A power chip test data processing system and method based on big data

Abstract

The present invention relates to the technical field of chip performance test data management, and specifically provides a power chip test data processing system and method based on big data. The present invention analyzes all historical performance test records of a target power chip, sorts out the corresponding test feedback data on each test item during the performance test, and the characteristic law presented with the change of the test operation environment information. And based on the above characteristic law, the detection attention of each test item is evaluated, a test item sequence is generated, and by guiding the management personnel to carry out performance tests according to the test item sequence, when a performance problem occurs in the target power chip, a conclusion of performance anomaly can be obtained relatively quickly, the detection efficiency of the management personnel when carrying out performance detection on the target power chip is improved, and more time can be reserved for arranging safety protection measures for the target power chip with a performance degradation phenomenon.

Description

Technical Field

[0001] The present invention relates to the technical field of chip performance test data management, and specifically to a power chip test data processing system and method based on big data. Background Art

[0002] A power chip is an integrated circuit chip used for power supply, which plays a role in stabilizing power supply and protection in electronic devices. The power chip is an important part of the integrated circuit, mainly used to provide stable power for other chips and circuits. However, due to various reasons, the power chip may malfunction, resulting in the device being unable to work properly;

[0003] The components in the power chip will gradually age with the increase of the usage time, resulting in the decline of its performance and eventually may lead to failures. Performance testing is an important step in the effective management of power chips; the performance indicators of power chips include conversion efficiency, switching frequency, output voltage accuracy, temperature, etc. Therefore, in the process of performing performance detection on power chips, it is necessary to follow a certain detection process to comprehensively cover and detect the performance indicators of power chips. Summary of the Invention

[0004] The purpose of the present invention is to provide a power chip test data processing system and method based on big data to solve the problems proposed in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: A power chip test data processing method based on big data, the method includes:

[0006] Step S1: Extract all historical performance test records carried out on the target power chip, and collect all historical performance test data of the target power chip; wherein, in each historical performance test record, the test items executed on the target power chip are the same; extract the characteristic information of the test running environment when each historical performance test record is executed.

[0007] Step S2: Collect the test feedback data and the corresponding test feedback conclusions obtained for each test item in each historical performance test record, and the test feedback conclusions include normal and abnormal.

[0008] Step S3: Sort out the characteristic law situations presented by the corresponding test feedback data with the change of the test running environment information in the historical performance test records with different test feedback conclusions for each test item.

[0009] Step S4: Evaluate the detection attention degree of each test item according to the characteristic law situations presented by the corresponding test feedback data with the change of the test running environment information for each test item.

[0010] Step S5: Send the detection attention levels of each test item to the management terminal to assist the management personnel in arranging the priorities of each test item during the real-time performance test of the target power chip.

[0011] Preferably, a sensor device is arranged on the target power chip. Whenever a performance test is carried out on the target power chip, the sensor device is triggered to collect the operating environment information of the target power chip once. Among them, one performance test record corresponds to an environment information set; the feature extraction is respectively carried out on the environment information sets collected when each historical performance test record is executed to obtain the characteristic environment information sets corresponding to each historical performance test record.

[0012] In this application, the operating environment information collected by the sensor device is the environment information that can affect the performance of the target power chip, including the surface temperature of the target power chip, the surface humidity of the target power chip, the surface vibration of the target power chip, the surface static voltage of the target power chip, and so on.

[0013] Preferably, step S3 includes:

[0014] Step S3-1: For each test item, collect all the historical performance test records corresponding to the normal test feedback conclusions to obtain the first record set corresponding to each test item, and collect all the historical performance test records corresponding to the abnormal test feedback conclusions to obtain the second record set corresponding to each test item; traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item respectively.

[0015] Step S3-2: If the first record set of a certain test item A is R1 and the second record set is R2, for any historical performance test record in the first record set R1 respectively, capture the historical performance test record in the second record set R2 whose test feedback data corresponding to a certain test item A is the most similar to the test feedback data corresponding to a certain test item A in any historical performance test record. Among them, the most similar means the smallest deviation; take a historical performance test record and any historical performance test record as a characteristic relative record group; among them, if there are n historical performance test records in the first record set R1 of a certain test item A, then n characteristic relative record groups are extracted.

[0016] Step S3-3: Extract the characteristic environment information set F1 corresponding to the historical performance test record belonging to the first record set R1 and the characteristic environment information set F2 corresponding to the historical performance test record belonging to the second record set R2 in each characteristic relative record group, obtain the similarity η between the characteristic environment information set F2 and the characteristic environment information set F1, where 1≥η≥0; calculate the test operating environment information change value α = 1 - η in each characteristic relative record group.

[0017] Preferably, step S4 includes:

[0018] Step S4-1: Traverse the change values of the test running environment information corresponding to each feature obtained for each test item with respect to the record group; for each test item, capture the minimum test running environment information change value U that appears in all the corresponding feature record groups, and set the feature record group that extracts the minimum test running environment information change value U as the target record group for each test item;

[0019] The smaller the change value of the test running environment information, the greater the similarity between the feature environment information set extracted from the performance test records with the corresponding test feedback conclusion being normal and the feature environment information set extracted from the performance test records with the corresponding test feedback conclusion being abnormal;

[0020] Step S4-2: In the target record group of each test item respectively, extract the test feedback data y1 corresponding to each test item in the historical performance test records belonging to the first record set of each test item, extract the test feedback data y2 corresponding to each test item in the historical performance test records belonging to the second record set of each test item, and obtain the similarity Q between the test feedback data y1 and the test feedback data y2; evaluate the detection attention level δ corresponding to each test item as δ = 1 / (U + Q);

[0021] If the minimum test running environment information change value U that appears in all the corresponding feature record groups of a certain test item is smaller, it indicates that when similar test feedback data leads to different test feedback conclusions respectively, at the level of external environment information, the required change amount is smaller, and the smaller the corresponding change amount, the more necessary it is to monitor the test feedback conclusion fed back on this test item in real time during the detection process; if in the target record group of a certain test item, the similarity Q between the corresponding test feedback data y1 and the test feedback data y2 is greater, it indicates that when different test feedback conclusions are caused under similar external environment conditions, at the level of test feedback data, the required change amount is smaller, and the smaller the corresponding change amount, the more necessary it is to monitor the test feedback conclusion fed back on this test item in real time during the detection process.

[0022] Preferably, step S5 includes:

[0023] Step S5-1: Sort all the test items in descending order according to the corresponding detection attention levels to generate a test item sequence;

[0024] Step S5-2: Send the test item sequence to the manager's terminal, prompt the manager to perform a performance test on the target power chip according to the test item sequence, and at the same time, receive the corresponding test feedback data according to the test item sequence to obtain the test feedback conclusion for each test item;

[0025] Sort all test items in descending order according to their corresponding detection attention levels to generate a test item sequence. The above content is beneficial for quickly observing anomalies from the data observation level when the target power chip has performance problems. That is, for the test items that are more sensitive when the target power chip has performance problems, priority is given to testing. In this way, when the test items ranked in the front feedback anomalies, safety protection preparations can be made for the target power chip in a timely manner, improving the detection efficiency of the manager when performing a performance test on the target power chip, and leaving more time for the manager to arrange safety protection measures when the performance of the target power chip decreases;

[0026] For example, the test items ranked relatively high in the test item sequence are often the test items that can quickly present data anomalies when the performance of the target power chip decreases. Therefore, once a conclusion on whether the performance has decreased is obtained based on the test data situation feedback by the test items ranked relatively high, a response to the current situation can be made quickly; the test items ranked relatively high in the test item sequence are often the test items that can lead to completely opposite test feedback conclusions based on relatively small data changes during the performance test process of the target power chip.

[0027] To better implement the above method, a power chip test data processing system is also proposed. The system includes: a performance test record information extraction module, a performance test record information sorting module, a detection attention level evaluation and management module, and a feedback management module;

[0028] The performance test record information extraction module is used to extract all historical performance test records of the target power chip and collect all historical performance test data of the target power chip; among them, in each historical performance test record, the test items executed on the target power chip are the same; extract the characteristic information of the test operation environment when each historical performance test record is executed;

[0029] The performance test record information sorting module is used to collect the test feedback data and the corresponding test feedback conclusions obtained for each test item in each historical performance test record. The test feedback conclusions include normal and abnormal; sort out the characteristic law situation presented by the corresponding test feedback data with the change of the test operation environment information in the historical performance test records with different test feedback conclusions for each test item;

[0030] The detection attention evaluation management module is used to evaluate the detection attention of each test item according to the characteristic law of the corresponding test feedback data on each test item presented with the change of the test running environment information;

[0031] The feedback management module is used to send the detection attention of each test item to the management terminal to assist the management personnel in arranging the priorities of each test item during the real-time performance test of the target power chip.

[0032] Preferably, the performance test record information sorting module includes a data acquisition management unit and a test item information sorting unit;

[0033] The data acquisition management unit is used to collect the test feedback data and the corresponding test feedback conclusions obtained for each test item in each historical performance test record. The test feedback conclusions include normal and abnormal; for each test item, collect all the historical performance test records with the corresponding test feedback conclusion being normal to obtain the first record set corresponding to each test item, and collect all the historical performance test records with the corresponding test feedback conclusion being abnormal to obtain the second record set corresponding to each test item;

[0034] The test item information sorting unit is used to traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item respectively; sort out the characteristic law of the corresponding test feedback data presented with the change of the test running environment information in the historical performance test records of each test item with different test feedback conclusions.

[0035] Preferably, the feedback management module includes an information reception management unit and a prompt management unit;

[0036] The information reception management unit is used to receive the data in the detection attention evaluation management module, sort all the test items in descending order according to the corresponding detection attention, and generate a test item sequence;

[0037] The prompt management unit is used to send the test item sequence to the management personnel terminal, prompt the management personnel to perform a performance test on the target power chip according to the test item sequence, and at the same time receive the corresponding test feedback data according to the test item sequence to obtain the test feedback conclusions corresponding to each test item.

[0038] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: By analyzing the data of all historical performance test records of the target power supply chip, the present invention sorts out the characteristic laws of the corresponding test feedback data of each test item with the change of the test operation environment information during the performance test. And based on the above characteristic laws, the detection attention of each test item is evaluated, and all test items are sorted from large to small according to the corresponding detection attention to generate a test item sequence. By guiding the management personnel to carry out performance tests according to the test item sequence, when the target power supply chip has performance problems, a conclusion of performance abnormality can be obtained quickly, the detection efficiency of the management personnel when carrying out performance detection on the target power supply chip can be improved, and more time can be reserved for arranging safety protection measures for the target power supply chip with performance degradation. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0040] Figure 1 is a schematic flowchart of a method for processing test data of a power supply chip based on big data according to the present invention;

[0041] Figure 2 is a schematic structural diagram of a system for processing test data of a power supply chip based on big data according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] Please refer to Figure 1 - Figure 2 , the present invention provides a technical solution: A method for processing test data of a power supply chip based on big data, the method includes:

[0044] Step S1: Extract all historical performance test records of the target power supply chip, and collect all historical performance test data of the target power supply chip; wherein, in each historical performance test record, the test items executed on the target power supply chip are the same; extract the characteristic information of the test operation environment when each historical performance test record is executed.

[0045] Among them, a sensor device is arranged for the target power chip. Whenever a performance test is carried out on the target power chip, the sensor device is triggered to collect the operation environment information of the target power chip once. Among them, one performance test record corresponds to one set of environment information; for the sets of environment information collected when each historical performance test record is executed, feature extraction is respectively carried out to obtain the characteristic environment information sets corresponding to each historical performance test record;

[0046] Step S2: Collect the test feedback data and the corresponding test feedback conclusions obtained for each test item in each historical performance test record. The test feedback conclusions include normal and abnormal;

[0047] Step S3: Sort out the characteristic law situations presented by the corresponding test feedback data with the change of the test operation environment information in the historical performance test records with different test feedback conclusions for each test item;

[0048] Among them, Step S3 includes:

[0049] Step S3-1: For each test item, collect all the historical performance test records corresponding to the test feedback conclusion of normal to obtain the first record set corresponding to each test item, and collect all the historical performance test records corresponding to the test feedback conclusion of abnormal to obtain the second record set corresponding to each test item; respectively traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item;

[0050] Step S3-2: If the first record set of a certain test item A is R1 and the second record set is R2, for any historical performance test record in the first record set R1 respectively, in the second record set R2, capture the historical performance test record whose test feedback data corresponding to a certain test item A is most similar to the test feedback data corresponding to a certain test item A in any historical performance test record, and take the historical performance test record and any historical performance test record as a characteristic relative record group; among them, if there are n historical performance test records in the first record set R1 of a certain test item A, then n characteristic relative record groups are extracted;

[0051] For example, there are a total of 6 historical performance test records in the first record set R1 of a certain test item A, and there are a total of 9 historical performance test records in the second record set R2 of a certain test item A. That is to say, it is necessary to find the historical performance test records that meet the most similar conditions in terms of test feedback data for the 6 historical performance test records in the first record set R1 in the 9 historical performance test records in the second record set R2 in turn, and form the corresponding characteristic relative record groups; therefore, in summary, based on the first record set R1 of a certain test item A, 6 characteristic relative record groups can be extracted;

[0052] Step S3-3: Extract the feature environment information set F1 corresponding to the historical performance test records belonging to the first record set R1 and the feature environment information set F2 corresponding to the historical performance test records belonging to the second record set R2 in each feature relative record group, and obtain the similarity η between the feature environment information set F2 and the feature environment information set F1, where 1≥η≥0; calculate the test run environment information change value α = 1 - η in each feature relative record group;

[0053] Step S4: Evaluate the detection attention of each test item according to the characteristic law presented by the corresponding test feedback data on each test item with the change of the test run environment information;

[0054] Among them, Step S4 includes:

[0055] Step S4-1: Traverse the test run environment information change values corresponding to each feature relative record group extracted for each test item; for each test item, capture the minimum test run environment information change value U that appears in all corresponding feature relative record groups, and set the feature relative record group where the minimum test run environment information change value U is extracted as the target record group for each test item;

[0056] Step S4-2: Respectively in the target record group of each test item, extract the test feedback data y1 corresponding to each test item in the historical performance test records belonging to the first record set of each test item, and extract the test feedback data y2 corresponding to each test item in the historical performance test records belonging to the second record set of each test item, and obtain the similarity Q between the test feedback data y1 and the test feedback data y2; evaluate the detection attention δ = 1 / (U + Q) corresponding to each test item.

[0057] Step S5: Send the detection attention of each test item to the management terminal to assist the management personnel in arranging the priorities of each test item during the real-time performance test of the target power chip;

[0058] Among them, Step S5 includes:

[0059] Step S5-1: Sort all test items in descending order according to the corresponding detection attention to generate a test item sequence;

[0060] Step S5-2: Send the test item sequence to the management personnel terminal, prompt the management personnel to perform a performance test on the target power chip according to the test item sequence, and at the same time receive the corresponding test feedback data according to the test item sequence to obtain the test feedback conclusion corresponding to each test item.

[0061] To better implement the above method, a power chip test data processing system is also proposed. The system includes: a performance test record information extraction module, a performance test record information sorting module, a detection attention evaluation management module, and a feedback management module;

[0062] The performance test record information extraction module is used to extract all historical performance test records of the target power chip and collect all historical performance test data of the target power chip. Among them, in each historical performance test record, the test items executed on the target power chip are the same; feature information extraction is performed on the test running environment when each historical performance test record is executed;

[0063] The performance test record information sorting module is used to collect the test feedback data and corresponding test feedback conclusions obtained for each test item in each historical performance test record. The test feedback conclusions include normal and abnormal; sort out the characteristic law of the corresponding test feedback data with the change of the test running environment information in the historical performance test records with different test feedback conclusions for each test item;

[0064] Among them, the performance test record information sorting module includes a data collection management unit and a test item information sorting unit;

[0065] The data collection management unit is used to collect the test feedback data and corresponding test feedback conclusions obtained for each test item in each historical performance test record. The test feedback conclusions include normal and abnormal; for each test item, collect all historical performance test records with the corresponding test feedback conclusion being normal to obtain the first record set corresponding to each test item, and collect all historical performance test records with the corresponding test feedback conclusion being abnormal to obtain the second record set corresponding to each test item;

[0066] The test item information sorting unit is used to traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item respectively; sort out the characteristic law of the corresponding test feedback data with the change of the test running environment information in the historical performance test records with different test feedback conclusions for each test item;

[0067] The detection attention evaluation management module is used to evaluate the detection attention of each test item according to the characteristic law of the corresponding test feedback data with the change of the test running environment information for each test item;

[0068] The feedback management module is used to send the detection attention of each test item to the management terminal to assist the management personnel in arranging the priorities of each test item during the real-time performance test of the target power chip;

[0069] Among them, the feedback management module includes an information reception management unit and a prompt management unit;

[0070] The information reception management unit is used to receive the data in the detection attention degree evaluation management module, sort all the test items in descending order according to the corresponding detection attention degree, and generate a test item sequence;

[0071] The prompt management unit is used to send the test item sequence to the manager's terminal, prompt the manager to perform performance tests on the target power chip according to the test item sequence, and at the same time receive the corresponding test feedback data according to the test item sequence to obtain the test feedback conclusions corresponding to each test item.

[0072] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0073] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A power chip test data processing method based on big data, characterized in that: The method comprises: Step S1: extracting all historical performance test records conducted on the target power chip and collecting all historical performance test data of the target power chip; wherein, in each historical performance test record, the test items executed on the target power chip are the same; extracting characteristic information of the test running environment when executing each historical performance test record; Step S2: Collecting test feedback data and corresponding test feedback conclusions obtained for each test item in each historical performance test record, wherein the test feedback conclusions include normal and abnormal; Step S3: sorting out the characteristic regularities of the corresponding test feedback data in the historical performance test records of different test feedback conclusions for each test item as the test running environment information changes; Step S4: evaluating the detection attention of each test item according to the characteristic regularity presented by the corresponding test feedback data on each test item as the test running environment information changes; Step S5: Send the detection attention of each test item to the management terminal to assist the management personnel in arranging the priority of each test item during the process of performing real-time performance testing on the target power chip; The step S4 comprises: Step S4-1: Traverse the test running environment information change value corresponding to each feature relative record group extracted from each test item; for each test item, capture the minimum test running environment information change value U appearing in all corresponding feature relative record groups, and set the feature relative record group that extracts the minimum test running environment information change value U as the target record group for each test item; Step S4-2: respectively in the target record group of each test item, extract the test feedback data y1 corresponding to each test item in the historical performance test records of the first record set belonging to each test item, extract the test feedback data y2 corresponding to each test item in the historical performance test records of the second record set belonging to each test item, and obtain the similarity Q between the test feedback data y1 and the test feedback data y2; evaluate the detection attention δ=1 / (U+Q) corresponding to each test item; The step S5 comprises: Step S5-1: sort all test items from large to small according to their corresponding detection concerns to generate a test item sequence; Step S5-2: Send the test item sequence to the management terminal, prompting the management to perform performance test on the target power chip according to the test item sequence, and receive corresponding test feedback data according to the test item sequence to obtain test feedback conclusions corresponding to each test item.

2. A power chip test data processing method based on big data according to claim 1, characterized in that: A sensor device is arranged on the target power chip. Whenever a performance test is carried out on the target power chip, the sensor device is triggered to collect operating environment information of the target power chip, wherein one performance test record corresponds to an environment information set. Feature extraction is performed on the environment information sets collected when executing each historical performance test record to obtain a feature environment information set corresponding to each historical performance test record.

3. The method for processing power chip test data based on big data according to claim 1, characterized in that: The step S3 comprises: Step S3-1: for each test item, collect all historical performance test records whose corresponding test feedback conclusions are normal to obtain a first record set corresponding to each test item, collect all historical performance test records whose corresponding test feedback conclusions are abnormal to obtain a second record set corresponding to each test item; traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item respectively; Step S3-2: If the first record set of a certain test item A is R1 and the second record set is R2, for any historical performance test record in the first record set R1, capture a certain historical performance test record in the second record set R2 whose test feedback data corresponding to a certain test item A is most similar to the test feedback data corresponding to a certain test item A in any of the historical performance test records, and use the certain historical performance test record and the any of the historical performance test records as a feature relative record group; wherein, if there are n historical performance test records in the first record set R1 of a certain test item A, then n feature relative record groups are extracted; Step S3-3: Extract the feature environment information set F1 corresponding to the historical performance test records belonging to the first record set R1 and the feature environment information set F2 corresponding to the historical performance test records belonging to the second record set R2 in each feature relative record group, and obtain the similarity η between the feature environment information set F2 and the feature environment information set F1, where 1≥η≥0; calculate the test running environment information change value α=1-η in each feature relative record group.

4. A power chip test data processing system for executing a power chip test data processing method based on big data as described in any one of claims 1 to 3, characterized in that: The system includes: a performance test record information extraction module, a performance test record information combing module, a detection attention evaluation management module, and a feedback management module; The performance test record information extraction module is used to extract all historical performance test records conducted on the target power chip and collect all historical performance test data of the target power chip; wherein, in each historical performance test record, the test items executed on the target power chip are the same; feature information is extracted from the test running environment when executing each historical performance test record; The performance test record information combing module is used to collect the test feedback data and corresponding test feedback conclusions obtained for each test item in each historical performance test record, wherein the test feedback conclusions include normal and abnormal; combing the characteristic regularity presented by the corresponding test feedback data in the historical performance test records with different test feedback conclusions on each test item as the test running environment information changes; The detection attention evaluation management module is used to evaluate the detection attention of each test item according to the characteristic regularity presented by the corresponding test feedback data on each test item as the test running environment information changes; The feedback management module is used to send the detection attention of each test item to the management terminal, so as to assist the management personnel in arranging the priority of each test item during the process of performing real-time performance testing on the target power chip; The performance test record information combing module includes a data acquisition management unit and a test item information combing unit; The data collection management unit is used to collect the test feedback data and the corresponding test feedback conclusions obtained for each test item in each historical performance test record, wherein the test feedback conclusions include normal and abnormal; for each test item, all historical performance test records with normal corresponding test feedback conclusions are collected to obtain a first record set corresponding to each test item, and all historical performance test records with abnormal corresponding test feedback conclusions are collected to obtain a second record set corresponding to each test item; The test item information combing unit is used to traverse the test feedback data corresponding to each test item in each historical performance test record in the first record set and the second record set of each test item respectively; combing the characteristic regularity presented by the corresponding test feedback data as the test running environment information changes in the historical performance test records of different test feedback conclusions on each test item; The feedback management module includes an information receiving management unit and a prompt management unit; The information receiving management unit is used to receive data in the detection attention evaluation management module, sort all test items from large to small according to the corresponding detection attention, and generate a test item sequence; The prompt management unit is used to send the test item sequence to the management terminal, prompting the management to perform performance testing on the target power chip according to the test item sequence, and at the same time receive corresponding test feedback data according to the test item sequence to obtain test feedback conclusions corresponding to each test item.

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