Intelligent agent multi-environment unified test method and system

Abstract

The invention discloses an agent multi-environment unified test method and system, relates to the technical field of data analysis, solves the problem that the environment is uncontrollable for a long time due to the lack of a unified baseline in an existing test platform by setting unified basic configuration for a test environment and generating the baseline, and ensures that all tests are carried out under consistent initial conditions. By recording configuration snapshots before testing, the system can accurately identify the difference with a baseline, and misjudgment caused by undefined configuration is avoided; all configuration modifications are detected and recorded in the testing process, and temporary testing adjustment and destructive modification can be distinguished; by calculating the influence of the damage index quantitative test on the basic configuration, the conversion from experience judgment to objective evaluation is realized; finally, whether the base line is recovered or not is automatically judged by comparing the damage index with the threshold value, so that resource waste caused by frequent reset is avoided while environment consistency is guaranteed, intelligence and self-repair of the test environment are realized, and distortion of a test result caused by implicit damage to basic configuration is prevented.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, and in particular to an agent multi-environment unified testing method and system. BACKGROUND

[0002] With the continuous expansion of the application of agents in scenarios such as dialogue, car machine, testing and automatic decision-making, enterprises generally use a multi-environment unified testing platform to centrally manage multiple types of environments such as research and development, testing, stress testing and demonstration. The existing platform generally ensures that agents in different environments can be consistently called and verified through capabilities such as template configuration, unified access layer, scenario-based testing, and panoramic observability. In the multi-environment testing system, the platform usually sets a set of basic configurations for the "test environment", including model version, key function switch, middleware address, data source configuration, and necessary verification strategies, as the common baseline for all test tasks. However, in actual testing, to meet different needs such as performance stress testing, abnormal verification, and new strategy testing, testers often need to make temporary adjustments to the test environment, such as modifying the flow limit threshold, adjusting the function switch, and switching to a specific test data source. Such adjustments are normal operations that help improve test coverage.

[0003] The problem is that the existing platform lacks a fine-grained identification and quantitative management mechanism for "which modifications are acceptable temporary adjustments and which modifications will affect the basic configuration of the test environment". All changes during testing directly affect the actual configuration of the test environment, and if sensitive modifications to the basic configuration are not discovered and rolled back in time, the baseline consistency of the test environment will be disrupted, making subsequent test results distorted and non-reproducible.

[0004] A simple way is to forcibly restore the basic configuration of the test environment after each test is completed. However, this approach requires frequent environment resets, service restarts or model reloads, which is costly, and for tests that only make light parameter adjustments, such full-scale restoration is a complete waste of resources. Therefore, the existing multi-environment testing platform still lacks a method that can: allow flexible configuration adjustments during testing, distinguish which modifications will disrupt the basic configuration, and selectively restore the baseline when necessary to avoid long-term pollution of the environment. This is a problem that current technology has not yet solved. SUMMARY

[0005] The purpose of the present application is to solve the above-mentioned problems and provide an agent multi-environment unified testing method and system.

[0006] In the first aspect of the present application, an agent multi-environment unified testing method is first proposed, which comprises: presetting a basic configuration for a test environment, and generating a basic configuration baseline of the test environment based on the basic configuration; Before each test, the current running configuration of the test environment is obtained, and recorded as a pre-test configuration snapshot; During the test, configuration modifications to the test environment are detected and recorded, forming a configuration modification set for the test, wherein the configuration modification set includes adjustments to test parameters and potential modifications to the basic configuration of the test environment; After the test, the configuration modification set is compared with the basic configuration baseline, and a damage index is calculated according to the comparison result, which is used to quantify the damage degree of the basic configuration by the test; The damage index is compared with a preset threshold, and whether the basic configuration baseline of the test environment is determined according to the comparison result.

[0007] Optionally, the step of calculating the damage index according to the comparison result is: According to the comparison result, a structural stability deviation index and a link disturbance index of the basic configuration are calculated, and the sum of the two indexes is the damage index.

[0008] Optionally, the calculation step of the structural stability deviation index is: According to the dependency relationship between each configuration item in the basic configuration baseline, a basic topology graph is constructed , and represent the number of configuration items; when the th configuration item has a direct structural dependency with the th configuration item, , otherwise ; According to the configuration modification set of the test, the basic topology graph is updated to obtain a modified topology graph , and a topology deviation matrix is calculated ; if the structure changes, , otherwise ; For all configuration item pairs satisfying , the shortest path distance in the basic topology graph is calculated, and a structural disturbance path tensor is constructed, and the formula is: ; The in-degree and out-degree of each configuration item in the basic topology graph and the modified topology graph are extracted, and the local structure fracture amplitude is calculated, and the formula is: , wherein represents the local structure fracture amplitude of the th configuration item, , respectively represent the configuration items in-degree and out-degree in the basic topology graph; , respectively represent the configuration items in-degree and out-degree in the modified topology graph; According to the local structure fracture amplitude of all configuration items Calculate the discrete amplitude index , the formula is: ; Add the discrete amplitude index and the structure disturbance path tensor to obtain the structure stability offset index.

[0009] Optionally, the step of calculating the link disturbance index is: Each call link in the basic configuration baseline is represented as a triple , wherein: is the link starting module number; is the link ending module number; represents the control state of the link under the basic configuration, taking 0 or 1; and a link state matrix is generated, and the elements of the matrix are defined as ; Record all the actual trigger records of the link states during the test to form a modified matrix , and calculate a dynamic disturbance difference matrix , the formula is: ; wherein, represents whether the state of the link is disturbed in the test; if the state of the link is changed from enabled to disabled or from disabled to enabled, , otherwise 0; For each disturbed link , extract its path length and the number of coupled chains , and calculate the link disturbance index , the formula is: , wherein, is the link disturbance index, represents the disturbed link set.

[0010] Optionally, the step of judging whether the basic configuration baseline of the test environment is according to the comparison result is: When the damage index is less than the preset threshold, it is determined that the test does not damage the basic configuration of the test environment, and the basic configuration baseline does not need to be restored. When the damage index is not less than the preset threshold, it is determined that the current test has damaged the test environment basic configuration, and the test environment is automatically restored to the baseline of the basic configuration after the current test is ended.

[0011] In the second aspect of the embodiment of the present application, an agent multi-environment unified test system is provided, which comprises: A basic configuration module: presetting a basic configuration for a test environment, and generating a baseline of the basic configuration of the test environment based on the basic configuration; A configuration snapshot module: obtaining a current running configuration of the test environment before each test starts, and recording it as a test-before configuration snapshot; A modification module: detecting and recording configuration modifications for the test environment during the test, forming a configuration modification set of the current test, wherein the configuration modification set comprises adjustments to test parameters and potential modifications to the basic configuration of the test environment; A damage module: comparing the configuration modification set with the baseline of the basic configuration after the test is ended, calculating a damage index according to the comparison result, and the damage index is used to quantify the damage degree of the current test to the basic configuration; An update test module: comparing the damage index with a preset threshold, and judging whether the baseline of the basic configuration of the test environment according to the comparison result.

[0012] Optionally, the damage module comprises: A damage index calculation module: calculating a structural stability offset index and a link disturbance index of the basic configuration according to the comparison result, and the two indexes are added to obtain the damage index.

[0013] Optionally, the damage module further comprises: A numbering module: constructing a basic topology graph according to the dependency relationship between each configuration item in the baseline of the basic configuration , and represent the number of configuration items; when the th configuration item has a direct structural dependency with the th configuration item, , otherwise ; A topology offset matrix module: updating the basic topology graph according to the configuration modification set of the current test, obtaining a modified topology graph , and calculating a topology offset matrix , ; if the structure changes, , otherwise ; A disturbance path tensor module: for all configuration item pairs satisfying , calculating the shortest path distance and construct a structural perturbation path tensor , the formula is: Local structure fracture amplitude module: extract the in-degree and out-degree of each configuration item in the basic topology graph and the modified topology graph, calculate the local structure fracture amplitude, and the formula is: , wherein, represents the local structure fracture amplitude of the i-th configuration item, , , respectively represent the in-degree and out-degree of the configuration item in the basic topology graph; , respectively represent the in-degree and out-degree of the configuration item in the modified topology graph; Discrete amplitude index module: calculate the discrete amplitude index according to the local structure fracture amplitude of all configuration items , and the formula is: Structural stability deviation index module: add the discrete amplitude index and the structural perturbation path tensor to obtain the structural stability deviation index.

[0014] Optionally, the destruction module comprises: Link module: represent each call link in the basic configuration baseline as a triple , wherein: is the link starting module number; is the link ending module number; represents the control state of the link under the basic configuration, taking 0 or 1; thereby generating a link state matrix , the elements of which are defined as ; Dynamic perturbation difference matrix module: record the actual trigger record of all link states during the test to form a modified matrix , and calculate the dynamic perturbation difference matrix , and the formula is: ; wherein, represents whether the state of the link is disturbed in the test; if the link state changes from enabled to disabled or from disabled to enabled, , otherwise 0; Action link disturbance module: for each disturbed link , extract its path length and the number of coupled chains , and calculate the action link disturbance index , and the formula is: ​​, wherein, is an action link disturbance index, represents a set of disturbed links.

[0015] Optionally, the update test module comprises: The first comparison module: when the damage index is less than the preset threshold, it is determined that the current test has not damaged the test environment basic configuration, and the basic configuration baseline does not need to be restored. The second comparison module: when the damage index is not less than the preset threshold, it is determined that the current test has damaged the test environment basic configuration, and the test environment is automatically restored to the basic configuration baseline after the current test is completed.

[0016] The beneficial effects of the present application are: The present application provides an agent multi-environment unified test method and system, which sets a unified basic configuration for the test environment and generates a baseline, solves the problem of long-term uncontrollable environment caused by lack of unified benchmark in the existing test platform, ensures that each test is executed with consistent initial conditions, records the configuration snapshot before the test, enables the system to accurately identify the difference with the baseline, avoids the result deviation caused by unknown state before the test, detects and records all configuration modifications during the test process, the platform can track each change and distinguish between temporary test adjustment and destructive modification, calculates the damage index, quantifies the environmental impact as a measurable index, replaces manual experience judgment, and makes up for the deficiency of traditional methods that cannot accurately evaluate the damage degree, finally, compares the damage index with the threshold, the system automatically judges whether to restore the baseline, ensures the consistency of the environment, avoids the waste of resources caused by each reset, realizes the intelligentization and self-repair of the test environment, and prevents the test result from being distorted due to the implicit damage of the basic configuration. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be further described below in conjunction with the accompanying drawings.

[0018] Figure 1 It is a flowchart of an agent multi-environment unified test method; Figure 2 It is a framework diagram of an agent multi-environment unified test system. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0020] The present application provides an agent multi-environment unified test method. Referring toFigure 1 , Figure 1 A flowchart illustrating a unified multi-environment testing method for intelligent agents provided in an embodiment of the present invention. The method includes the following steps: S1: Preset basic configuration for the test environment and generate a basic configuration baseline for the test environment based on the basic configuration; S2: Before each test begins, obtain the current running configuration of the test environment and record it as a pre-test configuration snapshot; S3: During the test, detect and record the configuration changes to the test environment to form a set of configuration changes for this test. The set of configuration changes includes adjustments to test parameters and potential modifications to the basic configuration of the test environment. S4: After the test is completed, the set of configuration modifications is compared with the baseline configuration. The destruction index is calculated based on the comparison results. The destruction index is used to quantify the degree of destruction to the baseline configuration caused by this test. S5: Compare the damage index with a preset threshold, and determine whether the test environment's basic configuration baseline is met based on the comparison results.

[0021] Based on the unified testing method for intelligent agents in multiple environments provided by embodiments of the present invention, the following steps are taken: First, by setting a basic configuration for the test environment and generating a basic configuration baseline, the problem of long-term uncontrollable environment due to the lack of a unified baseline in existing testing platforms is solved, ensuring that all tests are conducted under consistent initial conditions. Second, by recording a configuration snapshot before the test, the platform can accurately identify the differences between the current test and the baseline, avoiding misjudgments caused by unclear pre-test configurations. Third, by detecting and recording all configuration modifications during the test, the platform can accurately distinguish between "temporary adjustments used only for testing" and "sensitive modifications that may damage the basic configuration," solving the problem of untraceable test operations in existing technologies. Fourth, by calculating a destruction index to quantify the impact of the test on the basic configuration, the judgment no longer relies on human experience but becomes an objective and measurable indicator, solving the technical deficiency of traditional methods in accurately assessing the degree of damage to the basic configuration. Fifth, by comparing the destruction index with a threshold, it automatically determines whether the basic configuration baseline needs to be restored, ensuring environmental consistency while avoiding the resource waste and execution delay caused by forced resets for each test. Finally, through the above steps, intelligent, low-cost, and controllable consistency protection of the test environment is achieved, effectively avoiding test result distortion and test conclusion invalidation caused by implicit damage to the basic configuration.

[0022] In one embodiment, S1: Preset a basic configuration for the test environment and generate a basic configuration baseline for the test environment based on the basic configuration; Specifically, a basic configuration is preset for the test environment, and a baseline configuration for the test environment is generated based on this basic configuration. Specifically, when initially building a unified multi-environment testing system for intelligent agents, the testing platform first selects a set of core configuration items considered "default and should remain stable over the long term" for the test environment based on the target business scenario, the type of intelligent agent, and the subsequent functional testing, performance testing, regression testing, and other testing requirements. These are defined as the basic configuration of the test environment. Examples include the explicitly used intelligent agent model version (e.g., agent-model-v2.1), the corresponding inference service address, the connection configuration of the dependent database and caching middleware, the default data source or knowledge base address, the initial state of key function switches (e.g., whether tool calls are enabled, whether security filtering is enabled), the default timeout and retry strategy, security verification rules, and basic parameters for log and monitoring reporting. After determining this set of basic configurations, the platform solidifies these configurations into a structured "basic configuration base". The baseline serves as the common starting point for all subsequent test tasks running in this test environment. Implicit overwriting or unrecorded modification of this baseline during runtime is prohibited. For example, in load testing scenarios, only temporary adjustments to concurrency and rate limiting parameters are allowed on top of the baseline; the model version or middleware address specified in the baseline will not be directly modified. This approach ensures that all tests have a clear, traceable initial state, avoiding uncertainties such as "what is the current environment configuration?" or "which version of the configuration is the test based on?" It also provides an objective reference for calculating the destructive index and determining whether the test touched upon the basic configuration. For instance, if a test temporarily changes the model version from agent-model-v2.1 to agent-model-v3.0, the system can clearly identify this as a deviation from key fields in the baseline, allowing it to decide whether to restore the environment to the baseline configuration after the test.

[0023] In one embodiment, S2: Before each test begins, obtain the current running configuration of the test environment and record it as a pre-test configuration snapshot; Specifically, when the testing platform receives a test task (such as a performance load test, a functional regression test, or a new strategy verification) and prepares to start, it does not directly begin executing the test in the current environment. Instead, it first systematically collects all valid configurations of the test environment at this time, solidifies these configurations in a structured manner, and forms a "pre-test configuration snapshot" uniquely associated with this test. This configuration snapshot should at least include the current values ​​of all key fields involved in the basic configuration baseline, such as the currently effective model version number, inference service address, database and cache connection information, default data source or knowledge base path, function switch status, security policy parameters, timeout and retry count, log and monitoring reporting configuration, etc. It can also include some test adjustments that have been superimposed on the baseline (such as rate limiting threshold adjustments that have not been cleared in a previous round of testing, the on / off status of a temporary switch, etc.), thus fully reflecting the actual running state of the test environment before the start of this test. In terms of implementation, this configuration snapshot can be stored in the form of JSON, YAML, or database records, along with the test task... The platform automatically retrieves all configuration items of the current environment before conducting a regression test on the agent tool call chain, including information such as "model_version=agent-model-v2.1", "tool_calling_enabled=true", "kb_url=https: / / kb-test.company.com", and "rate_limit=200QPS", and writes them into a snapshot. This step provides a benchmark for subsequent calculation of configuration modification sets and destructive indices, enabling the platform to accurately identify "which configurations were changed during this test" and avoid omissions due to post-test memory or incomplete manual records. It also provides reliable evidence for subsequent troubleshooting and test result traceability. When abnormal agent behavior or test results are found to be inconsistent with expectations after a test, the pre-test configuration snapshot can be quickly restored and viewed to clarify the configuration starting point on which the test was executed, thereby improving the controllability and traceability of environment management.

[0024] In one embodiment, S3: During the test, configuration modifications to the test environment are detected and recorded to form a set of configuration modifications for this test, wherein the set of configuration modifications includes adjustments to test parameters and potential modifications to the basic configuration of the test environment; Specifically, during test task execution, the test platform does not simply allow all configuration changes to the test environment. Instead, it uniformly intercepts and monitors all configuration write, update, and delete operations. Each configuration modification event is structured and recorded according to information such as "value before modification, value after modification, modification time, source component or operator, and configuration category," and continuously accumulated in the configuration modification set bound to this test. In implementation, the platform can set monitoring hooks at the configuration center, environment variable management module, or test platform configuration distribution interface. When a test script, operations personnel, or automated testing tool attempts to modify typical "test parameters" such as rate limiting thresholds, concurrency, timeout, and log levels, this type of change is categorized as a test parameter adjustment and written into the configuration modification set. When the modification action touches critical fields defined in the basic configuration baseline, such as model version, middleware address, data source or knowledge base path, core function switches, and security policy fields, it is blocked. Potential modifications to the basic configuration are also synchronously written to this set. For example, during a performance load test, testers might first increase "rate_limit" from 200 QPS to 1000 QPS, and then temporarily change "model_version" from "agent-model-v2.1" to "agent-model-v3.0" to observe the effect of the new model. The platform will record these two changes separately, with the former marked as a test parameter adjustment and the latter as a modification to the basic configuration item. This step ensures that all configuration changes during the test are traceable, preventing situations such as "I can't remember what I changed during the test" or "I can't find the reason why a certain environment behaves differently than before." This provides a complete data foundation for subsequent difference analysis and calculation of the damage index based on the configuration modification set and the basic configuration baseline, and also provides accurate evidence for subsequent replay of problem tests and tracking of environmental pollution sources.

[0025] In one embodiment, S4: After the test is completed, the set of configuration modifications is compared with the baseline of the basic configuration, and the destruction index is calculated based on the comparison results. The destruction index is used to quantify the degree of destruction of the basic configuration by this test. In one implementation, S4: After the test is completed, the set of configuration modifications is compared with the baseline of the basic configuration, and the destruction index is calculated based on the comparison results. The destruction index is used to quantify the degree of destruction of the basic configuration by this test. Specifically, the steps for calculating the damage index based on the comparison results are as follows: Based on the comparison results, the structural stability offset index and the active link disturbance index of the basic configuration are calculated, and the damage index is obtained by adding the two indices together. In one implementation, the calculation steps for the structural stability offset index are as follows: Based on the dependencies between configuration items in the basic configuration baseline, construct a basic topology graph. , and Indicates the configuration item number; when the number is... The configuration item and the first When a configuration item has a direct structural dependency ,otherwise ; Based on the configuration modifications made in this test, the basic topology map was updated to obtain the modified topology map. And calculate the topological offset matrix. , ; Indicates the first The configuration item and the first The changes in the topology of each configuration item; If the structure changes, then ,otherwise ; For all satisfying For each configuration item pair, calculate its shortest path distance in the basic topology graph. And construct the structural perturbation path tensor The calculation formula is: ; Indicates the first The configuration item and the first The shortest path length between configuration items; when there is no path connection between them. Take the maximum path length limit; Characterizes the overall structural disturbance intensity caused by this test; Extract the in-degree and out-degree of each configuration item in the basic and modified topology maps, and calculate the local structural fracture amplitude using the following formula: In the formula, Indicates the first The extent of local structural fracture in each configuration item. , These represent configuration items. In-degree and out-degree in a basic topological graph; , These represent configuration items. In-degree and out-degree in the modified topological graph; Based on the local structural fracture amplitude of all configuration items Calculate the discrete amplitude exponent The calculation formula is: ,in, The discrete amplitude index is used to represent the degree of dispersion of structural disturbances across all configuration nodes; Discrete amplitude index and structural perturbation path tensor Adding them together yields the structural stability offset index.

[0026] It should be noted that in the calculation of the structural stability offset index mentioned above, the data required for each step comes from the real-time collection and parsing of the basic configuration baseline and the set of configuration modifications during the test process by the test platform. The data for the basic configuration baseline comes from the structured configuration files or database records saved by the system during the test environment initialization phase. These files typically contain information such as module names, dependencies, API calls, data source addresses, function switch statuses, and security policy parameters. The system obtains all configuration items and their dependency mappings by parsing the configuration manifest or automatically reading the configuration management system (such as Kubernetes, Ansible, Consul, configuration center databases, etc.), thereby constructing the basic topology graph. The data for the modified topology graph comes from the platform's log monitoring and event recording module for all configuration change operations during test execution. The system captures configuration writing, API call, or parameter change events in real time and extracts their impact. The configuration item number, dependent target, and timestamp are automatically updated to modify the topology. In-degree and out-degree data are calculated by comparing the number of connections between nodes in the topology. The system counts the number of input edges and output edges of each configuration item in the dependency graph and records them in the corresponding data structure. The difference information required for calculating the local fracture amplitude is automatically generated directly from the basic and modified topology data. The data for calculating the discrete amplitude index is formed by traversing the fracture amplitude values ​​of all nodes to form a sequence and then normalizing it. Overall, all the data required for calculation is automatically collected by the configuration monitoring module and dependency parsing engine of the test platform before, during, and after the test, without relying on manual input, ensuring the integrity, continuity, and repeatability of the data.

[0027] It's important to note that the Structural Stability Shift Index is a quantitative indicator used to measure the degree to which the test environment's infrastructure is disrupted or disturbed at the topology level during testing. Its core meaning is: during a test execution, what range and level of structural shift occurs between the system's basic configuration (such as service dependencies, module connections, call relationships, and data flow paths) and the original baseline structure. This index does not simply indicate whether "configuration items have changed," but rather reflects whether such changes have disrupted the structural stability of the system's overall dependency topology, control links, and module coupling patterns. A small Structural Stability Shift Index indicates that adjustments made during the test are limited to local parameter levels (such as adjusting rate limiting thresholds or modifying log levels), and the system's topological relationships remain stable, not affecting the overall coherence and reproducibility of the test environment. Conversely, a large Structural Stability Shift Index indicates that modifications during testing have affected critical structural layers of the system, such as the replacement of certain modules, broken dependencies, or refactoring of call paths. Such changes cause the test environment's execution logic, functional paths, and even data flow directions to deviate from the baseline state, thereby disrupting the structural stability of the test environment and making subsequent test results incomparable to the baseline environment. If the environment is not restored to the baseline configuration after the test, problems such as unreproducible test results, abnormal agent behavior, and misaligned link responses will occur, potentially even causing subsequent tests to be logically based on a "contaminated" environment. For example, in a regression test, if the model service address or middleware node is temporarily replaced, although the test can run, its topology dependencies have changed, resulting in different call paths and caching strategy reconstruction. The performance metrics obtained from the test will be incomparable to the results under the baseline conditions. If such structures are not restored, the next test, even without changing the configuration, will run on different structural paths, resulting in systematic biases. Therefore, the larger the structural stability offset index, the deeper the structural disturbance, the stronger the stability destruction, and the higher the risk of permanent environmental contamination. In this case, the system should automatically restore the environment to the baseline configuration after the test to prevent the accumulation of contamination and the spread of test biases, ensuring that subsequent tests can be conducted under unified and verifiable structural conditions.

[0028] It's important to note that the advantage of calculating the structural stability offset index using the above method is that it doesn't simply count the number of configuration items or compare configuration differences. Instead, it analyzes the system's topology, quantifying the real changes in the environmental structure during testing from both global dependencies and local connectivity disturbances. This allows the calculation results to not only reflect the "amount of changes" but also reveal the "impact of changes on overall structural stability." Specifically, topological maps can capture deep dependencies between configuration items, such as whether a configuration modification will cause cascading breaks or path reconstruction. Path tensor calculations can identify the propagation range and intensity of structural changes, compensating for the inability of traditional methods to identify "hidden structural damage." The magnitude of local in-degree and out-degree breaks reflects node-level connectivity losses, allowing the calculation to go beyond global changes and distinguish, at a fine-grained level, which parts are more severely damaged. Finally, a nonlinear compression function normalizes and fuses global disturbances and local discreteness, avoiding subjective factors introduced by manual weighting and stabilizing the results between 0 and 1, facilitating quantitative comparisons between different tests. Compared to conventional field comparison or hash verification methods, this method dynamically reflects the evolution of structural relationships, identifying high-risk operations that appear to have minor configuration changes but actually disrupt critical dependency chains. This allows for a more accurate assessment of whether the test environment remains under control. For example, if two tests modify the same number of different fields, but one of them breaks the connection between the model service and middleware, the structural stability offset index calculated using this method will significantly increase. This prompts the system to automatically restore the baseline, preventing subsequent tests from continuing on an unstable structure. In other words, this calculation method, based on the fusion of topology and path perturbation, can more comprehensively, objectively, and dynamically reflect the true structural stability of the test environment, significantly improving the scientific rigor and automation of environmental consistency assessment.

[0029] In one embodiment, the calculation steps for the active link disturbance index are as follows: Each call chain in the basic configuration baseline is represented as a triple. ,in: Number the module at the beginning of the link; Number the link endpoint module; This indicates the control state of the link under the basic configuration (e.g., enabled, disabled, conditionally triggered), and is either 0 or 1; this is used to generate the link state matrix. Its elements are defined as ; During the testing process, the actual trigger records of all link states were recorded, forming a modified matrix. And calculate the dynamic disturbance difference matrix. The calculation formula is: ;in, Indicates link During the test, was the state disturbed? If the link state changes from enabled to disabled or vice versa, then... Otherwise, it is 0; For each disturbed link Extract its path length With the number of coupling chains And calculate the link disturbance index. The calculation formula is: In the formula, This is the effect link disturbance index. This represents the set of disturbed links.

[0030] It should be noted that in the calculation of the link disturbance index mentioned above, all the data required for each calculation comes from the automatic collection and analysis of link-level operational behavior by the test platform throughout the entire test execution cycle, and the entire process requires no manual input. First, the data in the basic configuration baseline regarding the call relationships between modules, start and end node numbers, and control status comes from the structured configuration files or service registry information loaded by the system during the initialization phase, such as service dependency lists, interface call tables, and microservice topology registration data. The platform can extract the start point, end point, and control status of each link by parsing this information, thereby generating the basic link state matrix. Second, the data of the modified link state matrix during the test is collected in real time by the platform's operation monitoring engine when executing test tasks. This engine captures the request traffic, call success rate, interface response identifiers, and status codes between modules, determines whether the link is in an enabled, disabled, or conditionally triggered state at the current moment, and automatically generates the modified link state matrix. The calculation of the dynamic disturbance difference matrix is ​​based on the real-time call logs recorded by the platform. ΔM(s,t) can be obtained by comparing the changes in link status within each time slice. The data for link path length and the number of coupled chains come from the system's internal topology analysis module: the platform stores the path depth information of each link during the basic configuration phase and can calculate the number of nodes traversed by the path based on the dependency graph to obtain the path length; simultaneously, the platform scans all links sharing the same start or end point, counts the number of couplings, and uses this as input for the number of coupled chains. Ultimately, all this raw data is automatically extracted, compared, and calculated by the platform before and after the test task execution, ensuring that the input data for the link disturbance index is consistent, authentic, and has temporal continuity, so that the calculation results can objectively reflect the actual disturbance of the system's path structure during the test.

[0031] The Link Disturbance Index measures the degree to which the overall stability and connectivity of system call links are disrupted during testing. It reflects the "intensity of interference between test behaviors and the logical relationships between system modules." Specifically, this index considers not only whether links have been modified but also the path depth and coupling density of the links within the system topology. A larger Link Disturbance Index indicates more affected links, wider distribution, and these links are mostly located in the core layer with shorter paths or tighter coupling relationships. This means that the test behavior has touched the critical communication structure of the system, causing the call paths between modules to be reconstructed or interrupted. For example, if only the edge log service or cache refresh channel is modified, even with many state changes, the disturbance index will still be small due to its long path and low correlation with the main logic module, and the impact on the overall system stability will be limited. However, if a test mistakenly changes the call switch between the core authentication service and the scheduling center from enabled to disabled, although only one link is modified, the short path and multiple coupling chains of this link will cause the disturbance index to rise sharply, indicating that the modification has disrupted the main process's communication path. If the system is not automatically restored to the baseline configuration after the test, any subsequent tests may be executed under the corrupted topology, leading to severe deviations or unreproducible test results. In other words, the larger the link disturbance index, the further the system's operating structure deviates from the baseline, and the worse the controllability and consistency of the test environment. Therefore, it is necessary to roll back the environment immediately after the test to return the system to a controlled and stable baseline state, avoiding long-term distortion or error inheritance caused by the cumulative effect of configuration drift. This mechanism dynamically distinguishes between "acceptable testable changes" and "destructions that threaten environmental consistency," enabling automatic self-healing and baseline maintenance after testing, ensuring that the multi-environment test platform maintains high consistency and repeatability over the long term.

[0032] The advantage of calculating the link disturbance index using the above method is that it is not a simple "static difference comparison" of counting the number of links or the number of state changes. Instead, it starts from the topological connectivity of the system structure and the functionally dependent link hierarchy, dynamically measuring the actual degree of damage to the system communication path by the test behavior, thereby achieving accurate quantification of "structural disturbance". Specifically, this calculation method first introduces the triple structure of links, making each call path explicit and corresponding to the basic configuration baseline, so that the calculation not only focuses on whether the link has changed, but also identifies its position and role in the system. Second, the formula includes the path length and the number of coupled links in the denominator, reflecting the weight difference of the disturbance at different structural layers - core links are short and have many couplings, so even if a single link is modified, it will cause the index to rise, while the overall impact of multiple modifications to edge links is still limited. At the same time, the comparison matrix ΔM(s,t) can capture the instantaneous and persistent characteristics of link state switching in the time dimension, so that the index can reflect "whether the disturbance has structural influence", rather than just "how many changes have occurred". Compared to traditional evaluation methods based on log counts, error rate statistics, or average call latency, the biggest advantage of this approach is that it directly bases its calculations on the internal logical relationships of the system, without relying on additional performance metrics or manual threshold settings, thus avoiding misjudgments caused by environmental differences or load fluctuations. For example, traditional methods might consider the link changes in two test scenarios to be roughly equivalent, but using the calculation method of this invention, the system can identify that one scenario modified the main control chain, while the other only adjusted the auxiliary monitoring module, resulting in completely different disturbance index results. This not only improves the accuracy of the judgment but also allows the platform to automatically distinguish between "tolerable local disturbances" and "structural damage requiring rollback." Therefore, this calculation method based on structural relationships and path characteristics can achieve a more physically meaningful characterization of system stability while maintaining high computational efficiency, making the link disturbance index a reliable basis for automatic environmental recovery decisions after testing.

[0033] In one embodiment, S5: The step of comparing the damage index with a preset threshold and determining whether to test the basic configuration baseline of the environment based on the comparison result is as follows: When the damage index is less than the preset threshold, it is determined that the test has not damaged the basic configuration of the test environment, and there is no need to restore the basic configuration baseline. When the destruction index is not less than the preset threshold, it is determined that the basic configuration of the test environment has been destroyed in this test, and the test environment will be automatically restored to the basic configuration baseline after the test ends.

[0034] It's important to note that the calculated disruption index is compared to a preset threshold to determine whether the test has caused structural damage to the test environment's basic configuration, thus deciding whether automatic recovery is necessary. Specifically, the preset threshold is an empirical critical value learned from multiple historical test samples during the system initialization phase, used to distinguish between "normal, tolerable test configuration adjustments" and "destructive configuration drift." When the disruption index is less than this threshold, it indicates that the configuration changes during the test are limited to the test parameter level, such as adjusting log levels, adding performance monitoring items, or temporarily disabling certain non-critical interfaces. These operations do not affect the core structure of the environment, so the test environment can be considered to remain within a stable and controllable range, and can be reused without restoring the baseline after the test. However, when the disruption index is not less than the preset threshold, the system determines that the test behavior has altered core configuration relationships, such as broken service dependencies, blocked main path calls, or mismatched core component states. This type of damage will cause the environment structure to deviate too much from the baseline. If not restored in time, subsequent tests may run under incorrect configurations, resulting in distorted test results or inconsistencies across environments. For example, if a performance load test mistakenly changes the rate limiting policy of the caching service from enabled to disabled, the disruption index will increase significantly, triggering the automatic rollback mechanism. The system will immediately re-import the basic configuration baseline after the test, restoring the caching policy to the enabled state. In this way, the testing platform can dynamically determine the risk level of testing behavior based on quantitative indicators without manual intervention, achieving automatic environment state repair and baseline reconstruction. This avoids the long-term accumulation of configuration drift, thereby ensuring the continuous consistency of the unified testing system across multiple environments and the reliability of test results.

[0035] Based on the same inventive concept, this invention also provides a unified testing system for intelligent agents in multiple environments. See also Figure 2 , Figure 2 This invention provides a framework diagram of a unified multi-environment testing system for intelligent agents, comprising: Basic configuration module: Presets basic configurations for the test environment and generates a basic configuration baseline for the test environment based on the basic configurations; Configuration snapshot module: Before each test begins, it obtains the current running configuration of the test environment and records it as a pre-test configuration snapshot; Modification module: During the test, the module detects and records configuration modifications to the test environment, forming a set of configuration modifications for this test. The set of configuration modifications includes adjustments to test parameters and potential modifications to the basic configuration of the test environment. Destruction Module: After the test is completed, the set of configuration modifications is compared with the baseline configuration. The destruction index is calculated based on the comparison results. The destruction index is used to quantify the degree of destruction to the baseline configuration caused by this test. Update the test module: compare the damage index with the preset threshold, and determine whether the test environment's basic configuration baseline is met based on the comparison results.

[0036] Based on the intelligent agent multi-environment unified testing system provided by this invention, the following methods are employed: First, by setting a basic configuration for the test environment and generating a basic configuration baseline, the system solves the problem of long-term uncontrollable environments caused by the lack of a unified baseline in existing testing platforms, ensuring that all tests are conducted under consistent initial conditions. Second, by recording a configuration snapshot before the test, the system ensures that the platform can accurately identify the differences between the current test and the baseline, avoiding misjudgments caused by unclear pre-test configurations. Third, by detecting and recording all configuration modifications during the test, the system can accurately distinguish between "temporary adjustments used only for testing" and "sensitive modifications that may damage the basic configuration," solving the problem of untraceable test operations in existing technologies. Fourth, by calculating a destruction index to quantify the impact of the test on the basic configuration, the system transforms judgment from relying on human experience into an objective and measurable indicator, overcoming the technical deficiency of traditional methods in accurately assessing the degree of damage to the basic configuration. Fifth, by comparing the destruction index with a threshold, the system automatically determines whether the basic configuration baseline needs to be restored, ensuring environmental consistency while avoiding the resource waste and execution delays caused by forced resets for each test. Finally, through these steps, the system achieves intelligent, low-cost, and controllable consistency protection of the test environment, effectively preventing test result distortion and test conclusion invalidation caused by implicit damage to the basic configuration.

[0037] In one embodiment, the sabotage module includes: Damage Index Calculation Module: Based on the comparison results, calculate the structural stability offset index and the active link disturbance index of the basic configuration. The damage index is obtained by adding these two indices together.

[0038] In one embodiment, the destruction module further includes: Numbering module: Constructs a basic topology graph based on the dependencies between configuration items in the basic configuration baseline. , and Indicates the configuration item number; when the number is... The configuration item and the first When a configuration item has a direct structural dependency ,otherwise ; Topology Offset Matrix Module: Based on the configuration modification set for this test, the basic topology map is updated to obtain the modified topology map. And calculate the topological offset matrix. , If the structure changes, then ,otherwise ; Perturbation path tensor module: for all satisfying For each configuration item pair, calculate its shortest path distance in the basic topology graph. And construct the structural perturbation path tensor The calculation formula is: ;; Local structural fracture amplitude module: Extracts the in-degree and out-degree of each configuration item in the basic topology map and the modified topology map, calculates the local structural fracture amplitude, and uses the following formula: In the formula, Indicates the first The extent of local structural fracture in each configuration item. , These represent configuration items. In-degree and out-degree in a basic topological graph; , These represent configuration items. In-degree and out-degree in the modified topological graph; Discrete Amplitude Index Module: Based on the local structural fracture amplitude of all configuration items. Calculate the discrete amplitude exponent The calculation formula is: ; Structural stability offset index module: The structural stability offset index is obtained by adding the discrete amplitude index and the structural disturbance path tensor.

[0039] In one embodiment, the sabotage module includes: Link module: Represents each call link in the basic configuration baseline as a triple. ,in: Number the module at the beginning of the link; Number the link endpoint module; This indicates the control state of the link under the basic configuration, taking a value of 0 or 1; this is used to generate the link state matrix. Its elements are defined as ; Dynamic Disturbance Difference Matrix Module: Records the actual trigger records of all link states during the test, forming a modified matrix. And calculate the dynamic disturbance difference matrix. The calculation formula is: ;in, Indicates link During the test, was the state disturbed? If the link state changes from enabled to disabled or vice versa, then... Otherwise, it is 0; The link disturbance module: for each disturbed link Extract its path length With the number of coupling chains And calculate the link disturbance index. The calculation formula is: In the formula, This is the effect link disturbance index. This represents the set of disturbed links.

[0040] In one embodiment, the update test module includes: First comparison module: When the damage index is less than the preset threshold, it is determined that the test has not damaged the basic configuration of the test environment and there is no need to restore the basic configuration baseline. The second comparison module: When the destruction index is not less than the preset threshold, it is determined that the basic configuration of the test environment has been destroyed in this test, and the test environment will be automatically restored to the basic configuration baseline after the test ends.

[0041] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for unified testing of agents in multiple environments, the method comprising: The method comprises the following steps: presetting a basic configuration for a test environment, and generating a basic configuration baseline of the test environment based on the basic configuration; acquiring a current running configuration of the test environment before each test starts, and recording the configuration as a pre-test configuration snapshot; detecting and recording configuration modifications to the test environment during the test, and forming a configuration modification set for the test, wherein the configuration modification set comprises adjustments to test parameters and potential modifications to the basic configuration of the test environment; comparing the configuration modification set with the basic configuration baseline after the test ends, and calculating a damage index according to the comparison result; comparing the damage index with a preset threshold, and determining whether the basic configuration baseline of the test environment according to the comparison result. 2.The unified test method for intelligent agents in multiple environments according to claim 1, characterized in that, The step of calculating the damage index according to the comparison result comprises: calculating a structure stability offset index and an action link disturbance index of the basic configuration according to the comparison result, and adding the two indexes to obtain the damage index. 3.The unified testing method for intelligent agents in multiple environments according to claim 2, characterized in that, The calculation step of the structure stability offset index comprises: According to the dependency relationship between each configuration item in the basic configuration baseline, a basic topology map is constructed , and represent the number of configuration items; when the first configuration item has a direct structural dependency with the first configuration item, , otherwise ; According to the configuration modification set of this test, the base topology map is updated to obtain a modified topology map , and a topology offset matrix is calculated , ; if the structure changes, then , otherwise ; For all configuration item pairs satisfying , calculate their shortest path distances in the base topology map , and construct the structural disturbance path tensor The formula for calculation is: ; The in-degree and out-degree of each configuration item in the basic topology graph and the modified topology graph are extracted, and the local structure breaking amplitude is calculated, and the formula is: , wherein, the local structure breaking amplitude of the i-th configuration item, , , the in-degree and out-degree of the configuration item, , , the in-degree and out-degree of the configuration item, in the modified topology graph. According to the local structure break amplitude of all configuration items Computing the discrete amplitude index , the formula for calculation is: ; adding the discrete amplitude index and the structure disturbance path tensor to obtain the structure stability offset index. 4.The unified testing method for intelligent agents in multiple environments according to claim 2, characterized in that, The calculation step of the action link disturbance index comprises: Each call link in the base configuration baseline is represented as a triple where is the module number of the link origin; is the module number of the link destination; denotes the control state of the link under the base configuration, taking 0 or 1; thus generating the link state matrix whose elements are defined as ; All actual trigger records of link states are recorded during the test to form a modified matrix , and a dynamic disturbance difference matrix is calculated , the formula of which is: ; wherein, represents whether the link state is disturbed in the test; if the link state changes from enabled to disabled or from disabled to enabled, , otherwise 0; For each disturbed link , extract its path length and the number of coupled links , and calculate the link disturbance index , the formula is: , where is the link disturbance index, denotes the disturbed link set.

5. The method of claim 1, wherein, The step of determining whether the basic configuration baseline of the test environment according to the comparison result comprises: when the damage index is less than the preset threshold, determining that the basic configuration of the test environment is not damaged in the test, and there is no need to restore the basic configuration baseline; when the damage index is not less than the preset threshold, determining that the basic configuration of the test environment is damaged in the test, and automatically restoring the test environment to the basic configuration baseline after the test ends.

6. An agent multi-environment unified testing system, characterized in that, The system comprises: a basic configuration module configured to preset a basic configuration for a test environment, and generate a basic configuration baseline of the test environment based on the basic configuration; a configuration snapshot module configured to acquire a current running configuration of the test environment before each test starts, and record the configuration as a pre-test configuration snapshot; a modification module configured to detect and record configuration modifications to the test environment during the test, and form a configuration modification set for the test, wherein the configuration modification set comprises adjustments to test parameters and potential modifications to the basic configuration of the test environment; a damage module configured to compare the configuration modification set with the basic configuration baseline after the test ends, and calculate a damage index according to the comparison result; an update test module configured to compare the damage index with a preset threshold, and determine whether the basic configuration baseline of the test environment according to the comparison result.

7. The unified testing system for intelligent entities in multiple environments according to claim 6, wherein, The damage module comprises: a damage index calculation module configured to calculate a structure stability offset index and an action link disturbance index of the basic configuration according to the comparison result, and add the two indexes to obtain the damage index. 8.The unified test system for intelligent agents in multiple environments according to claim 7, wherein, The damage module further comprises: Numbering module: according to the dependency relationship between each configuration item in the basic configuration baseline, the basic topology atlas is constructed , and represent the number of configuration items; when the first configuration item has a direct structural dependency with the first configuration item, , otherwise ; Topology offset matrix module: according to the configuration modification set of this test, the basic topology graph is updated to obtain the modified topology graph , and the topology offset matrix is calculated , ; If the structure changes, then , else ; Disturbance path tensor module: for all configuration item pairs satisfying , calculate its shortest path distance in the base topology map , and construct the structure disturbance path tensor , the formula for calculation is: ; ; Local structure fracture amplitude module: extract the in-degree and out-degree of each configuration item in the basic topology graph and the modified topology graph, calculate the local structure fracture amplitude, the formula is: , wherein, represents the local structure fracture amplitude of the i-th configuration item, , , respectively represent the in-degree and out-degree of the configuration item in the basic topology graph; , respectively represent the in-degree and out-degree of the configuration item in the modified topology graph; Discrete amplitude index module: local structure break amplitude according to all configuration items Computing discrete amplitude index , the formula is: ; a structure stability offset index module configured to add a discrete amplitude index and a structure disturbance path tensor to obtain the structure stability offset index. 9.The unified test system for intelligent agents in multiple environments according to claim 7, wherein, The update test module comprises: Link module: Represent each call link in the base configuration baseline as a triple where is the link start module number; is the link end module number; denotes the control state of the link under the base configuration, taking 0 or 1; thus generating the link state matrix whose elements are defined as ; Dynamic disturbance difference matrix module: record the actual trigger record of all link states during the test to form the modified matrix , and calculate the dynamic disturbance difference matrix , the formula is: ; wherein, indicates whether the link state is disturbed in the test; if the link state changes from enabled to closed or from closed to enabled, , otherwise 0; The active link perturbation module extracts the path length of each perturbed link and the number of coupled links and calculates the active link perturbation index The formula for the calculation is: wherein is the active link perturbation index, and the set of perturbed links is denoted by . 10.The unified test system for intelligent agents in multiple environments according to claim 7, wherein, a first comparison module configured to, when the damage index is less than the preset threshold, determine that the basic configuration of the test environment is not damaged in the test, and there is no need to restore the basic configuration baseline; a second comparison module configured to, when the damage index is not less than the preset threshold, determine that the basic configuration of the test environment is damaged in the test, and automatically restore the test environment to the basic configuration baseline after the test ends. ​

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