Method and device for processing outliers in chip test data

Abstract

The present invention provides a method and apparatus for processing outliers in chip test data. The method involves determining a target test item for which outliers need to be processed; obtaining a user-configured outlier threshold, threshold constraint interval, and impact range corresponding to the outlier; and, based on the outlier threshold and threshold constraint interval, responding to a user-selected outlier processing mode and performing the processing corresponding to the processing mode on the outliers within the impact range. This method improves the accuracy of finding outliers in chip test data and flexibly adapts to the outlier analysis and processing requirements of different test items.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor testing technology, and in particular to a method and device for processing outliers in chip test data. Background Art

[0002] Before each semiconductor chip is shipped, it undergoes multiple tests using different test procedures, generating a large amount of test data. This data is typically stored in Standard Test Data Files (STDF). During the chip production process, process defects or other abnormal factors can cause some of the chip's indicators to deviate from the normal range. These anomalies are detected during chip testing and reflected as abnormal values in the test results. These abnormal data values, which generally deviate from the normal range, are called outliers.

[0003] When analyzing semiconductor chip test data, the appearance of outliers can interfere with normal analysis. One or more values that deviate significantly from the normal range can cause the calculated results of some indicators to deviate significantly from the actual results, resulting in inaccurate analysis results. Therefore, when analyzing data, it is necessary to use some algorithms to process the outlier data to eliminate the interference of the outlier data, or to process and analyze the outlier data. However, existing methods for processing and analyzing outlier data cannot accurately find outlier data among a large number of test results, and cannot flexibly adapt corresponding processing methods for outlier data that appears in different test item scenarios. Summary of the Invention

[0004] The embodiments of the present disclosure at least provide a method and device for processing outliers in chip test data, which can improve the accuracy of finding outliers in chip test data and flexibly adapt to the analysis and processing requirements of outliers for different test items.

[0005] The present disclosure provides a method for processing outliers in chip test data, including:

[0006] Identify the target test items that need to handle outliers;

[0007] Obtaining the outlier threshold, threshold constraint interval, and impact range corresponding to the outlier configured by the user for the target test item;

[0008] According to the outlier threshold and the threshold constraint interval, in response to the outlier processing mode selected by the user, the processing corresponding to the processing mode is performed on the outlier within the influence range.

[0009] In an optional implementation, the outlier threshold is obtained based on the following steps:

[0010] Provide a threshold configuration function block including threshold algorithm selection items;

[0011] Calling the threshold configuration function block, in response to a user's selection operation on a target threshold algorithm, providing a filling template corresponding to the target threshold algorithm, wherein the filling template includes parameter filling items corresponding to the target threshold algorithm;

[0012] The algorithm parameter value filled in by the user in the parameter filling item is obtained, and the target threshold algorithm is executed according to the algorithm parameter value to determine the outlier threshold.

[0013] In an optional implementation, the outlier threshold includes an outlier upper limit and an outlier lower limit, and the threshold constraint interval is obtained based on the following steps:

[0014] Providing an interval configuration function block including an interval type selection item, wherein the interval type selection item provides a plurality of preset interval types;

[0015] The interval configuration function block is called to determine a target threshold constraint interval selected by the user in response to a user selecting the preset interval type in the interval type selection item.

[0016] In an optional implementation, the preset interval types include less than the outlier lower limit, greater than the outlier upper limit, between the outlier upper limit and the outlier lower limit, and outside the outlier upper limit and the outlier lower limit.

[0017] In an optional implementation, the influence range corresponding to the outlier is obtained based on the following steps:

[0018] Providing an influence range configuration function block including an influence range selection item, wherein the influence range selection item provides a plurality of preset influence range types;

[0019] The influence range configuration function block is called to determine the target influence range selected by the user in response to the user's selection operation for the preset influence range type in the influence range selection item.

[0020] In an optional implementation manner, the preset impact range type includes impact on the current target test item and associated impact;

[0021] When the user selects the associated impact as the target impact range, an impact target filling item is provided in the impact range configuration function block;

[0022] Obtain the target chip ID filled in by the user in the impact target filling item, wherein the target chip ID is used to identify the chip affected by the outlier association.

[0023] In an optional embodiment, the outlier processing mode includes an outlier screening mode and an outlier deletion mode, and processes the outliers based on the following steps:

[0024] For the outlier screening mode, when the impact range is affecting the current target test item, a conditional query statement is constructed according to the outlier threshold and the threshold constraint interval;

[0025] Executing the conditional query statement to filter outlier chip test data in the target test item;

[0026] When the impact range is the associated impact, constructing a conditional query statement according to the outlier threshold, the threshold constraint interval, and the target chip ID;

[0027] Executing the conditional query statement to filter the outlier chip test data from the target test item and the test items of the chip corresponding to the target chip ID;

[0028] In the outlier deletion mode, after the outlier chip test data is screened out, the outlier chip test data is deleted.

[0029] The present disclosure also provides an outlier processing device for chip test data, comprising:

[0030] A target test item determination module is used to determine the target test items that need to process outliers;

[0031] A screening condition acquisition module is used to obtain the outlier threshold, threshold constraint interval and influence range corresponding to the outlier configured by the user for the target test item;

[0032] The outlier processing module is configured to perform processing corresponding to the processing mode on the outlier within the influence range in response to the outlier processing mode selected by the user according to the outlier threshold and the threshold constraint interval.

[0033] An embodiment of the present disclosure also provides an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the above-mentioned outlier processing method for chip test data, or steps in any possible implementation of the above-mentioned outlier processing method for chip test data is performed.

[0034] An embodiment of the present disclosure also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program executes the above-mentioned outlier processing method for chip test data, or steps in any possible implementation of the above-mentioned outlier processing method for chip test data.

[0035] An embodiment of the present disclosure also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the above-mentioned outlier processing method for chip test data, or the steps in any possible implementation of the above-mentioned outlier processing method for chip test data.

[0036] The disclosed embodiments provide a method and apparatus for processing outliers in chip test data. These methods determine target test items for which outliers need to be processed; obtain the outlier threshold, threshold constraint interval, and impact range corresponding to the outlier configured by the user for the target test item; and, based on the outlier threshold and threshold constraint interval, respond to the user-selected outlier processing mode and perform processing corresponding to the processing mode on the outlier within the impact range. This method can improve the accuracy of finding outliers in chip test data and flexibly adapt to the outlier analysis and processing requirements of different test items.

[0037] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and, together with the specification, are used to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without inventive effort.

[0039] Figure 1 A flowchart of a method for processing outliers in chip test data provided by an embodiment of the present disclosure is shown;

[0040] Figure 2 A flowchart of another method for processing outliers in chip test data provided by an embodiment of the present disclosure is shown;

[0041] Figure 3 A schematic diagram of an outlier processing device for chip test data provided by an embodiment of the present disclosure is shown;

[0042] Figure 4 A schematic diagram of an electronic device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the disclosure for which protection is sought, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present disclosure.

[0044] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0045] The term "and / or" herein simply describes an association relationship, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, and the existence of B alone. In addition, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0046] Research has found that when analyzing semiconductor chip test data, the presence of outliers can interfere with normal analysis. One or more values that deviate significantly from the normal range can cause the calculated results of some indicators to deviate significantly from the actual results, resulting in inaccurate analysis. Therefore, when analyzing data, it is necessary to use algorithms to process outlier data to eliminate the interference of outlier data, or to process and analyze the outlier data specifically. However, existing methods for processing and analyzing outlier data cannot accurately locate outlier data within a large number of test results, and cannot flexibly adapt corresponding processing methods for outlier data that appears in different test scenarios.

[0047] Based on the above research, the present disclosure provides a method and apparatus for processing outliers in chip test data. The method involves determining a target test item for which outliers need to be processed; obtaining the outlier threshold, threshold constraint interval, and impact range corresponding to the outlier configured by the user for the target test item; and, based on the outlier threshold and threshold constraint interval, responding to the user-selected outlier processing mode, performing the processing corresponding to the processing mode on the outlier within the impact range. This method can improve the accuracy of finding outliers in chip test data and flexibly adapt to the outlier analysis and processing requirements of different test items.

[0048] To facilitate understanding of this embodiment, a method for processing outliers in chip test data disclosed in an embodiment of the present disclosure is first introduced in detail. The execution subject of the method for processing outliers in chip test data provided in the embodiment of the present disclosure is generally a computer device with certain computing capabilities. The computer device includes, for example: a terminal device or a server or other processing device. The terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the method for processing outliers in chip test data can be implemented by a processor calling computer-readable instructions stored in a memory.

[0049] See also Figure 1 FIG. 1 is a flowchart of a method for processing outliers in chip test data provided by an embodiment of the present disclosure. The method includes steps S101 to S103, wherein:

[0050] S101. Determine target test items that need to process outliers.

[0051] In a specific implementation, first, the user selects a test item that needs to be processed for outliers from existing test items in the current chip test process as a target test item.

[0052] S102: Obtain an outlier threshold, a threshold constraint interval, and an impact range corresponding to the outlier configured by a user for the target test item.

[0053] In a specific implementation, since outliers are values in chip test data that deviate from the normal range, it is necessary to first determine the threshold of the outliers. In an embodiment of the present application, the outlier threshold can be configured by the user according to the requirements of the test item, or the required outlier threshold calculation algorithm can be selected, and the corresponding outlier threshold can be calculated by configuring the parameter values in the outlier threshold calculation algorithm.

[0054] Here, the outlier threshold includes an outlier upper limit and an outlier lower limit. The outlier upper limit can be understood as the upper limit of the corresponding data normal value, and the outlier lower limit can be understood as the lower limit of the corresponding data normal value.

[0055] As a possible implementation, the outlier threshold configured by the user for the target test item can be obtained by following steps 1 to 3:

[0056] Step 1: Provide a threshold configuration function block including threshold algorithm selection items.

[0057] Step 2: Call the threshold configuration function block, and in response to the user's selection operation for the target threshold algorithm, provide a filling template corresponding to the target threshold algorithm, wherein the filling template includes parameter filling items corresponding to the target threshold algorithm.

[0058] Step 3: Obtain the algorithm parameter value filled in by the user in the parameter filling item, execute the target threshold algorithm according to the algorithm parameter value, and determine the outlier threshold.

[0059] In a specific implementation, a threshold configuration function block is provided for interacting with the user through a human-computer interaction interface. The threshold configuration function block is pre-configured with threshold algorithm selection items for the user to select. The threshold algorithm selection items include a list of multiple preset threshold algorithms displayed to the user.

[0060] Here, the user selects the target threshold algorithm required to calculate the outlier threshold in the threshold algorithm selection item through a selection operation. In response to the user's selection operation, the threshold configuration function block provides the user with a filling template corresponding to the selected target threshold algorithm.

[0061] Among them, the filling template includes the algorithm structure of the corresponding threshold algorithm, and the parameter filling items for implementing the threshold algorithm reserved at the corresponding positions of the algorithm structure. The user fills in the corresponding algorithm parameter values in the parameter filling items, and the threshold configuration function block executes the threshold algorithm to calculate the corresponding outlier threshold.

[0062] Optionally, the threshold configuration function block can construct a corresponding query statement based on the target threshold algorithm selected by the user, query the relevant parameter types required by the target threshold algorithm in the preset database, and then build a filling template based on the parameter type and provide it to the user for filling.

[0063] Exemplary threshold algorithms include: mean ± n × standard deviation; median ± n × standard deviation; Q1 / Q3 ± n × IQR, where Q1 = 25th percentile, Q3 = 75th percentile, and IQR = Q3 - Q1; the upper limit (highLimit) or lower limit (lowLimit) of the test item parsed from the STDF; or the upper limit (highLimit) or lower limit (lowLimit) of the test item set by the user.

[0064] It should be noted that the configuration methods of the outlier upper limit and the outlier lower limit can adopt the methods provided in the above steps 1 to 3. The preset threshold algorithm can be set according to the actual situation based on the requirements of the chip test items, and no specific restrictions are made here.

[0065] Furthermore, in order to limit the scope of data analysis with outliers, eliminate outlier interference, or analyze outlier data effectively, the user needs to configure the constraint area of the outlier threshold. As a possible implementation method, the following steps 1-2 can be used to obtain the threshold constraint interval configured by the user for the target test item:

[0066] Step 1: Provide an interval configuration function block including an interval type selection item, wherein the interval type selection item provides multiple preset interval types.

[0067] Step 2: Call the interval configuration function block, and determine the target threshold constraint interval selected by the user in response to the user's selection operation for the preset interval type in the interval type selection item.

[0068] In a specific implementation, an interval configuration function block is provided for interacting with the user through a human-computer interaction interface. The interval configuration function block is pre-configured with interval type selection items for the user to select, and the interval type selection items include a list of multiple preset interval types displayed to the user.

[0069] Here, the user selects the desired threshold constraint interval in the interval type selection item by selecting the operation. The preset interval types include less than the outlier lower limit, greater than the outlier upper limit, between the outlier upper limit and the outlier lower limit, and outside the outlier upper limit and the outlier lower limit.

[0070] Among them, the less than outlier lower limit interval type is used to filter chip test data with data values within the range less than the outlier lower limit as data with outliers; the greater than outlier upper limit type is used to filter chip test data with data values within the range greater than the outlier upper limit as data with outliers; the between outlier upper limit and outlier lower limit type is used to filter chip test data with data values within the range between the outlier upper limit and the outlier lower limit as data with outliers; the outside outlier upper limit and outlier lower limit type is used to filter chip test data with data values within the range outside the outlier upper limit and the outlier lower limit as data with outliers.

[0071] Furthermore, through the above steps, the range of outliers can be determined. However, the identified outliers at this time are only the range of the test results of the selected target test item. It is also necessary to determine the impact of the outliers on the data of non-selected test items. The user is also required to configure the impact range of the outlier threshold. As a possible implementation method, the impact range configured by the user for the target test item can be obtained by following the steps 1-2 below:

[0072] Step 1: Provide an influence range configuration function block including an influence range selection item, wherein the influence range selection item provides multiple preset influence range types.

[0073] Step 2: Call the influence range configuration function block, and determine the target influence range selected by the user in response to the user's selection operation for the preset influence range type in the influence range selection item.

[0074] In a specific implementation, an influence range configuration function block is provided for interacting with the user through a human-computer interaction interface. The influence range configuration function block is pre-configured with interval type selection items for the user to select, and the interval type selection items include a list of multiple preset interval types displayed to the user.

[0075] Here, the user selects the desired outlier impact range in the impact range selection item through a selection operation, wherein the preset impact range types include impact on the current target test item and associated impact. Impact on the current target test item means that the outlier only affects the chip test data in the selected target test item, and associated impact means that the outlier not only affects the chip test data in the selected target test item, but also affects the chip test data in other chip test items.

[0076] Optionally, the corresponding item associated with the currently selected target test item can be identified and indicated by the chip ID. Specifically, when the user selects the associated impact as the target impact range, an impact target filling item is provided in the impact range configuration function block; the target chip ID filled in by the user in the impact target filling item is obtained, wherein the target chip ID is used to identify the chip associated with the outlier.

[0077] Here, after obtaining the target chip ID filled in by the user in the impact target filling item, the impact range configuration function block can construct a query statement according to the target chip ID and access the preset database to query all chips that meet the conditions.

[0078] In this way, through the above-mentioned method, flexible outlier action range options are provided to the user.

[0079] S103 : Based on the outlier threshold and the threshold constraint interval, and in response to an outlier processing mode selected by a user, perform processing corresponding to the processing mode on the outlier within the influence range.

[0080] In practice, after guiding users to configure the outlier scope, they also need to be guided to select an outlier handling method to determine how outliers affect analysis. Outlier handling modes can include outlier filtering and outlier removal. Outlier removal eliminates outliers during analysis through an algorithm; outlier filtering eliminates outliers through an algorithm.

[0081] On this basis, as a possible implementation, outliers can be handled based on the following steps: Figure 2 FIG. 1 is a flowchart of another method for processing outliers in chip test data provided by an embodiment of the present disclosure. The method includes steps S1031 to S1035, wherein:

[0082] S1031. For the outlier screening mode, when the impact range is affecting the current target test item, construct a conditional query statement according to the outlier threshold and the threshold constraint interval.

[0083] S1032: Execute the conditional query statement to filter outlier chip test data in the target test item.

[0084] S1033: When the impact range is the associated impact, construct a conditional query statement according to the outlier threshold, the threshold constraint interval, and the target chip ID.

[0085] S1034: Execute the conditional query statement to filter the outlier chip test data from the target test item and the test items of the chip corresponding to the target chip ID.

[0086] S1035 . For the outlier deletion mode, after the outlier chip test data is screened out, the outlier chip test data is deleted.

[0087] The disclosed embodiments provide a method for processing outliers in chip test data. The method involves determining a target test item for which outliers need to be processed; obtaining a user-configured outlier threshold, threshold constraint interval, and impact range corresponding to the outlier; and, based on the outlier threshold and threshold constraint interval, responding to a user-selected outlier processing mode and performing the processing corresponding to the processing mode on the outlier within the impact range. This method can improve the accuracy of finding outliers in chip test data and flexibly adapt to the outlier analysis and processing requirements of different test items.

[0088] Those skilled in the art will understand that in the above-mentioned method of the specific implementation method, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0089] Based on the same inventive concept, the embodiment of the present disclosure also provides an outlier processing device for chip test data corresponding to the outlier processing method for chip test data. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the outlier processing method for chip test data in the above-mentioned embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0090] See also Figure 3 , Figure 3 Schematic diagram of an outlier processing device for chip test data provided by an embodiment of the present disclosure. Figure 3 As shown in FIG, the outlier processing device 300 for chip test data provided by the embodiment of the present disclosure includes:

[0091] The target test item determination module 310 is configured to determine target test items for which outlier processing is required.

[0092] The screening condition acquisition module 320 is used to obtain the outlier threshold, the threshold constraint interval, and the influence range corresponding to the outlier configured by the user for the target test item.

[0093] The outlier processing module 330 is configured to perform processing corresponding to the processing mode selected by the user on the outlier within the influence range according to the outlier threshold and the threshold constraint interval.

[0094] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference can be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0095] An embodiment of the present disclosure provides an outlier processing device for chip test data. The device determines a target test item for which outliers need to be processed; obtains a user-configured outlier threshold, threshold constraint interval, and impact range corresponding to the outlier; and, based on the outlier threshold and threshold constraint interval, responds to a user-selected outlier processing mode and performs processing corresponding to the processing mode on the outlier within the impact range. This device can improve the accuracy of finding outliers in chip test data and flexibly adapt to the outlier analysis and processing requirements of different test items.

[0096] Corresponding to Figure 1 and Figure 2 The embodiment of the present disclosure further provides an electronic device 400, such as Figure 4 FIG. 4 is a schematic diagram of the structure of an electronic device 400 provided in an embodiment of the present disclosure, including:

[0097] Processor 41, memory 42, and bus 43; memory 42 is used to store execution instructions, including memory 421 and external memory 422; the memory 421 here is also called internal memory, which is used to temporarily store the operation data in the processor 41 and the data exchanged with the external memory 422 such as the hard disk. The processor 41 exchanges data with the external memory 422 through the memory 421. When the electronic device 400 is running, the processor 41 and the memory 42 communicate through the bus 43, so that the processor 41 executes Figure 1 and Figure 2 Steps of the outlier processing method for chip test data.

[0098] The present disclosure also provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program executes the steps of the method for processing outliers in chip test data described in the above method embodiment. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0099] An embodiment of the present disclosure also provides a computer program product, which includes computer instructions. When the computer instructions are executed by a processor, the steps of the outlier processing method for chip test data described in the above method embodiment can be executed. For details, please refer to the above method embodiment, which will not be repeated here.

[0100] The computer program product may be implemented in hardware, software, or a combination thereof. In one embodiment, the computer program product is implemented as a computer storage medium. In another embodiment, the computer program product is implemented as a software product, such as a software development kit (SDK).

[0101] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0102] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0103] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0104] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0105] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The scope of protection of the present disclosure is not limited thereto. Although the present disclosure has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed in the present disclosure, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure shall be subject to the scope of protection of the claims.

Claims

1. A method for processing outliers in chip test data, characterized in that: include: Identify the target test items that need to handle outliers; Obtaining the outlier threshold, threshold constraint interval, and impact range corresponding to the outlier configured by the user for the target test item; According to the outlier threshold and the threshold constraint interval, in response to the outlier processing mode selected by the user, performing processing corresponding to the processing mode on the outlier within the influence range; Obtain the influence range corresponding to the outlier based on the following steps: Providing an influence range configuration function block including an influence range selection item, wherein the influence range selection item provides a plurality of preset influence range types; Calling the influence range configuration function block, in response to the user selecting the preset influence range type in the influence range selection item, determining the target influence range selected by the user; The preset impact scope types include the impact on the currently stated target test item and associated impacts; When the user selects the associated impact as the target impact range, an impact target filling item is provided in the impact range configuration function block; Obtaining a target chip ID filled in by the user in the impact target filling item, wherein the target chip ID is used to identify the chip affected by the outlier association; The outlier processing mode includes an outlier screening mode and an outlier deletion mode, and processes the outliers based on the following steps: For the outlier screening mode, when the impact range is affecting the current target test item, a conditional query statement is constructed according to the outlier threshold and the threshold constraint interval; Executing the conditional query statement to filter outlier chip test data in the target test item; When the impact range is the associated impact, constructing a conditional query statement according to the outlier threshold, the threshold constraint interval, and the target chip ID; Executing the conditional query statement to filter the outlier chip test data from the target test item and the test items of the chip corresponding to the target chip ID; In the outlier deletion mode, after the outlier chip test data is screened out, the outlier chip test data is deleted.

2. The method according to claim 1, characterized in that The outlier threshold is obtained based on the following steps: Provide a threshold configuration function block including threshold algorithm selection items; Calling the threshold configuration function block, in response to a user's selection operation on a target threshold algorithm, providing a filling template corresponding to the target threshold algorithm, wherein the filling template includes parameter filling items corresponding to the target threshold algorithm; The algorithm parameter value filled in by the user in the parameter filling item is obtained, and the target threshold algorithm is executed according to the algorithm parameter value to determine the outlier threshold.

3. The method according to claim 1, characterized in that The outlier threshold includes an outlier upper limit and an outlier lower limit, and the threshold constraint interval is obtained based on the following steps: Providing an interval configuration function block including an interval type selection item, wherein the interval type selection item provides a plurality of preset interval types; The interval configuration function block is called to determine a target threshold constraint interval selected by the user in response to a user selecting the preset interval type in the interval type selection item.

4. The method according to claim 3, wherein: The preset interval types include less than the outlier lower limit value, greater than the outlier upper limit value, between the outlier upper limit value and the outlier lower limit value, and outside the outlier upper limit value and the outlier lower limit value.

5. A device for processing outliers in chip test data, characterized in that: include: A target test item determination module is used to determine the target test items that need to process outliers; A screening condition acquisition module is used to obtain the outlier threshold, threshold constraint interval and influence range corresponding to the outlier configured by the user for the target test item; an outlier processing module, configured to perform processing corresponding to the processing mode selected by a user on the outlier within the influence range according to the outlier threshold and the threshold constraint interval; The screening condition acquisition module is specifically configured to provide an influence range configuration function block including an influence range selection item, wherein the influence range selection item provides a plurality of preset influence range types; Calling the influence range configuration function block, in response to the user selecting the preset influence range type in the influence range selection item, determining the target influence range selected by the user; The preset impact scope types include the impact on the currently stated target test item and associated impacts; When the user selects the associated impact as the target impact range, an impact target filling item is provided in the impact range configuration function block; Obtaining a target chip ID filled in by the user in the impact target filling item, wherein the target chip ID is used to identify the chip affected by the outlier association; The outlier processing mode includes an outlier screening mode and an outlier deletion mode. The device is further configured to, for the outlier screening mode, construct a conditional query statement based on the outlier threshold and the threshold constraint interval when the impact range is affecting the current target test item; Executing the conditional query statement to filter outlier chip test data in the target test item; When the impact range is the associated impact, constructing a conditional query statement according to the outlier threshold, the threshold constraint interval, and the target chip ID; Executing the conditional query statement to filter the outlier chip test data from the target test item and the test items of the chip corresponding to the target chip ID; In the outlier deletion mode, after the outlier chip test data is screened out, the outlier chip test data is deleted.

6. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus. When the machine-readable instructions are executed by the processor, the steps of the outlier processing method for chip test data according to any one of claims 1 to 4 are performed.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the outlier processing method for chip test data according to any one of claims 1 to 4.

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