Product failure reproduction method and device, computer device, medium and program product

Abstract

The application relates to a product failure reproduction method and device, computer equipment, a medium and a program product. The method comprises the following steps: obtaining historical use data of a target product to be subjected to failure reproduction, the target product being an unstable failure product that has appeared failure; based on the historical use data, selecting a target stress type to be currently detected from a plurality of candidate stress types, and determining corresponding target stress parameters, the target stress type and the target stress parameters being used to set a current test condition of a reproduction test device; when the target product located in the reproduction test device is operated under the test condition, obtaining test data of the target product, and determining a failure reproduction result of the target product based on the test data, so as to improve the product failure reproduction accuracy.

Description

Technical Field

[0001] This application relates to the field of testing technology, and in particular to a product failure reproduction method, apparatus, computer equipment, medium, and program product. Background Technology

[0002] With the rapid development of electronic technology, electronic products are being used more and more widely. However, electronic product failures occur frequently, seriously affecting the stability and reliability of equipment. In particular, the problem of unstable failures (faults that cannot be reproduced) is becoming increasingly prominent, thus requiring the ability to reproduce electronic product failures.

[0003] In related technologies, offline testing is usually used to reproduce the failure of electronic products. However, offline methods are difficult to accurately reproduce failure scenarios, which means that the accuracy of failure reproduction is low. Summary of the Invention

[0004] Therefore, it is necessary to provide a product failure reproduction method, apparatus, computer equipment, medium, and program product that can improve the accuracy of failure reproduction in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for reproducing product failure, including:

[0006] Obtain historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure.

[0007] Based on the historical usage data, the target stress type to be detected is selected from multiple candidate stress types, and the corresponding target stress parameters are determined. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0008] When the target product located in the reproduction test equipment is run under the test conditions, test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the test data.

[0009] Secondly, this application also provides a product failure reproduction device, comprising:

[0010] The acquisition module is used to acquire historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure.

[0011] The first determining module is used to select the target stress type to be detected from multiple candidate stress types based on the historical usage data, and to determine the corresponding target stress parameters. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0012] The second determining module is used to acquire test data of the target product when the target product located in the reproduction test equipment is running under the test conditions, and to determine the failure reproduction result of the target product based on the test data.

[0013] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0014] Obtain historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure.

[0015] Based on the historical usage data, the target stress type to be detected is selected from multiple candidate stress types, and the corresponding target stress parameters are determined. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0016] When the target product located in the reproduction test equipment is run under the test conditions, test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the test data.

[0017] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0018] Obtain historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure.

[0019] Based on the historical usage data, the target stress type to be detected is selected from multiple candidate stress types, and the corresponding target stress parameters are determined. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0020] When the target product located in the reproduction test equipment is run under the test conditions, test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the test data.

[0021] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0022] Obtain historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure.

[0023] Based on the historical usage data, the target stress type to be detected is selected from multiple candidate stress types, and the corresponding target stress parameters are determined. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0024] When the target product located in the reproduction test equipment is run under the test conditions, test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the test data.

[0025] The aforementioned product failure reproduction method, apparatus, computer equipment, medium, and program products acquire historical usage data of the target product to be reproduced. The target product is an unstable product that has experienced failure before. This allows for the pre-selection of the target stress type from multiple candidate stress types based on historical usage data, and the determination of the corresponding target stress parameters. The target stress type and parameters are used to set the current test conditions of the reproduction test equipment. Thus, without traversing all test conditions one by one, matching test conditions are determined based on historical usage data for effective failure reproduction. Subsequently, when the target product is run under the test conditions within the reproduction test equipment, the target product is tested online using those conditions, and test data is acquired in real time. Based on this test data, the failure reproduction result of the target product under online testing can be accurately determined, thereby improving the accuracy of failure reproduction. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a diagram illustrating the application environment of a product failure reproduction method in one embodiment;

[0028] Figure 2 This is a flowchart illustrating a product failure reproduction method in one embodiment;

[0029] Figure 3 This is a schematic diagram illustrating the process of determining the target stress type and target stress parameters in one embodiment;

[0030] Figure 4 This is a schematic diagram of the failure reproduction steps in one embodiment;

[0031] Figure 5 This is a schematic diagram of a failure reproduction test in one embodiment;

[0032] Figure 6 This is a structural block diagram of a product failure reproduction device in one embodiment;

[0033] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0035] The product failure reproduction method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the reproduction test device 102 communicates with the computer device 104 via a network. The product failure reproduction method provided in this application embodiment can be executed by the reproduction test device 102 or the computer device 104 alone, or it can be executed collaboratively by the reproduction test device 102 and the computer device 104.

[0036] In some embodiments, the target product is placed inside the reproduction test device 102 and connected to an external power supply or driver, and the reproduction test device 102 is connected to a computer device 104. The computer device 104 acquires historical usage data of the target product to be reproduced, where the target product is an unstable product that has experienced failure. Based on the historical usage data, the computer device 104 selects the target stress type to be detected from multiple candidate stress types and determines the corresponding target stress parameters. The target stress type and target stress parameters are used to set the current test conditions of the reproduction test device 102. When the target product located inside the reproduction test device 102 is running under test conditions, the computer device 104 receives the test data of the target product sent by the reproduction test device 102, and determines the failure reproduction result of the target product based on the test data.

[0037] For example, if the failure reproduction result indicates that the failure was successfully reproduced, then failure analysis is performed based on the test data to determine the failure mechanism.

[0038] The reproduction test equipment 102 can be understood as a test chamber, used to perform online testing on the target product and collect test data of the target product during runtime (when performing online testing). The computer equipment 104 can be a terminal or a server. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0039] In one exemplary embodiment, such as Figure 2 As shown, a method for reproducing product failure is provided, which can be applied to... Figure 1 Taking computer device 104 as an example, the explanation includes the following steps S202 to S206. Wherein:

[0040] Step S202: Obtain historical usage data of the target product to be reproduced. The target product is an unstable product that has experienced failure.

[0041] The target product is an electronic product that has experienced unstable failures. It can also be a non-electronic product with fluctuating parameters or functions. Unstable failures refer to sporadic or transient failures characterized by instability. Target historical usage data refers to data generated during previous use of the target product. This data may include previous failures, model information, and the application circuits used. Target historical usage data can be compiled by the product user. For example, if a failure occurs during product use, the user records the failure phenomenon, the environmental information of the target product at the time of the failure, and the application circuits used to obtain target historical usage data. This data is then sent to a computer (as the failure reproducer) to instruct the computer to reproduce the failure based on the target historical data for failure analysis.

[0042] For example, after enabling failure reproduction of the target product, the computer device obtains the historical usage data of the target product based on the data input operation.

[0043] For example, each time a failure reproduction cycle is reached, the computer device automatically acquires historical usage data of the target product located in the reproduction test equipment.

[0044] Step S204: Based on historical usage data, select the target stress type to be detected from multiple candidate stress types and determine the corresponding target stress parameters. The target stress type and target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0045] The candidate stress type is the stress type that can be selected for failure reproduction. For example, the candidate stress type can be temperature type, humidity type, temperature and humidity alternation type, vibration type, etc. The stress parameter refers to the stress value or range. The target stress parameter and target stress type are matched with historical usage data, and the current test conditions are determined based on the target stress parameter and target stress type. These test conditions are applied to the target product, allowing the target product to be tested online under these conditions. For example, a preset stress is applied to the target product in the failure reproduction test equipment. The stress type of this preset stress is the target stress type, and the parameters of the preset stress are the target stress parameters. For example, the target stress type is temperature change stress, and the target stress parameters include a temperature change range of -55℃ to 85℃ and a temperature change rate of 15℃ / min.

[0046] For example, the computer device determines whether a historical failure reproduction record corresponding to the historical usage data exists based on historical usage data. If not, it selects the target stress type to be detected from multiple candidate stress types and determines the corresponding target stress parameters based on the historical usage data. The computer device then determines the current test conditions of the reproduction test equipment based on the target stress type and target stress parameters.

[0047] If there is a historical failure reproduction record corresponding to the historical usage data, the failure reproduction data is obtained from the historical implementation reproduction record, and failure analysis is performed based on the failure reproduction data to determine the failure mechanism.

[0048] For example, after determining the test conditions, the power supply to the target product is turned on, and the test is started to run under the test conditions, such as starting the run at the set temperature range and temperature change rate.

[0049] For example, after selecting the target stress type from multiple candidate stress types based on historical usage information, the target stress parameter corresponding to the historical usage information is determined from multiple stress parameters belonging to the target stress type.

[0050] For example, based on historical usage information, a target stress type is selected from multiple candidate stress types and a target stress parameter is selected from multiple candidate stress parameters.

[0051] For example, if the target stress type to be detected cannot be selected from multiple candidate stress types, a type selection failure message is sent to the reproduction test device for display, and the current test conditions are determined in response to the test information input operation on the reproduction test device.

[0052] In some embodiments, historical usage data includes at least the failures that have occurred with the target product, environmental information of the environment in which the failures occurred, and product attribute information of the target product.

[0053] For example, a failure phenomenon refers to an unstable failure that has previously occurred in the target product, such as short circuit, open circuit instability, leakage, etc. Environmental information refers to the operating environment in which the target product was used when the failure phenomenon occurred. The attribute information of the target product includes at least the application circuit used by the target product.

[0054] Therefore, in some embodiments, such as Figure 3 The diagram illustrates the process of determining the target stress type and target stress parameters in one embodiment. Based on historical usage data, the currently detected target stress type is selected from multiple candidate stress types, and the corresponding target stress parameters are determined, including:

[0055] Step S302: If no failure reproduction data related to historical usage data can be found locally, obtain a mapping table for determining test conditions. The mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions.

[0056] The mapping table contains many-to-one mapping relationships. For example, the mapping relationship is that a failure phenomenon, environmental information, and product attribute information correspond to a single test information. For instance, after determining the failure phenomenon, environmental information, and product attribute information, a corresponding test information is determined based on the mapping relationship.

[0057] For example, the computer device queries the local machine to see if there are historical failure reproduction records. If they exist, it determines that there is failure reproduction data related to historical usage data and performs failure analysis based on the failure reproduction data. If they do not exist, step S302 is executed.

[0058] Step S304: Based on the failure phenomenon, environmental information, and product attribute information of the target product, find the test information corresponding to the target product from the mapping table. The test information includes the recommended stress type and recommended stress parameters.

[0059] Step S306: If a recommended stress type exists among multiple candidate stress types, the recommended stress type is taken as the target stress type, and the recommended stress parameters are taken as the target stress parameters.

[0060] Among them, the candidate stress type is the stress type provided by the test equipment, and the recommended stress type is the stress type automatically recommended based on historical usage data.

[0061] For example, after obtaining the test information, it is checked whether there is a recommended stress type among the multiple candidate stress types stored in advance. If there is, the recommended stress type is used as the target stress type, and it is determined whether the recommended stress parameters meet the parameter conditions of the recommended stress type. If they do, the recommended stress parameters are used as the target stress parameters.

[0062] For example, if the recommended stress parameter is a stress parameter range, then it is determined whether the stress parameter range exceeds the standard stress range of the recommended stress type. If it does not exceed the standard stress range (i.e., the stress parameter range is a subset of the standard stress range), then it is determined that the parameter conditions of the recommended stress type are met. If the recommended stress parameter is a stress parameter value, then it is determined whether the stress parameter value is within the standard stress range of the recommended stress type. If it is, then it is determined that the parameter conditions of the recommended stress type are met.

[0063] In this embodiment, the mapping table used to determine test conditions can quickly and accurately determine the test conditions that match the target product without having to go through all the test conditions one by one, thus improving the efficiency of failure reproduction. At the same time, based on the matched test conditions, the accuracy of failure reproduction can be effectively improved.

[0064] Step S206: When the target product is running under test conditions in the reproduction test equipment, acquire the test data of the target product, and determine the failure reproduction result of the target product based on the test data.

[0065] The test data refers to the data collected in real time when the target product is running under test conditions; it can be understood as the data collected during online testing. The test data must include at least one data type, such as voltage data, current data, resistance data, and waveform data.

[0066] The failure reproduction result is used to indicate whether the failure phenomenon that occurred was successfully reproduced when running under the test conditions.

[0067] For example, when the target product located in the reproduction test equipment is running under test conditions, the reproduction test equipment collects data about the target product within a preset collection period and sends it to the computer equipment. The computer equipment preprocesses the received data to obtain the test data of the target product and determines the failure reproduction result of the target product based on the test data.

[0068] For example, when the target product is running under test conditions within the reproduction test equipment, the computer sends a data acquisition command to the reproduction test equipment, acquires data based on the acquisition duration specified in the command, and sends the acquired data back to the computer. The computer then preprocesses the received data to obtain the test data for the target product.

[0069] Preprocessing can involve cleaning the data, such as removing invalid data, to avoid interfering with the reproduction of failures.

[0070] In some embodiments, determining the failure reproduction result of the target product based on test data includes: acquiring normal data of the target product and comparing the normal data with the test data; if the comparison result indicates that the normal data and the test data are inconsistent, then extracting the data that is inconsistent with the normal data from the test data, using the extracted data as the failure reproduction data of the target product, and determining that the failure reproduction is successful; if the comparison result indicates that the normal data and the test data are consistent, then determining that the failure reproduction is unsuccessful.

[0071] Normal data refers to data collected from the target product when no failure occurs. This normal data can be provided by the product user or collected in advance by the computer equipment before proceeding to step S202.

[0072] For example, the computer device obtains normal data of the target product from the local machine, or sends a data acquisition request to the product user to instruct the product user to send the normal data corresponding to the product identifier to the computer device based on the product identifier in the data acquisition request.

[0073] For example, the data type to be compared is determined. For each data type to be compared, the computer device compares whether the first data of the data type in the normal data is consistent with the second data of the data type in the test data, and obtains the comparison result of the data type.

[0074] If the computer device verifies that the comparison results for each data type to be compared are consistent, then the failure reproduction is determined to have failed. If the computer device verifies that the comparison results for at least one data type to be compared are inconsistent, then the failure reproduction is determined to have succeeded.

[0075] For example, the data type to be compared can be determined by the test functions of each test point in the target product, or at least one candidate test point can be selected from all test points, and the test function of the candidate test point can be used as the data type to be compared. There are no specific limitations.

[0076] In this embodiment, by comparing normal data with test data, the failure reproduction result can be accurately and quickly determined, thereby improving the accuracy of failure reproduction.

[0077] In the aforementioned product failure reproduction method, historical usage data of the target product to be reproduced is obtained. The target product is an unstable product that has experienced failure. This allows for the pre-selection of the target stress type from multiple candidate stress types based on historical usage data, and the determination of the corresponding target stress parameters. The target stress type and parameters are used to set the current test conditions of the reproduction test equipment. Thus, without traversing all test conditions one by one, the matching test conditions are determined based on historical usage data for effective failure reproduction. Subsequently, when the target product is run under the test conditions within the reproduction test equipment, the target product is tested online according to the test conditions, and the test data of the target product is acquired in real time. Based on this test data, the failure reproduction result of the target product under online testing can be accurately determined, thereby improving the accuracy of failure reproduction.

[0078] In some embodiments, the method further includes: obtaining multiple candidate test points located on the target product based on the product attribute information of the target product; dividing the multiple candidate test points into at least one candidate set based on the degree of correlation between each candidate test point and other candidate test points, wherein the multiple candidate test points in the same candidate set have a high degree of correlation; for each candidate set, randomly selecting at least one candidate test point as a target test point, wherein each target test point is used to collect data to obtain test data.

[0079] The product attribute information includes circuit information used in the product, which is used to determine the correlation between various candidate test points in the circuit. Candidate test points are points on the product's circuitry that can be used for data acquisition; for example, a current pin might be a candidate test point, as might a voltage pin. A high correlation between two candidate test points indicates that their failures are mutually influential; that is, if one candidate test point fails, the other will also fail. A low correlation indicates that their failures are independent; that is, if one candidate test point fails, the other will not fail.

[0080] For example, a computer device obtains circuit information based on the product attribute information of the target product. Based on the circuit information, it determines multiple candidate test points on the target product and the correlation between each candidate test point and other candidate test points. The computer device obtains a correlation threshold that matches the target product. Based on this correlation threshold and the correlation between each candidate test point and other candidate test points, the multiple candidate test points are divided into at least one candidate set. The correlation between multiple test points in each candidate set is higher than the correlation threshold, that is, the correlation between multiple candidate test points in the same candidate set is high, and the correlation between different candidate sets is low.

[0081] For each candidate set, a candidate test point is randomly selected from the candidate set as the target test point. Data values ​​of the corresponding data type are collected based on the function of the target test point to obtain test data.

[0082] Alternatively, for each candidate set, multiple candidate test points are randomly selected from the candidate set as target test points, with the number of selected candidate test points being less than the total number of candidate test points in the candidate set. Data values ​​of the corresponding data type are collected based on the function of the target test points to obtain the test data.

[0083] For example, there are 5 candidate test points, P1-P5. The correlation between any two candidate test points P1, P2, and P3 is greater than the correlation threshold, and the correlation between P4 and P5 is also greater than the correlation threshold. Therefore, P1, P2, and P3 belong to candidate set 1, and P4 and P5 belong to candidate set 2. Next, P1 is selected as the target test point from candidate set 1, and P4 is also selected as the target test point from candidate set 2. This eliminates the need to collect data for every candidate test point; data is only collected for the target test points selected from the candidate sets. Compared to collecting 5 types of data previously, this embodiment only requires collecting 2 types of data, reducing the amount of data collected and improving the efficiency of failure reproduction while ensuring the effectiveness of failure reproduction.

[0084] For example, for each candidate set, the computer device selects the candidate test point with the highest historical failure rate as the target test point based on the historical failure rate of each candidate test point in the candidate set.

[0085] In this embodiment, at least one candidate set is determined based on the correlation between each candidate test point and other candidate test points. That is, multiple related candidate test points are placed into a candidate set. Then, target test points are selected from the candidate set for data collection. This eliminates the need to collect data for each candidate test point, and only collects data for the target test points selected from the candidate set. This reduces the amount of data collection and improves the efficiency of failure reproduction while ensuring the effectiveness of failure reproduction.

[0086] In some embodiments, the method further includes: when the failure reproduction result indicates that the failure reproduction has failed, obtaining test condition requirement information related to the target product, calling a large language model to perform semantic understanding on the test condition requirement information to obtain new test conditions; when the target product located in the reproduction test equipment is running under the new test conditions, obtaining new test data of the target product, and determining the failure reproduction result of the target product based on the new test data.

[0087] Among them, a large language model refers to a deep learning model trained using a large amount of text data, capable of generating natural language text or understanding the meaning of language text. Test condition requirement information is used to request test conditions related to the target product.

[0088] For example, when the failure reproduction result indicates that the failure reproduction has failed, the computer device determines the prompt text based on the successful failure reproduction cases of other products, calls the large language model, and performs semantic understanding of the test condition requirement information through the prompt text to obtain new test conditions.

[0089] For example, the new test conditions are different from the current test conditions.

[0090] In some embodiments, a large language model is invoked to perform semantic understanding on the test condition requirement information to obtain new test conditions, including: obtaining a prompt text, which includes a question and an answer to the question, wherein the question is used to inquire about other test conditions used when reproducing failures in other products; invoking the large language model to identify the question-and-answer format of the prompt text, and using the test condition requirement information as the question, determining the answer to the test condition requirement information according to the question-and-answer format, wherein the answer to the test condition requirement information is used to determine the new test conditions.

[0091] For example, the notification text is a message indicating successful failure reproduction. This notification text contains multiple positive question-and-answer pairs (indicating successful failure reproduction based on the recommended test conditions in the responses). Each positive question-and-answer pair includes a question and a corresponding answer. The question inquires about alternative test conditions for other products, and the answer states that other test conditions were used to successfully reproduce the failure of those other products. The test condition requirement information indicates that new test conditions should not contain target stress types or target stress parameters.

[0092] For example, a question using test condition requirements as a question could be: "Please determine the test conditions for the target product. The test conditions do not include the target stress type or target stress parameter." Correspondingly, an answer using a question-and-answer format to determine the test condition requirements could be: "Other stress types and other stress parameters."

[0093] In this way, by using a large language model to determine the prompt text based on other test conditions when reproducing failures in other products, the large language model can semantically understand the test condition requirements and select new test conditions from the perspective of the large language model to ensure the normal execution of failure reproduction of the target product.

[0094] In this embodiment, after running the target product with the target stress type and target stress parameters and determining that the reproduction has failed, the large language model is invoked to perform semantic understanding of the test condition requirement information, and new test conditions are determined to ensure the normal execution of the failure reproduction of the target product.

[0095] In one specific embodiment, after the computer (personal computer, belonging to the terminal) is connected to the reproduction test device, as follows: Figure 4 The diagram shown is a schematic representation of the failure reproduction steps in one embodiment. (Refer to...) Figure 4 Perform the following steps:

[0096] Step 1: Stress determination, i.e., determining the target stress type and target stress parameters.

[0097] Specifically, the computer obtains multiple candidate test points located on the target product based on the product attribute information of the target product; based on the degree of correlation between each candidate test point and other candidate test points, the multiple candidate test points are divided into at least one candidate set, and the multiple candidate test points in the same candidate set have a high degree of correlation; for each candidate set, at least one candidate test point is randomly selected from the candidate set as a target test point, and each target test point is used to collect data to obtain test data.

[0098] The computer acquires historical usage data of the target product to be reproduced, where the target product is an unstable product that has experienced failure. The historical usage data includes at least the failure phenomena that occurred with the target product, environmental information about the environment in which the failure occurred, and product attribute information. If no failure reproduction data related to the historical usage data is found locally, a mapping table is obtained to determine the test conditions. This mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information, and test information for the test conditions. Based on the failure phenomena, environmental information, and product attribute information of the target product, the corresponding test information is retrieved from the mapping table. This test information includes recommended stress type and recommended stress parameters. If a recommended stress type exists among multiple candidate stress types, it is used as the target stress type, and the recommended stress parameters are used as the target stress parameters. The target stress type and target stress parameters are used to set the current test conditions for the reproduction test equipment.

[0099] Step 2: Apply stress to the target product located inside the reproduction test equipment, i.e., run it under the current test conditions.

[0100] Specifically, such as Figure 5 The diagram shown is a schematic diagram of a failure reproduction test in one embodiment. Figure 5The device under test (DUT) is the target product, and the DUT is located in the reproduction test equipment. Figure 5 Within (not shown), environmental stress refers to the stress applied to the target product, the type of which is the target stress type, and the parameter is the target stress parameter. Figure 5 The computer (personal computer) is a terminal. Data is acquired through a power supply, signal source, electronic load, multi-channel triggering and timing synchronization management module (timing management unit), data acquisition instrument (multiplexer), source meter, multimeter, waveform recorder, and oscilloscope to determine the test data.

[0101] Step 3: Conduct failure reproduction tests.

[0102] Step 4: Record the data.

[0103] Specifically, the computer acquires recorded data; that is, when the target product is running under test conditions within the reproduction test equipment, the computer acquires the test data of the target product. Then, it acquires the normal data of the target product and compares it with the test data. If the comparison result indicates that the normal data and the test data are inconsistent, the inconsistent data is extracted from the test data and used as the failure reproduction data for the target product, thus confirming successful failure reproduction. If the comparison result indicates that the normal data and the test data are consistent, then failure reproduction is confirmed as a failure.

[0104] In the event that failure reproduction fails, the computer acquires test condition requirement information related to the target product and obtains a prompt text. This prompt text includes a question and an answer, where the question inquires about alternative test conditions used for failure reproduction on other products. A large language model is invoked to identify the question-and-answer format of the prompt text. Using the test condition requirement information as the question, the answer is determined according to the question-and-answer format. The answer is used to determine the new test conditions. When the target product, located within the reproduction test equipment, runs under the new test conditions, new test data for the target product is acquired, and the failure reproduction result is determined based on this new test data.

[0105] In this embodiment, historical usage data of the target product to be reproduced is acquired. The target product is an unstable product that has experienced failure. This allows for the selection of the target stress type from multiple candidate stress types based on historical usage data, and the determination of the corresponding target stress parameters. The target stress type and parameters are used to set the current test conditions of the reproduction test equipment. Thus, without traversing all test conditions one by one, the matching test conditions are determined based on historical usage data for effective failure reproduction. Subsequently, when the target product is run under the test conditions within the reproduction test equipment, the target product is tested online using these conditions, and the test data is acquired in real time. Based on this test data, the failure reproduction result of the target product under online testing can be accurately determined, thereby improving the accuracy of failure reproduction.

[0106] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0107] Based on the same inventive concept, this application also provides a product failure reproduction device for implementing the product failure reproduction method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more product failure reproduction device embodiments provided below can be found in the limitations of the product failure reproduction method described above, and will not be repeated here.

[0108] In one exemplary embodiment, such as Figure 6 As shown, a product failure reproduction device 600 is provided, including: an acquisition module 602, a first determination module 604, and a second determination module 606, wherein:

[0109] The acquisition module 602 is used to acquire historical usage data of the target product to be reproduced. The target product is an unstable product that has experienced failure.

[0110] The first determining module 604 is used to select the target stress type to be detected from multiple candidate stress types based on historical usage data, and to determine the corresponding target stress parameters. The target stress type and target stress parameters are used to set the current test conditions of the reproduction test equipment.

[0111] The second determining module 606 is used to acquire test data of the target product when the target product is running under test conditions in the reproduction test equipment, and to determine the failure reproduction result of the target product based on the test data.

[0112] In some embodiments, historical usage data includes at least the failure phenomena that have occurred with the target product, environmental information of the environment in which the failure phenomena occurred, and product attribute information of the target product; the first determining module 604 is used to obtain a mapping table for determining test conditions when failure reproduction data related to historical usage data cannot be found locally, the mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions; based on the failure phenomena, environmental information and product attribute information of the target product, the test information corresponding to the target product is found from the mapping table, the test information includes recommended stress type and recommended stress parameter; if a recommended stress type exists among multiple candidate stress types, the recommended stress type is used as the target stress type and the recommended stress parameter is used as the target stress parameter.

[0113] In some embodiments, the apparatus further includes a selection module, which is configured to acquire multiple candidate test points located on the target product based on the product attribute information of the target product; divide the multiple candidate test points into at least one candidate set based on the degree of correlation between each candidate test point and other candidate test points, wherein the multiple candidate test points in the same candidate set have a high degree of correlation; and for each candidate set, randomly select at least one candidate test point as a target test point, wherein each target test point is used to collect data to obtain test data.

[0114] In some embodiments, the second determining module 606 is used to acquire normal data of the target product, compare the normal data with the test data; if the comparison result indicates that the normal data and the test data are inconsistent, then the data that is inconsistent with the normal data is extracted from the test data, and the extracted data is used as the failure reproduction data of the target product, and the failure reproduction is determined to be successful; if the comparison result indicates that the normal data and the test data are consistent, then the failure reproduction is determined to be unsuccessful.

[0115] In some embodiments, the first determining module 604 is further configured to, when the failure reproduction result indicates that the failure reproduction has failed, obtain test condition requirement information related to the target product, call a large language model to perform semantic understanding on the test condition requirement information, and obtain new test conditions; the second determining module 606 is configured to, when the target product located in the reproduction test equipment is running under the new test conditions, obtain new test data of the target product, and determine the failure reproduction result of the target product based on the new test data.

[0116] In some embodiments, the first determining module 604 is further configured to obtain a prompt text, which includes a question and an answer to the question. The question is used to inquire about other test conditions used when reproducing failures in other products. The module calls a large language model to identify the question-and-answer format of the prompt text, and uses the test condition requirement information as the question to determine the answer to the test condition requirement information according to the question-and-answer format. The answer to the test condition requirement information is used to determine new test conditions.

[0117] Each module in the aforementioned product failure reproduction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0118] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 7 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media to run. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a product failure reproduction method.

[0119] Those skilled in the art will understand that Figure 7The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0120] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring historical usage data of a target product to be reproduced, the target product being an unstable product that has experienced failure; based on the historical usage data, selecting the target stress type to be detected from multiple candidate stress types and determining the corresponding target stress parameters, the target stress type and target stress parameters being used to set the current test conditions of the reproduction test device; and when the target product located in the reproduction test device is run under test conditions, acquiring test data of the target product and determining the failure reproduction result of the target product based on the test data.

[0121] In one embodiment, historical usage data includes at least the failure phenomena that have occurred with the target product, environmental information of the environment in which the failure phenomena occurred, and product attribute information of the target product. When the processor executes the computer program, it also performs the following steps: if no failure reproduction data related to historical usage data can be found locally, a mapping table for determining test conditions is obtained. The mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information, and test information of test conditions. Based on the failure phenomena, environmental information, and product attribute information of the target product, the test information corresponding to the target product is found from the mapping table. The test information includes recommended stress type and recommended stress parameters. If a recommended stress type exists among multiple candidate stress types, the recommended stress type is used as the target stress type, and the recommended stress parameters are used as the target stress parameters.

[0122] In one embodiment, when the processor executes the computer program, it further performs the following steps: based on the product attribute information of the target product, it obtains multiple candidate test points located on the target product; based on the correlation between each candidate test point and other candidate test points, it divides the multiple candidate test points into at least one candidate set, wherein the correlation between multiple candidate test points in the same candidate set is high; for each candidate set, it randomly selects at least one candidate test point as a target test point, and each target test point is used to collect data to obtain test data.

[0123] In one embodiment, when the processor executes the computer program, it further performs the following steps: acquiring normal data of the target product and comparing the normal data with the test data; if the comparison result indicates that the normal data and the test data are inconsistent, then extracting the data that is inconsistent with the normal data from the test data, using the extracted data as the failure reproduction data of the target product, and determining that the failure reproduction is successful; if the comparison result indicates that the normal data and the test data are consistent, then determining that the failure reproduction is unsuccessful.

[0124] In one embodiment, when the processor executes the computer program, it further performs the following steps: when the failure reproduction result indicates that the failure reproduction has failed, it obtains test condition requirement information related to the target product, calls a large language model, performs semantic understanding on the test condition requirement information, and obtains new test conditions; when the target product located in the reproduction test equipment is running under the new test conditions, it obtains new test data of the target product, and determines the failure reproduction result of the target product based on the new test data.

[0125] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining a prompt text, the prompt text including a question and an answer to the question, the question being used to inquire about other test conditions used when reproducing failures in other products; invoking a large language model to identify the question-and-answer format of the prompt text, and using the test condition requirement information as the question, determining the answer to the test condition requirement information according to the question-and-answer format, the answer to the test condition requirement information being used to determine new test conditions.

[0126] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon. When executed by a processor, the computer program performs the following steps: acquiring historical usage data of a target product to be reproduced, wherein the target product is an unstable product that has experienced failure; selecting the target stress type to be detected from multiple candidate stress types based on the historical usage data, and determining the corresponding target stress parameters, wherein the target stress type and target stress parameters are used to set the current test conditions of the reproduction test equipment; and acquiring test data of the target product when the target product located in the reproduction test equipment is running under test conditions, and determining the failure reproduction result of the target product based on the test data.

[0127] In one embodiment, historical usage data includes at least the failure phenomena that have occurred with the target product, environmental information of the environment in which the failure phenomena occurred, and product attribute information of the target product. When the computer program is executed by the processor, it also performs the following steps: if no failure reproduction data related to historical usage data can be found locally, a mapping table for determining test conditions is obtained, the mapping table including the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions; based on the failure phenomena, environmental information and product attribute information of the target product, the test information corresponding to the target product is found from the mapping table, the test information including recommended stress type and recommended stress parameters; if a recommended stress type exists among multiple candidate stress types, the recommended stress type is used as the target stress type, and the recommended stress parameters are used as the target stress parameters.

[0128] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: based on the product attribute information of the target product, obtain multiple candidate test points located on the target product; based on the degree of correlation between each candidate test point and other candidate test points, divide the multiple candidate test points into at least one candidate set, wherein the degree of correlation between multiple candidate test points in the same candidate set is high; for each candidate set, randomly select at least one candidate test point from the candidate set as a target test point, and each target test point is used to collect data to obtain test data.

[0129] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: acquiring normal data of the target product and comparing the normal data with the test data; if the comparison result indicates that the normal data and the test data are inconsistent, then extracting the data that is inconsistent with the normal data from the test data, using the extracted data as the failure reproduction data of the target product, and determining that the failure reproduction is successful; if the comparison result indicates that the normal data and the test data are consistent, then determining that the failure reproduction is unsuccessful.

[0130] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: when the failure reproduction result indicates that the failure reproduction has failed, it obtains test condition requirement information related to the target product, calls a large language model, performs semantic understanding on the test condition requirement information, and obtains new test conditions; when the target product located in the reproduction test equipment is running under the new test conditions, it obtains new test data of the target product, and determines the failure reproduction result of the target product based on the new test data.

[0131] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining a prompt text, the prompt text including a question and an answer to the question, the question being used to inquire about other test conditions used when reproducing failures in other products; invoking a large language model to identify the question-and-answer format of the prompt text, and using the test condition requirement information as the question, determining the answer to the test condition requirement information according to the question-and-answer format, the answer to the test condition requirement information being used to determine new test conditions.

[0132] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: acquiring historical usage data of a target product to be reproduced, the target product being an unstable product that has experienced failure; based on the historical usage data, selecting the target stress type to be detected from multiple candidate stress types and determining the corresponding target stress parameters, the target stress type and target stress parameters being used to set the current test conditions of the reproduction test equipment; and, when the target product located within the reproduction test equipment is running under test conditions, acquiring test data of the target product and determining the failure reproduction result of the target product based on the test data.

[0133] In one embodiment, historical usage data includes at least the failure phenomena that have occurred with the target product, environmental information of the environment in which the failure phenomena occurred, and product attribute information of the target product. When the computer program is executed by the processor, it also performs the following steps: if no failure reproduction data related to historical usage data can be found locally, a mapping table for determining test conditions is obtained, the mapping table including the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions; based on the failure phenomena, environmental information and product attribute information of the target product, the test information corresponding to the target product is found from the mapping table, the test information including recommended stress type and recommended stress parameters; if a recommended stress type exists among multiple candidate stress types, the recommended stress type is used as the target stress type, and the recommended stress parameters are used as the target stress parameters.

[0134] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: based on the product attribute information of the target product, obtain multiple candidate test points located on the target product; based on the degree of correlation between each candidate test point and other candidate test points, divide the multiple candidate test points into at least one candidate set, wherein the degree of correlation between multiple candidate test points in the same candidate set is high; for each candidate set, randomly select at least one candidate test point from the candidate set as a target test point, and each target test point is used to collect data to obtain test data.

[0135] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: acquiring normal data of the target product and comparing the normal data with the test data; if the comparison result indicates that the normal data and the test data are inconsistent, then extracting the data that is inconsistent with the normal data from the test data, using the extracted data as the failure reproduction data of the target product, and determining that the failure reproduction is successful; if the comparison result indicates that the normal data and the test data are consistent, then determining that the failure reproduction is unsuccessful.

[0136] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: when the failure reproduction result indicates that the failure reproduction has failed, it obtains test condition requirement information related to the target product, calls a large language model, performs semantic understanding on the test condition requirement information, and obtains new test conditions; when the target product located in the reproduction test equipment is running under the new test conditions, it obtains new test data of the target product, and determines the failure reproduction result of the target product based on the new test data.

[0137] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining a prompt text, the prompt text including a question and an answer to the question, the question being used to inquire about other test conditions used when reproducing failures in other products; invoking a large language model to identify the question-and-answer format of the prompt text, and using the test condition requirement information as the question, determining the answer to the test condition requirement information according to the question-and-answer format, the answer to the test condition requirement information being used to determine new test conditions.

[0138] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0141] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for reproducing product failure, characterized in that, The method includes: Obtain historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure. Based on the historical usage data, the target stress type to be detected is selected from multiple candidate stress types, and the corresponding target stress parameters are determined. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment. When the target product located in the reproduction test equipment is run under the test conditions, test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the test data; wherein, the test data acquisition step includes: acquiring multiple candidate test points located on the target product based on the product attribute information of the target product; dividing the multiple candidate test points into at least one candidate set based on the correlation between each candidate test point and other candidate test points, wherein the correlation between multiple candidate test points in the same candidate set is high; for each candidate set, randomly selecting at least one candidate test point as a target test point, and each target test point is used to collect data to obtain test data; When the failure reproduction result indicates that the failure reproduction has failed, the test condition requirement information related to the target product is obtained, and the large language model is invoked to perform semantic understanding on the test condition requirement information to obtain new test conditions. When the target product located in the reproduction test equipment is run under the new test conditions, new test data of the target product is acquired, and the failure reproduction result of the target product is determined based on the new test data.

2. The method according to claim 1, characterized in that, The historical usage data includes at least the failure phenomena that have occurred with the target product, the environmental information of the environment in which the failure phenomena occurred, and the product attribute information of the target product. The step of selecting the target stress type to be detected from multiple candidate stress types based on the historical usage data and determining the corresponding target stress parameters includes: If no failure reproduction data related to the historical usage data can be found locally, a mapping table for determining test conditions is obtained. The mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions. Based on the failure phenomenon, environmental information, and product attribute information of the target product, the test information corresponding to the target product is retrieved from the mapping table. The test information includes recommended stress type and recommended stress parameters. If the recommended stress type exists among multiple candidate stress types, the recommended stress type is taken as the target stress type, and the recommended stress parameter is taken as the target stress parameter.

3. The method according to claim 1, characterized in that, The determination of the failure reproduction result of the target product based on the test data includes: Obtain normal data of the target product and compare the normal data with the test data; If the comparison results indicate that the normal data and the test data are inconsistent, then the data that is inconsistent with the normal data is extracted from the test data, and the extracted data is used as the failure reproduction data of the target product, and the failure reproduction is confirmed to be successful. If the comparison results indicate that the normal data is consistent with the test data, then the failure to reproduce the failure is determined to be unsuccessful.

4. The method according to claim 1, characterized in that, The process of calling a large language model to perform semantic understanding on the test condition requirement information and obtain new test conditions includes: Obtain prompt text, which includes a question and an answer to the question, wherein the question is used to inquire about other test conditions used when reproducing failures in other products; The large language model is invoked to identify the question-and-answer format of the prompt text, and the answer to the test condition requirement information is determined according to the question-and-answer format, based on the test condition requirement information. The answer to the test condition requirement information is used to determine new test conditions.

5. A product failure reproduction device, characterized in that, The device includes: The acquisition module is used to acquire historical usage data of the target product to be reproduced, wherein the target product is an unstable product that has experienced failure. The first determining module is used to select the target stress type to be detected from multiple candidate stress types based on the historical usage data, and to determine the corresponding target stress parameters. The target stress type and the target stress parameters are used to set the current test conditions of the reproduction test equipment. The second determining module is used to acquire test data of the target product when the target product is running under the test conditions within the reproduction test equipment, and to determine the failure reproduction result of the target product based on the test data; wherein, the device further includes a selection module, used to acquire multiple candidate test points located on the target product based on the product attribute information of the target product; based on the correlation between each candidate test point and other candidate test points, the multiple candidate test points are divided into at least one candidate set, and the correlation between multiple candidate test points in the same candidate set is high; for each candidate set, at least one candidate test point is randomly selected from the candidate set as a target test point, and each target test point is used to collect data to obtain test data; The first determining module is further configured to, when the failure reproduction result characterizes the failure reproduction as unsuccessful, obtain test condition requirement information related to the target product, call a large language model, perform semantic understanding on the test condition requirement information, and obtain new test conditions; The second determining module is used to acquire new test data of the target product when the target product located in the reproduction test equipment is running under the new test conditions, and to determine the failure reproduction result of the target product based on the new test data.

6. The apparatus according to claim 5, characterized in that, The historical usage data includes at least the failure phenomena that the target product has experienced, the environmental information of the environment in which the failure phenomena occurred, and the product attribute information of the target product; the first determining module is used to obtain a mapping table for determining test conditions when failure reproduction data related to the historical usage data cannot be found locally, the mapping table includes the mapping relationship between failure phenomena, environmental information, product attribute information and test information of test conditions; Based on the failure phenomenon, environmental information, and product attribute information of the target product, the test information corresponding to the target product is retrieved from the mapping table. The test information includes recommended stress type and recommended stress parameters. If the recommended stress type exists among multiple candidate stress types, the recommended stress type is taken as the target stress type, and the recommended stress parameter is taken as the target stress parameter.

7. The apparatus according to claim 5, characterized in that, The second determining module is used to acquire normal data of the target product and compare the normal data with the test data; if the comparison result indicates that the normal data is inconsistent with the test data, then the data inconsistent with the normal data is extracted from the test data, and the extracted data is used as the failure reproduction data of the target product, and the failure reproduction is determined to be successful; if the comparison result indicates that the normal data is consistent with the test data, then the failure reproduction is determined to be unsuccessful.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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