, with the exponential growth in the complexity of tested object systems (e.g., from a single controller to a whole vehicle network), the explosive growth of test data (e.g., sensor fusion data, high sampling rate signals), and the fundamental increase in requirements for intelligent testing and collaborative efficiency, the limitations of this traditional centralized architecture are increasingly becoming a bottleneck for industry development. Traditional host computer systems face the following core pain points and challenges: Computing power bottlenecks and lack of intelligence: Modern testing, especially in fields such as automotive electronics (e.g., ADAS / AD) and industrial IoT, generates massive amounts of high-dimensional data. Traditional host computers, as stand-alone systems, with their fixed CPU, memory, and storage resources, cannot effectively support advanced intelligent requirements such as historical data analysis based on big data, fault mode prediction based on machine learning, and automatic optimization and generation of test cases. Complex signal processing or simulation model calculations can easily lead to system lag or even crashes, limiting the depth and efficiency of testing.

[0005] Insufficient collaborative testing capabilities: When dealing with complex systems composed of dozens or even hundreds of ECUs (such as vehicle networks), testing often requires synchronous stimulation and data acquisition across multiple nodes and interfaces. Traditional architectures either rely on a single host computer paired with complex multiplexing hardware (high cost and complex configuration), or require deploying multiple independent host computers and performing manual synchronization. The latter leads to isolated test resources, difficulties in task scheduling, misalignment of data timestamps, and an inability to uniformly monitor overall test progress and status, resulting in extremely low collaborative efficiency and difficulty in reproducing system-level interaction scenarios.

[0006] The contradiction between real-time assurance and network dependence: For test scenarios requiring hard real-time response (such as hardware-in-the-loop testing), traditional host computers can guarantee microsecond-level latency through direct local connections, but their computational tasks are heavy and easily introduce jitter due to operating system scheduling, interference from other software processes, etc., affecting determinism. If attempts are made to offload some computational tasks through the network, the inherent and unpredictable transmission latency and jitter of public networks or regular enterprise networks are completely unable to meet the millisecond-level or even more stringent closed-loop control timing requirements.

[0007] System scalability, maintainability, and cost issues: Poor scalability: Each additional test station or new test type typically requires configuring complete hardware and software, leading to linear or even higher cost increases.

[0008] Maintenance difficulties: Software upgrades and test case updates need to be performed on each physical device individually, making it difficult to guarantee deployment consistency and resulting in a large maintenance workload.

[0009] Low resource utilization: Test tasks typically have peaks and troughs. The fixed resources of a single device cannot be used by other tasks when idle, while bottlenecks may occur under high load, resulting in low overall resource utilization.

[0010] In summary, existing traditional test host computer systems cannot simultaneously meet the modern industrial testing requirements of powerful computing capabilities, efficient collaboration, high real-time performance, and flexible scalability. Therefore, the industry urgently needs an innovative system architecture solution that can fundamentally resolve these contradictions.

[0011] Therefore, there is an urgent need to provide a cloud-based testing host computer system and testing method. Summary of the Invention

[0012] To address the above issues, the present invention provides a cloud-based testing host computer system and testing method, which decouples the core functions of the host computer and deploys them to the cloud, while separating the real-time execution unit and deploying it to the edge near the object under test, thereby achieving an efficient, intelligent, and scalable distributed testing solution.

[0013] According to a first aspect of the present invention, a cloud-based test host computer system is provided, characterized in that it includes a cloud-based host computer and at least one edge execution unit; The cloud-based host computer, deployed in the cloud, includes: The user interaction module provides an interface for inputting test requirements and displaying test results. The artificial intelligence module is used to automatically generate test scripts based on the input test requirements; The central control and task management module is used to manage test projects, schedule test tasks, and distribute the test scripts to edge execution units; A cloud-based database is used to store test project information, test scripts, historical test data, and models of the objects under test. The edge execution unit is deployed at the test site close to the object under test; The cloud-based host computer and the edge execution unit are connected via a network to collaboratively complete the centralized management, distributed execution, and result aggregation of test tasks.

[0014] In the above scheme, the cloud-based host computer also includes: The cloud-based simulation environment is used to perform logical and syntax verification on the test script before it is sent to the edge execution unit.

[0015] In the above scheme, the edge execution unit includes: The network communication module is used to establish a communication connection with the cloud-based host computer and receive the test scripts sent to it. The script execution engine is used to parse and execute received test scripts locally in real time. Hardware I / O modules are used for real-time data interaction with the object under test via at least one industrial communication protocol.

[0016] In the above scheme, the edge execution unit includes software modules and is deployed on a hardware platform, which includes Linux industrial control computers, standard PCs and container environments.

[0017] In the above scheme, the industrial communication protocols supported by the hardware I / O module include at least one of CAN, LIN, 10Base-T1S, DDS, CAN FD, or Ethernet.

[0018] In the above scheme, the cloud host computer sends test scripts to the edge execution unit via the MQTT protocol.

[0019] In the above scheme, for test scenarios where the real-time requirements are higher than the preset threshold, after the edge execution unit receives and deploys the complete test project, it independently completes the closed-loop test control with the test object locally, and asynchronously transmits the test process data back to the cloud host computer.

[0020] In the above scheme, the artificial intelligence module is specifically used to: automatically generate an executable test script containing test logic and parameters based on the test requirements input by the user through natural language or structured forms, combined with a pre-stored knowledge base or model of the object under test.

[0021] According to a second aspect of the present invention, a testing method based on a system according to any one of the above-described solutions is provided, comprising: S1. Users input test requirements through the user interaction module of the cloud-based host computer; S2. The artificial intelligence module of the cloud-based host computer generates a test script according to the test requirements; S3. The central control and task management module of the cloud-based host computer sends the test script to the designated edge execution unit; S4. The script execution engine of the edge execution unit executes the test script locally in real time and interacts with the object under test through the hardware I / O module; S5. The edge execution unit transmits the test execution process data and / or results back to the cloud host computer for storage, analysis and display.

[0022] In the above scheme, before step S3, it also includes: verifying the test script generated by the artificial intelligence module in the simulation environment of the cloud host computer.

[0023] The beneficial effects of this invention are: 1. Decoupling and Cloudification: Break the tight coupling between traditional host computer functions and hardware, and migrate non-real-time, computationally intensive functions (such as intelligent decision-making, project management, and UI interaction) to the cloud to achieve elastic scaling and centralized management of resources.

[0024] 2. Intelligent Upgrade: By integrating artificial intelligence modules, test projects and test cases can be automatically generated and optimized, freeing test engineers from tedious repetitive work and improving the intelligence level and coverage of testing.

[0025] 3. Real-time performance guarantee: Time-sensitive functions (such as real-time script execution and hardware I / O communication) are separated into independent edge execution units and deployed in physical locations close to the object under test to minimize network latency and meet the stringent requirements of millisecond-level real-time performance in fields such as automotive testing.

[0026] 4. High-efficiency collaboration: Establish a high-efficiency collaboration mechanism between the cloud-based host computer and the edge execution unit to realize the centralized distribution, distributed execution and unified aggregation of test tasks, thereby supporting large-scale, multi-node collaborative testing scenarios. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0028] Figure 1 This is an architecture diagram of the cloud-based test host computer system in this invention; Figure 2 This is a flowchart of the testing method for the cloud-based host computer system in this invention.

[0029] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0031] The terms "first," "second," etc., used in this disclosure are for distinguishing similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented, for example, in orders other than those illustrated or described herein.

[0032] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0033] Multiple, including two or more.

[0034] And / or, it should be understood that, for the purposes of this disclosure, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0035] like Figure 1 As shown, one embodiment of the technical solution of the present invention provides a cloud-based test host computer system, including a cloud host computer and at least one edge execution unit; The cloud-based host computer, deployed in the cloud, includes: The user interaction module provides test engineers with a browser-based access point for inputting test requirements, monitoring test progress, displaying test results, and managing test projects.

[0036] An artificial intelligence module is used to automatically generate test scripts based on input test requirements. In this invention, the artificial intelligence module serves as the core engine for achieving intelligent testing. Based on user-input test requirements (e.g., natural language descriptions, specifications of the device under test, etc.), it utilizes a pre-trained artificial intelligence model to automatically generate corresponding test items and test case scripts. This not only significantly improves the efficiency of test case design, reduces the workload and error rate of manual script writing, but also, through the optimization of AI algorithms, generates more comprehensive and higher-coverage test cases, thereby improving the quality and depth of testing.

[0037] The central control and task management module is responsible for scheduling the entire testing process, managing test projects, scheduling test tasks, and distributing test scripts to edge execution units.

[0038] A cloud-based database is used to store test project information, test scripts, historical test data, and models of the objects under test.

[0039] The cloud-based host computer also includes a cloud-based simulation environment, which is a virtual simulation platform used to perform logical and syntax verification on test scripts before they are sent to edge execution units, reducing the time spent debugging on real hardware.

[0040] Edge execution units, deployed at the test site close to the object under test, include: The network communication module is used to establish a communication connection with the cloud host computer and receive the test scripts sent down. The script execution engine is used to parse and execute received test scripts locally in real time. The hardware I / O module is used to perform real-time data interaction with the object under test through at least one industrial communication protocol. Specifically, the industrial communication protocols supported by the hardware I / O module include at least one of CAN, LIN, 10Base-T1S, DDS, CAN FD, or Ethernet.

[0041] The cloud-based host computer and the edge execution unit are connected via a network to collaboratively complete the centralized management, distributed execution, and result aggregation of test tasks.

[0042] This invention separates real-time execution functionality from the host machine, designing a lightweight, independently deployable edge execution unit. This edge execution unit is a software module that can be flexibly deployed on various hardware platforms, such as Linux industrial PCs, standard PCs, and even container environments like Docker. The edge execution unit connects to a cloud-based host computer via a network, receives test scripts, and performs real-time parsing and execution locally. It interacts directly with the object under test using multiple industrial communication protocols such as CAN, LIN, 10Base-T1S, and DDS, ensuring rapid delivery of test commands and real-time acquisition of test data. This edge deployment approach pushes computation and data processing to the network edge, minimizing data transmission paths and effectively solving the problem of public network latency failing to meet closed-loop testing requirements.

[0043] Furthermore, the cloud-based host computer sends test scripts to the edge execution unit via the MQTT protocol.

[0044] The edge execution unit also includes a local cache and storage module, which is used to temporarily store test scripts and collected data during the test, and to ensure the continuous execution of the test in the event of network failure.

[0045] For test scenarios where real-time requirements exceed a preset threshold, the edge execution unit receives and deploys the complete test project, independently completes closed-loop test control with the tested object locally, and asynchronously transmits the test process data back to the cloud host computer.

[0046] The system of this invention adopts a collaborative mode of centralized cloud management and distributed edge execution. For scenarios with high real-time requirements (such as ADAS testing), the edge unit independently completes closed-loop control locally after receiving the complete test item, and the test data is asynchronously transmitted back, ensuring that the response time is within the millisecond level.

[0047] System architecture implementation details The system of this invention is divided into three layers: Cloud layer: Deployed on a public or private cloud platform, providing elastic computing and storage resources. Modules are decoupled and can be independently scaled through a microservice architecture. Users can access the web interface through any terminal browser.

[0048] Edge layer: Composed of several edge execution units, each of which can run independently and supports containerized deployment for easy rapid deployment and migration. Units can synchronize data with each other via a local area network or dedicated bus (if required).

[0049] Device layer: This includes various objects under test (ECUs, sensors, actuators, etc.), which are connected to the edge execution unit through standard industrial interfaces.

[0050] like Figure 2 As shown, according to a second aspect embodiment of the present invention, a testing method based on any of the above-described solutions is provided, comprising: S1. Users input test requirements through the user interaction module of the cloud-based host computer; S2, the AI ​​module of the cloud-based host computer generates test scripts according to the test requirements; S3, the central control and task management module of the cloud-based host computer will distribute the test script to the designated edge execution unit; S4, the script execution engine of the edge execution unit executes the test script locally in real time and interacts with the object under test through the hardware I / O module; S5, the edge execution unit, transmits the test execution process data and / or results back to the cloud host computer for storage, analysis and display.

[0051] Before step S3, the method further includes: verifying the test script generated by the artificial intelligence module in the simulation environment of the cloud host computer and determining whether the verification is successful. If it is successful, step S3 is executed; if it is unsuccessful, the method returns to step S2 to modify the test script.

[0052] Example 1 Automotive ECU Automated Testing 1. Test Scenario Description An automaker needs to conduct comprehensive functional and performance regression testing on its newly developed engine ECU. The test program includes hundreds of test cases, covering everything from basic sensor signal acquisition and actuator driving to complex fuel injection control and emission control. Traditional testing methods require multiple test engineers to manually operate multiple test devices, which is time-consuming, labor-intensive, and makes it difficult to ensure test consistency and coverage.

[0053] 2. Cloud-based host computer operation Test engineers log into the cloud-based host computer system via a browser. First, they create a new ECU test project in the project management module and upload the ECU's DBC file and functional specification document. Then, in the test requirement definition interface, the engineer inputs test requirements in natural language, such as: "Please generate a set of test cases to verify whether the ECU's control logic for the electric fan is correct under different coolant temperatures." After receiving the requirements, the artificial intelligence module automatically analyzes and generates a series of test scripts, including simulating different coolant temperature sensor signals, monitoring the duty cycle of the electric fan's PWM control signal, and verifying the fan's start / stop thresholds and speed. The engineer quickly verifies the generated scripts in the cloud simulation environment. Once confirmed to be correct, the test task is distributed to multiple edge execution units deployed in the laboratory.

[0054] 3. Edge Execution Unit Deployment and Execution In the laboratory, each test bench is equipped with an edge execution unit running Linux. These execution units are connected to the ECU hardware under test via CAN and LIN buses. Upon receiving the test script from the cloud, the edge execution units immediately begin execution. Following the script instructions, they send simulated coolant temperature signals to the ECU via the CAN card, while simultaneously acquiring real-time electronic fan control commands from the ECU via the CAN bus. The entire testing process requires no manual intervention; the edge execution units automatically complete all test steps and transmit detailed test data and results back to the cloud-based host computer in real time. Test engineers can monitor the progress and results of all test benches in real time from their office computers via the monitoring panel on the cloud-based host computer. After the test is completed, the system automatically generates a test report containing detailed data and conclusions for all test cases, significantly improving testing efficiency and automation.

[0055] Example 2 Advanced Driver Assistance Systems (ADAS) Real-time Performance Test 1. Test Scenario Description An autonomous driving technology company needs to conduct hardware-in-the-loop testing of the emergency braking function of its developed ADAS controller. This test scenario demands extremely high real-time performance: when the system detects a collision risk ahead, it must trigger braking within tens of milliseconds. Any significant delay could lead to test failure and fail to accurately reflect the system's performance.

[0056] 2. Cloud-based host computer operation Test engineers define AEB test scenarios in a cloud-based host computer, including setting parameters such as the speed of the virtual vehicle, the distance and speed of the target object, and the road surface friction coefficient. Based on these parameters, the artificial intelligence module automatically generates complex test scripts, which define the logic for injecting sensor data and the desired braking response. Due to the extremely high real-time requirements of AEB testing, after completing script generation and preliminary logic verification in the cloud, engineers package and distribute the entire test project to a dedicated edge execution unit deployed next to the HIL test bench.

[0057] 3. Edge Execution Unit Deployment and Execution The edge execution unit (EMU) is a high-performance real-time industrial control computer that connects directly to the ADAS controller under test (ADAS) via high-speed Ethernet and CAN FD bus. Upon receiving the test item, the EMU begins execution. It injects simulated sensor data streams (such as images of vehicles ahead and radar point cloud data) into the ADAS controller in real time via Ethernet. The ADAS controller runs its perception and decision-making algorithms based on the received data. When a collision risk is detected, the ADAS controller sends a braking request via the CAN FD bus. The EMU receives this request via the CAN FD bus and immediately triggers the braking of the virtual vehicle in the HIL simulation model. The entire perception-decision-execution closed loop is completed entirely between the EMU and the ADAS controller, with latency controlled to within 10 milliseconds. Simultaneously, the EMU records all key data throughout the process, including sensor inputs, the internal state of the ADAS controller, and the timestamp of the braking request, and uploads this data asynchronously to a cloud-based host computer. Test engineers can analyze this data in the cloud to accurately evaluate the response time and braking effect of the AEB system, thereby optimizing the algorithm.

[0058] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0059] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0060] Through the above description of the embodiments, those skilled in the art can clearly understand that the above implementation methods can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0061] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A cloud-based testing host computer system, characterized in that, Includes a cloud-based host computer and at least one edge execution unit; The cloud-based host computer, deployed in the cloud, includes: The user interaction module provides an interface for inputting test requirements and displaying test results. The artificial intelligence module is used to automatically generate test scripts based on the input test requirements; The central control and task management module is used to manage test projects, schedule test tasks, and distribute the test scripts to edge execution units; A cloud-based database is used to store test project information, test scripts, historical test data, and models of the objects under test. The edge execution unit is deployed at the test site close to the object under test; The cloud-based host computer and the edge execution unit are connected via a network to collaboratively complete the centralized management, distributed execution, and result aggregation of test tasks.

2. The cloud-based test host computer system according to claim 1, characterized in that, The cloud-based host computer also includes: The cloud-based simulation environment is used to perform logical and syntax verification on the test script before it is sent to the edge execution unit.

3. The cloud-based test host computer system according to claim 1, characterized in that, The edge execution unit includes: The network communication module is used to establish a communication connection with the cloud-based host computer and receive the test scripts sent to it. The script execution engine is used to parse and execute received test scripts locally in real time. Hardware I / O modules are used for real-time data interaction with the object under test via at least one industrial communication protocol.

4. The cloud-based test host computer system according to claim 1, characterized in that, The edge execution unit includes software modules deployed on a hardware platform, which includes Linux industrial control computers, standard PCs, and container environments.

5. The cloud-based test host computer system according to claim 1, characterized in that, The industrial communication protocols supported by the hardware I / O module include at least one of CAN, LIN, 10Base-T1S, DDS, CAN FD, or Ethernet.

6. The cloud-based test host computer system according to claim 1, characterized in that, The cloud-based host computer sends test scripts to the edge execution unit via the MQTT protocol.

7. The cloud-based test host computer system according to claim 1, characterized in that, For test scenarios where real-time requirements exceed a preset threshold, the edge execution unit receives and deploys a complete test project, independently completes closed-loop test control with the tested object locally, and asynchronously transmits the test process data back to the cloud host computer.

8. The cloud-based test host computer system according to claim 1, characterized in that, The artificial intelligence module is specifically used to: automatically generate an executable test script containing test logic and parameters based on the test requirements input by the user through natural language or structured forms, combined with a pre-stored knowledge base or model of the object under test.

9. A testing method based on the system according to any one of claims 1-8, characterized in that, include: S1. Users input test requirements through the user interaction module of the cloud-based host computer; S2. The artificial intelligence module of the cloud-based host computer generates a test script according to the test requirements; S3. The central control and task management module of the cloud-based host computer sends the test script to the designated edge execution unit; S4. The script execution engine of the edge execution unit executes the test script locally in real time and interacts with the object under test through the hardware I / O module; S5. The edge execution unit transmits the test execution process data and / or results back to the cloud host computer for storage, analysis and display.

10. The test method according to claim 9, characterized in that, Before step S3, the method further includes: verifying the test script generated by the artificial intelligence module in a simulation environment on a cloud-based host computer.

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