Test pattern generation method and device, computer equipment and storage medium

Abstract

The invention relates to a test pattern generation method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps that a parameter limiting area of a test pattern is generated according to a parameter design rule of the test pattern, the test pattern has a first parameter, a second parameter and a third parameter, and the remaining parameter can be determined according to any two of the first parameter, the second parameter and the third parameter, the parameter design rule of the test pattern comprises design rules of a first parameter, a second parameter and a third parameter, and the parameter limitation area is an area under a coordinate system with the first parameter and the second parameter as coordinate axes; determining a preset number of target points in the parameter limiting area; and generating a plurality of test patterns according to the coordinates of the plurality of target points. According to the method, the parameters meeting the parameter design rule can be quickly and effectively selected, and the test pattern can be quickly produced.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and in particular to a test pattern generation method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] With the development of semiconductor technology, the design of test patterns to establish semiconductor process models has been widely used in large-scale manufacturing.

[0003] Traditional techniques for generating test patterns typically involve manually designing and selecting various parameter values. However, the rules for designing test pattern parameters are often quite complex. Therefore, manually designing specific parameters can lead to inefficiencies in parameter selection and a high risk of violating these design rules. Summary of the Invention

[0004] Therefore, it is necessary to provide a test pattern generation method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can quickly and efficiently generate test patterns, addressing the aforementioned technical problems.

[0005] A test graph generation method, comprising:

[0006] According to the parameter design rules of the test pattern, a parameter restriction region of the test pattern is generated. The test pattern has a first parameter, a second parameter, and a third parameter. The remaining parameter can be determined based on any two of the first parameter, the second parameter, and the third parameter. The parameter design rules of the test pattern include the design rules of the first parameter, the second parameter, and the third parameter. The parameter restriction region is the region in a coordinate system with the first parameter and the second parameter as coordinate axes.

[0007] A preset number of target points are determined within the parameter constraint area;

[0008] Multiple test graphics are generated based on the coordinates of the multiple target points.

[0009] In one embodiment, while generating the parameter constraint region of the test pattern according to the parameter design rules of the test pattern, a parameter range is also generated. The parameter range includes a first range of a first parameter and a second range of a second parameter.

[0010] Determining a preset number of target points within the parameter constraint area includes:

[0011] Based on the preset quantity, determine the first number of values ​​for the first parameter and the second number of values ​​for the second parameter, where the first number of values ​​is m and the second number of values ​​is n;

[0012] Within the first range, m values ​​are taken for the first parameter, and for each value of the first parameter, n values ​​of the second parameter within the second range are taken to form m×n original points;

[0013] Remove the original points located outside the parameter restriction area, and the remaining original points form candidate points;

[0014] From the candidate points, select the preset number of target points.

[0015] In one embodiment, selecting the preset number of target points from the candidate points includes:

[0016] Under each value of the first parameter, candidate points are selected within the corresponding selection quantity range, so as to select the preset number of quasi-target points under m values ​​of the first parameter. The selection quantity range is the range of the number of candidate points selected. Under each value of the first parameter, all selectable values ​​within the selection quantity range are traversed to select candidate points, so as to select the preset number of quasi-target points multiple times under m values ​​of the first parameter.

[0017] Multiple distributions of the second parameter values ​​are formed by selecting the preset number of quasi-target points under the m values ​​of the first parameter multiple times.

[0018] The multiple value distributions are fitted with a normal distribution function, and the value distribution with the highest shape similarity is selected as the target value distribution.

[0019] The target point is formed by taking the quasi-target points corresponding to the target value distribution.

[0020] In one embodiment, when taking m values ​​for the first parameter within the first range, a non-linear value selection method is adopted; and / or, when taking n values ​​for the second parameter within the second range for each value of the first parameter, a non-linear value selection method is adopted.

[0021] In one embodiment, the test pattern includes a plurality of main patterns arranged in an array, the first parameter includes the width W of the main pattern, the second parameter includes the density D of the main pattern, and the third parameter includes the spacing S of the main patterns, wherein D=W / (W+S).

[0022] In one embodiment, the parameter design rules include the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, and the minimum value of the third parameter within a plurality of preset ranges, wherein the preset ranges are the ranges of values ​​for the first parameter.

[0023] The step of generating the parameter constraint region of the test pattern according to the parameter design rules of the test pattern includes:

[0024] The maximum and minimum values ​​of each preset range are calculated with the minimum value of the third parameter corresponding to the preset range to obtain the value of the second parameter under the maximum and minimum values ​​of each preset range.

[0025] Based on the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, the maximum and minimum values ​​of each preset range, and the values ​​of the second parameter corresponding to the maximum and minimum values ​​of each preset range, multiple positioning points are determined on the coordinate plane determined by the first parameter and the second parameter.

[0026] The multiple positioning points are connected to form the parameter restriction area.

[0027] In one embodiment, a test pattern is generated in a target pattern array, wherein the number of array positions in the target pattern array is 'a', and the preset number is a-1.

[0028] The step of generating multiple test images based on the coordinates of multiple target points includes:

[0029] The values ​​of all the second parameters and all the first parameters at the a-1 target points are divided into high value ranges, medium value ranges, and low value ranges according to their magnitude;

[0030] The target points whose values ​​of the first parameter and the second parameter are both within the range of the middle value are arranged in the outermost array position of the target graphic array;

[0031] The remaining target points and the origin of the coordinate system are arranged in the inner circle of the target graphic array, wherein the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range.

[0032] Based on the arranged target points, the test pattern is generated at the corresponding array positions.

[0033] In one embodiment, the remaining target points and the origin of the coordinate system are arranged after the array position of the inner circle of the target graphic array, and the method further includes:

[0034] The distribution rules of the target points in the target graphic array are verified;

[0035] The distribution rules include: the values ​​of the first parameter and the second parameter of the outermost target points are both located in the middle value range; among the target points in the inner circle, the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range; the distribution of the second parameter of the a-1 target points in the target graphic array satisfies a normal distribution.

[0036] A test graphic generation apparatus, the apparatus comprising:

[0037] The first generation module is used to generate a parameter restriction region of the test pattern according to the parameter design rules of the test pattern. The test pattern has a first parameter, a second parameter, and a third parameter. The remaining parameter can be determined based on any two of the first parameter, the second parameter, and the third parameter. The parameter restriction region is a region in a coordinate system with the first parameter and the second parameter as coordinate axes.

[0038] The determination module is used to determine a preset number of target points within the parameter restriction area;

[0039] The second generation module is used to generate multiple test graphics based on the coordinates of multiple target points.

[0040] A computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method described above.

[0041] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0042] A computer program product includes a computer program that, when executed by a processor, implements the steps of the method described above.

[0043] The aforementioned test pattern generation method, apparatus, computer equipment, storage medium, and computer program product generate a parameter constraint region for the test pattern based on the parameter design rules, thereby graphically representing the parameter design rules into a parameter constraint region. Target points are selected within the parameter constraint region, and test patterns are generated based on these target points, enabling the rapid and effective selection of parameters that satisfy the parameter design rules and the quick generation of test patterns. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the testing of a graphics generation method in one embodiment;

[0045] Figure 2This is a flowchart illustrating step S20 of testing the graphics generation method in one embodiment;

[0046] Figure 3 This is a flowchart illustrating step S24 of testing the graphics generation method in one embodiment;

[0047] Figure 4 This is a flowchart illustrating step S10 of testing the graphics generation method in one embodiment;

[0048] Figure 5 This is a schematic diagram of the parameter restriction region formed in one embodiment;

[0049] Figure 6 This is a schematic diagram illustrating m values ​​for the first parameter in one embodiment;

[0050] Figure 7 This is a schematic diagram illustrating the formation of candidate points in one embodiment;

[0051] Figure 8 This is a schematic diagram illustrating the value distribution of the second parameter in one embodiment;

[0052] Figure 9 This is a schematic diagram illustrating the generation of multiple test graphics in one embodiment;

[0053] Figure 10 This is a schematic diagram illustrating the formation of positioning points in one embodiment;

[0054] Figure 11 This is a schematic diagram of the formation of positioning points in another embodiment;

[0055] Figure 12 This is a schematic diagram of a test graphics array in one embodiment;

[0056] Figure 13 This is a structural block diagram of a test graphics generation device in one embodiment. Detailed Implementation

[0057] 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.

[0058] In one embodiment, see Figure 1 This paper provides a method for generating test graphics, which can be applied to the establishment of semiconductor process models. The semiconductor process model can include, but is not limited to, chemical mechanical polishing (CMP) models. The method includes the following steps:

[0059] Step S10, please refer to Figure 5According to the parameter design rules of test pattern 100, the parameter restriction region of test pattern 100 is generated. Test pattern 100 has a first parameter, a second parameter and a third parameter. The remaining one can be determined by any two of the first parameter, the second parameter and the third parameter. The parameter design rules of test pattern 100 include the design rules of the first parameter, the second parameter and the third parameter. The parameter restriction region is the region under the coordinate system with the first parameter and the second parameter as the coordinate axes.

[0060] Please see Figure 9 The test pattern 100 may include multiple main patterns 110 arranged in an array. The main patterns 110 may be, for example, but are not limited to, rectangular.

[0061] The first, second, and third parameters of the test graphic 100 can be parameters related to the size, arrangement, etc. of the main graphic 110.

[0062] As an example, the first parameter includes the width W of the main graphic 110, the second parameter includes the density D of the main graphic 110, and the third parameter includes the spacing S of the main graphic 110, where D = W / (W + S).

[0063] Of course, the setting of the first, second, and third parameters is not limited to this. For example, the width W of the main graphic 110 can also be used as the first parameter, the spacing S of the main graphic 110 as the second parameter, and the density D of the main graphic 110 as the third parameter.

[0064] The parameter design rules for test graphic 100 include design rules for the first parameter, the second parameter, and the third parameter. Furthermore, the remaining parameter can be determined based on any two of the first, second, and third parameters.

[0065] Therefore, in a coordinate system with the first parameter and the second parameter as coordinate axes, a parameter constraint region for the test pattern 100 that satisfies the parameter design rules can be formed.

[0066] Step S20: Determine a preset number of target points within the parameter constraint area.

[0067] The parameter constraint region graphically represents the parameter design rules. Points located within the parameter constraint region then satisfy the parameter design rules. It's understood that points "within the parameter constraint region" can include points inside the contour line of the parameter constraint region, or points on the contour line of the parameter constraint region.

[0068] Therefore, the preset number of target points within the parameter constraint area will not violate the parameter design rules. Furthermore, multiple target points can be quickly determined within the parameter constraint area. The preset number can be set according to actual needs.

[0069] Step S30, please refer to Figure 9 Multiple test graphics 100 are generated based on the coordinates of multiple target points.

[0070] The target point is located in a coordinate system with the first parameter and the second parameter as coordinate axes. The coordinates of the target point can include the coordinates of the first parameter and the second parameter.

[0071] Therefore, based on the coordinates of a target point, the values ​​of a first parameter and a second parameter can be determined, and the value of the third parameter can also be determined accordingly. Based on this, a test pattern 100 can be generated. Multiple test patterns 100 can be generated based on the coordinates of multiple target points.

[0072] In this embodiment, a parameter constraint region for the test pattern 100 is generated according to the parameter design rules of the test pattern 100, thereby graphically representing the parameter design rules as a parameter constraint region. Target points are selected within the parameter constraint region, and the test pattern 100 is generated based on these target points. This allows for the rapid and efficient selection of parameters that meet the parameter design rules and the rapid production of the test pattern 100.

[0073] In one embodiment, see Figure 2 In step S10, while generating the parameter restriction area of ​​the test pattern 100 according to the parameter design rules of the test pattern 100, a parameter range is also generated. The parameter range includes the first range of the first parameter and the second range of the second parameter.

[0074] Step S20 includes:

[0075] Step S21: Determine the first value quantity of the first parameter and the second value quantity of the second parameter according to the preset quantity, where the first value quantity is m and the second value quantity is n.

[0076] When m and n are determined according to a preset quantity, m×n can be made to be greater than the preset quantity.

[0077] The values ​​of m and n can be obtained by performing calculations according to preset quantities and preset arithmetic rules.

[0078] As an example, the smallest integer greater than or equal to the square root of a preset quantity can be calculated first. Then, based on this smallest integer and the preset redundancy quantity, the first and / or second value quantities are determined. The preset redundancy quantity can be, but is not limited to, a positive integer greater than or equal to 4. Both the preset redundancy quantity and the preset quantity can be set according to actual needs.

[0079] For example, if the preset quantity is 48 and the preset redundancy is 4, then the square root of the preset quantity is approximately 6.93. The smallest integer greater than or equal to 6.93 is 7. Therefore, the first and / or second possible quantities can be 7 + 4 = 11.

[0080] Of course, the algorithm for obtaining the values ​​of m and n based on the preset quantity is not limited to this; it can be set according to actual needs.

[0081] Step S22: Within the first range, take m values ​​for the first parameter (see [reference]). Figure 6 Furthermore, for each value of the first parameter, n values ​​of the second parameter within the second range are taken to form m×n original points.

[0082] The remaining parameter can be determined by any two of the first, second, and third parameters. After determining the value of the first parameter, if the third parameter is determined, then the second parameter is also determined.

[0083] In a coordinate system with the first and second parameters as coordinate axes, the m×n original points lie within a rectangular region defined by the first range of the first parameter and the second range of the second parameter. The parameter constraint regions that simultaneously define the first, second, and third parameters are part of this rectangular region.

[0084] Therefore, we can design m×n original points, in which some original points are located within the parameter constraint region and some original points are located outside the parameter constraint region.

[0085] Step S23, please refer to Figure 7 Remove the original points located outside the parameter constraint area, and the remaining original points form the candidate points.

[0086] By using parameter-restricted regions, original points that violate parameter design rules can be quickly removed. The remaining original points form candidate points.

[0087] Step S24: Select a preset number of target points from the candidate points.

[0088] The number of candidate points can be greater than the preset number, so that the preset number of target points can be selected from the candidate points.

[0089] In step S21, the determined values ​​of m and n differ, resulting in different numbers of remaining candidate points after removing the original points outside the parameter-restricted area. Therefore, by selecting a sufficient number of m and n values ​​in step S21, it can be ensured that the number of remaining original points (i.e., the number of candidate points) within the parameter-restricted area is greater than a preset number, thereby obtaining a sufficient number of target points.

[0090] In this embodiment, m×n original points are first formed within a rectangular area defined by the first range of the first parameter and the second range of the second parameter. Then, the original points that violate the parameter design rules are quickly removed through the parameter restriction area, thereby quickly and effectively forming multiple target points that satisfy the parameter design rules.

[0091] In one embodiment, see Figure 3 Step S24 includes:

[0092] Step S241: Under each value of the first parameter, select candidate points within the corresponding selection quantity range, so as to select a preset number of quasi-target points under m values ​​of the first parameter, the selection quantity range being the range of the number of candidate points selected, and under each value of the first parameter, traverse all selectable values ​​within the selection quantity range to select candidate points, so as to select a preset number of quasi-target points multiple times under m values ​​of the first parameter.

[0093] For each value of the first parameter, a corresponding selection quantity range can be set. Different values ​​of the first parameter can result in different or the same selection quantity range, depending on the shape of the parameter-restricted area.

[0094] For example, please see Figure 6 In step S21, the value of m is determined to be 8. In step S22, the eight possible values ​​of the first parameter within the first range are determined to be W1, W2, W3, W4, W5, W6, W7, and W8. Corresponding to W... i The selection quantity range can be set to r. i Where 1 ≤ i ≤ 8. Meanwhile, in r... i In this context, the minimum and maximum values ​​can be set according to actual needs, and the maximum value cannot exceed W. i The total number of corresponding alternative points.

[0095] At this point, based on the shape of the parameter restriction area, the maximum values ​​of W1 to W6 can be set to increase sequentially, while the maximum values ​​of W6 to W8 can be set to be the same.

[0096] For each value of the first parameter, iterate through all possible values ​​within the selection range to select candidate points, so that when selecting a preset number of quasi-target points multiple times under m values ​​of the first parameter:

[0097] For example, the selection range for W1 is 5 to 7. Therefore, when selecting the preset number of quasi-target points for the first time under the m values ​​of the first parameter, 5 candidate points can be selected as quasi-target points at W1. The second time, under the m values ​​of the first parameter, 6 candidate points can be selected as quasi-target points at W1. The third time, under the m values ​​of the first parameter, 7 candidate points can be selected as quasi-target points at W1. The traversal method is similar for other values ​​of the first parameter.

[0098] At the same time, it is understandable that each time a preset number of quasi-target points are selected under the values ​​of m first parameters, the total number of quasi-target points selected is determined (the total number is the preset number). Therefore, the larger the value of the first parameter, the number of candidate points that can be selected for these values ​​will be limited by both the corresponding selection range and the total number of quasi-target points.

[0099] Step S242: Select a preset number of quasi-target points under the values ​​of m first parameters multiple times to form a distribution of multiple values ​​of second parameters.

[0100] The coordinates of the quasi-target point include the first parameter coordinates and the second parameter coordinates. Therefore, please refer to... Figure 8 By selecting a preset number of quasi-target points each time under the m values ​​of the first parameter, a distribution of the values ​​of the second parameter can be formed.

[0101] Step S243: Fit the normal distribution function to the multiple value distributions and select the value distribution with the highest shape similarity as the target value distribution.

[0102] By selecting the distribution with the highest shape similarity, the normal distribution function curve will be closer to a normal distribution. Selecting the distribution with the highest shape similarity allows us to obtain the distribution of the second parameter whose value is closest to a normal distribution, which can then be used as the target distribution.

[0103] Step S244: Form the target points from the quasi-target points corresponding to the target value distribution.

[0104] In this embodiment, by repeatedly selecting a preset number of quasi-target points under the values ​​of m first parameters, and performing normal distribution fitting based on the results of multiple selections, target points that make the values ​​of the second parameter conform to a normal distribution can be effectively obtained. At this point, a test pattern 100 conforming to the requirements of process models such as chemical mechanical polishing models can be effectively formed based on these normally distributed target points.

[0105] In other embodiments, when the requirements of the process model are different, step S24 may also select a preset number of target points from the candidate points in other ways, and this is not limited here.

[0106] In one embodiment, when taking m values ​​for the first parameter within a first range, the values ​​can be taken in a non-linear manner.

[0107] For example, please see Figure 6 When the first parameter is the width of the main graphic 110 in the test graphic 100, the values ​​of the m first parameters can be distributed from dense to sparse in an increasing direction. This allows for the formation of more test graphics 100 with smaller main graphic 110 widths to meet practical application requirements.

[0108] In one embodiment, when taking n values ​​of the second parameter within the second range for each value of the first parameter, a non-linear value selection method can also be adopted.

[0109] For example, when the second parameter is the density of the main graphic 110 in the test graphic 100, the values ​​of the n second parameters are distributed from sparse to dense in the direction from small to large. At this time, more test graphics 100 with larger density main graphics 110 can be formed to meet the needs of practical applications.

[0110] For example, when the second parameter is the spacing between the main graphics 110 in the test graphic 100, the values ​​of the n second parameters are distributed from dense to sparse in the direction from small to large. In this case, more test graphics 100 with smaller spacing between the main graphics 110 can be formed to meet the needs of practical applications.

[0111] Of course, in other embodiments, the values ​​of the first and second parameters are not limited to this. For example, the first and / or second parameters can also be uniformly selected within their respective parameter ranges.

[0112] In one embodiment, the parameter design rules include the maximum and minimum values ​​of the first parameter and the maximum and minimum values ​​of the second parameter.

[0113] Furthermore, the parameter design rules include the minimum value of the third parameter under multiple preset ranges, and the preset range is the range of the value interval of the first parameter.

[0114] The maximum and minimum values ​​of the second parameter can include multiple ranges of the first parameter, thus encompassing multiple preset ranges for the first parameter. Within each preset range of the first parameter, the parameter design rule can assign a minimum value for the third parameter.

[0115] As an example, the test pattern 100 includes multiple main patterns 110 arranged in an array. The first parameter includes the width W of the main pattern 110, the second parameter includes the density D of the main pattern 110, and the third parameter includes the spacing S of the main pattern 110, where D = W / (W + S).

[0116] Therefore, the maximum and minimum values ​​of the first parameter are the maximum and minimum values ​​of the width W of the main graphic 110.

[0117] The maximum and minimum values ​​of the second parameter are the maximum and minimum values ​​of the density D of the main graphic 110.

[0118] That is, within each preset range of the width W of the main graphic 110, the parameter design rule can set a minimum value for the spacing S of the main graphic 110.

[0119] Please also see Figure 4 Step S10 includes:

[0120] Step S11: Perform calculations on the maximum and minimum values ​​of each preset range with the minimum value of the third parameter corresponding to that preset range to obtain the value of the second parameter under the maximum and minimum values ​​of each preset range.

[0121] For example, please see Figure 10 or Figure 11 The minimum value of the first parameter x is x1, and the maximum value of the first parameter x is x5. The range between x1 and x5 includes three value intervals: [x1, x2], [x2, x3], and [x3, x4], which in turn includes three preset ranges of the first parameter x: x1≤x≤x2, x2≤x≤x3, and x3≤x≤x4.

[0122] In this case, the parameter design rules can include the following: when the value of the first parameter x is x1≤x≤x2, the minimum value of the third parameter z is z1; when the value of the first parameter x is x2≤x≤x3, the minimum value of the third parameter z is z2; and when the value of the first parameter x is x3≤x≤x4, the minimum value of the third parameter z is z3. However, when the value of the first parameter x is greater than x4, the parameter design rules do not require a minimum value for the third parameter z.

[0123] Then, x1 and x2 within the preset range x1≤x≤x2 are respectively calculated with z1 to obtain two values ​​y1 and y2 of the second parameter y. Where the first parameter x is the width W of the main graphic 110, the second parameter y is the density D of the main graphic 110, and the third parameter z is the spacing S of the main graphic 110, the formula for obtaining the second parameter y can be, for example, y=x / (x+z). Similarly, x2 and x3 within the preset range x2≤x≤x3 are respectively calculated with z2 to obtain two values ​​y3 and y4 of the second parameter y; x3 and x4 within the preset range x3≤x≤x4 are respectively calculated with z3 to obtain two values ​​y5 and y6 of the second parameter y.

[0124] Step S12: Based on the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, the maximum and minimum values ​​of each preset range, and the values ​​of the second parameter corresponding to the maximum and minimum values ​​of each preset range, determine multiple positioning points on the coordinate plane determined by the first parameter and the second parameter.

[0125] For example, based on the maximum and minimum values ​​of each preset range and the corresponding value of the second parameter, two positioning points A (x2, y2) and B (x2, y3) can be formed at x2, two positioning points C (x3, y4) and D (x3, y5) can be formed at x3, and one positioning point E (x1, y1) can be formed at x1.

[0126] Meanwhile, at x1, according to the parameter design rules, when the third parameter z (such as the spacing S of the main graphic 110) is greater than the minimum value, then according to y=x / (x+z), the second parameter y is less than y1, and the second parameter y also needs to be greater than the minimum value y0 of the second parameter y. Based on this, another positioning point F(x1, y0) can be formed at x1.

[0127] Meanwhile, at x4, the value of the second parameter y, calculated according to the formula, is y6. Please refer to [link / reference]. Figure 11 When y6 is less than or equal to the maximum value y7 of the second parameter y, a location point G(x4, y6) can be formed at x4. Please refer to [link / reference]. Figure 10 When y6 is greater than the maximum value y7 of the second parameter y, the parameter design rule is violated. Therefore, a location point G(x4, y7) can be formed at x4. In this case, lowering the second parameter y is equivalent to raising the third parameter z, which still satisfies the parameter design rule. Simultaneously, when the value of the first parameter x is greater than x4 but less than or equal to the maximum value x5, the parameter design rule does not require a minimum value for the third parameter z. However, since the maximum value of the first parameter x is at x5, the value of the second parameter y still needs to be between the maximum value y7 and the minimum value y0 of the second parameter y. Thus, two location points H(x5, y7) and I(x5, y0) can be formed at x5.

[0128] Step S13: Connect multiple positioning points to form a parameter constraint area.

[0129] For example, positioning points A to I can be connected to form a parameter-constrained region.

[0130] In one embodiment, the test pattern generation method is used to generate test patterns 100 in a target pattern array. The number of array positions in the target pattern array is 'a'. Simultaneously, the preset number is 'a-1'. Then, step S20 determines 'a-1' target points within the parameter constraint region.

[0131] For example, if the target pattern array is a 7x7 pattern array, then the number of array positions is 49. Meanwhile, according to the design requirements of the semiconductor process model (such as a chemical mechanical polishing model), one array position can be left unset with the test pattern 100. Therefore, a preset number of 48 can be designed. Thus, the 48 target points determined in step S20 within the parameter constraint region can form 48 test patterns 100 in the target pattern array.

[0132] Step S30 generates multiple test graphics 100 based on the coordinates of multiple target points, including:

[0133] Step S31: Divide the values ​​of all second parameters and all first parameters of the a-1 target points into high value ranges, medium value ranges, and low value ranges according to the magnitude of the values.

[0134] This involves dividing all the second parameters at the a-1 target points into high, medium, and low value ranges based on their magnitude. The specific ranges for these ranges can be set according to actual requirements.

[0135] Furthermore, all the first parameters at the a-1 target points are divided into high-value, medium-value, and low-value ranges based on their values. The specific ranges of the high-value, medium-value, and low-value ranges of the first parameters can be set according to actual needs.

[0136] At this point, for example, we can first sort the first parameter of the a-1 target points in ascending order, and sort the second parameter of the a-1 target points in ascending order as well. Then, we take the first 10%-20% (e.g., 15%) of the first parameter (or second parameter) values ​​as the low value range, the last 10%-20% (e.g., 15%) of the first parameter (or second parameter) values ​​as the high value range, and the remaining first parameter (or second parameter) values ​​as the middle value range.

[0137] Step S32, please refer to Figure 12 The target points, whose values ​​for both the first and second parameters are within the range of the target parameters, are arranged in the outermost array position of the target graphic array.

[0138] The number of target points whose values ​​for both the first and second parameters are within the range of values ​​can be greater than the number of array positions in the outermost ring of the target graphic array, thus ensuring that the array positions in the outermost ring of the target graphic array can be effectively filled with the test graphic 100.

[0139] Step S33: Arrange the remaining target points and the origin of the coordinates in the array position of the inner circle of the target graphic array, wherein the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range.

[0140] You can first arrange the layout according to the first arrangement method.

[0141] In the first arrangement, the values ​​of the first parameter of target points at adjacent array positions are arranged with high and low value ranges adjacent to each other, and the values ​​of the second parameter of target points at adjacent array positions are also arranged with high and low value ranges adjacent to each other. Simultaneously, the first and second parameters of the coordinate origin are both 0, thus allowing this point to correspond to an array position without a test graphic 100. The coordinate origin can be placed at any array position within the inner circle of the target graphic array and can be adjacent to any target point.

[0142] When the first arrangement method cannot fully meet the requirements, the first arrangement method and the second arrangement method can be combined. In the second arrangement method, the values ​​of the second parameter and / or the first parameter of the target points at adjacent array positions can also be arranged with high value range and medium value range adjacent to each other, and low value range and medium value range adjacent to each other.

[0143] The arrangement ends when the preset number of target points and the origin can be arranged in each array position according to the above arrangement rules. Otherwise, the process can return to step S20 to regenerate the preset number of target points until the preset number of target points and the origin can be arranged in each array position according to the above arrangement rules.

[0144] Step S35: Generate test pattern 100 at the corresponding array positions based on the arranged target points.

[0145] Based on a target point, a test pattern 100 can be generated at the array position corresponding to that target point. Based on a-1 target points, a-1 corresponding test patterns 100 can be generated at each array position, thus effectively completing the generation of the test pattern 100.

[0146] In one embodiment, after step S33, the method further includes:

[0147] Step S34: Verify the distribution rules of the target points in the target graphic array.

[0148] Distribution rules include:

[0149] Rule 1: The values ​​of the first and second parameters of the outermost target point are both within the middle range.

[0150] Rule 2: Among the target points in the inner circle, the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range.

[0151] Rule 3: The distribution of the second parameter of the a-1 target points in the target graphic array satisfies a normal distribution.

[0152] The verification is successful when the test graphic 100 in the target graphic array simultaneously satisfies rules one, two, and three. Otherwise, it is necessary to return to step S20 to regenerate the preset number of target points and arrange them.

[0153] By verifying the distribution rules of the test pattern 100 in the target pattern array, the reliability of the test pattern 100 in the target pattern array can be effectively improved.

[0154] It should be understood that, although Figure 1-4 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1-4 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0155] In one embodiment, such as Figure 13 As shown, a test graphic generation device is provided, comprising: a first generation module 10, a determining module 20, and a second generation module 30, wherein:

[0156] The first generation module 10 is used to generate the parameter restriction region of the test pattern 100 according to the parameter design rules of the test pattern 100. The test pattern 100 has a first parameter, a second parameter and a third parameter. The remaining one can be determined based on any two of the first parameter, the second parameter and the third parameter. The parameter restriction region is the region under the coordinate system with the first parameter and the second parameter as the coordinate axes.

[0157] The determination module 20 is used to determine a preset number of target points within the parameter-restricted area.

[0158] The second generation module 30 is used to generate multiple test graphics 100 based on the coordinates of multiple target points.

[0159] In one embodiment, the first generation module generates the parameter restriction region of the test pattern 100 according to the parameter design rules of the test pattern 100, and also generates the parameter range, which includes the first range of the first parameter and the second range of the second parameter.

[0160] The determination module includes a first determination unit, an original point formation unit, a removal unit, and a selection unit.

[0161] The first determining unit is used to determine the first value quantity of the first parameter and the second value quantity of the second parameter according to a preset quantity, wherein the first value quantity is m and the second value quantity is n;

[0162] The original point forming unit is used to take m values ​​for the first parameter within a first range, and for each value of the first parameter, take n values ​​for the second parameter within a second range to form m×n original points.

[0163] The removal unit is used to remove original points located outside the parameter constraint region, and the remaining original points form candidate points.

[0164] The selection unit is used to select a preset number of target points from the candidate points.

[0165] In one embodiment, the selection unit includes a selection subunit, a distribution forming subunit, a distribution selection subunit, and a forming subunit:

[0166] The selection sub-unit is used to select candidate points within the corresponding selection quantity range for each value of the first parameter, so as to select a preset number of quasi-target points under m values ​​of the first parameter. The selection quantity range is the range of the number of candidate points selected. Under each value of the first parameter, it iterates through all selectable values ​​within the selection quantity range to select candidate points, so as to select a preset number of quasi-target points multiple times under m values ​​of the first parameter.

[0167] The distribution forming sub-unit is used to select a preset number of quasi-target points under the values ​​of m first parameters multiple times to form a distribution of values ​​of the second parameter.

[0168] The distribution selection sub-unit is used to fit a normal distribution function to multiple value distributions, and selects the value distribution with the highest shape similarity as the target value distribution.

[0169] The sub-units are used to form target points by distributing the target values ​​to corresponding quasi-target points.

[0170] In one embodiment, the original point forming unit adopts a non-linear value selection method when taking m values ​​for the first parameter within a first range; and / or, adopts a non-linear value selection method when taking n values ​​for the second parameter within a second range for each value of the first parameter.

[0171] In one embodiment, the test pattern 100 includes a plurality of main patterns 110 arranged in an array. The first parameter includes the width W of the main pattern 110, the second parameter includes the density D of the main pattern 110, and the third parameter includes the spacing S of the main pattern 110, where D = W / (W + S).

[0172] In one embodiment, the parameter design rules include the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, and the minimum value of the third parameter within multiple preset ranges, wherein the preset range is the range of values ​​for the first parameter.

[0173] The first generation module includes a calculation unit, a positioning unit, and a connection unit.

[0174] The calculation unit is used to perform calculations on the maximum and minimum values ​​of each preset range and the minimum value of the third parameter corresponding to that preset range, respectively, to obtain the value of the second parameter under the maximum and minimum values ​​of each preset range.

[0175] The positioning unit is used to determine multiple positioning points on the coordinate plane determined by the first parameter and the second parameter based on the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, the maximum and minimum values ​​of each preset range, and the values ​​of the second parameter corresponding to the maximum and minimum values ​​of each preset range.

[0176] The connecting unit is used to connect multiple positioning points to form a parameter-restricted area.

[0177] In one embodiment, the test pattern generating device is used to generate a test pattern 100 in a target pattern array, wherein the number of array positions in the target pattern array is a, and the preset number is a-1.

[0178] The second generation module includes a division unit, a first arrangement unit, a second arrangement unit, and a generation unit.

[0179] The partitioning unit is used to divide the values ​​of all second parameters and all first parameters of a-1 target points into high value ranges, medium value ranges, and low value ranges according to the value size;

[0180] The first arrangement unit is used to arrange target points whose values ​​of the first parameter and the second parameter are both within the middle range in the outermost array position of the target graphic array;

[0181] The second arrangement unit is used to arrange the remaining target points and the origin of coordinates in the array position of the inner circle of the target graphic array. The values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range.

[0182] The generation unit is used to generate test pattern 100 at the corresponding array position based on the arranged target points.

[0183] In one embodiment, the second generation module further includes a verification unit.

[0184] The verification unit is used to verify the distribution rules of target points in the target graphic array. The distribution rules include: the values ​​of the first and second parameters of the outermost target points are both within the middle range; among the target points in the inner circle, the values ​​of the first parameters of adjacent target points are not simultaneously within the high or low range, and the values ​​of the second parameters of adjacent target points are not simultaneously within the high or low range; the distribution of the second parameters of the a-1 target points in the target graphic array follows a normal distribution.

[0185] Specific limitations regarding the test graphic generation device can be found in the limitations of the test graphic generation method described above, and will not be repeated here. Each module in the aforementioned test graphic generation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, 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.

[0186] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0187] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0188] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0189] 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 methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0190] 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 specification.

[0191] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. 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 patent application should be determined by the appended claims.

Claims

1. A method for generating test graphics, characterized in that, include: According to the parameter design rules of the test pattern, a parameter restriction region of the test pattern is generated. The test pattern has a first parameter, a second parameter, and a third parameter. The remaining parameter can be determined based on any two of the first parameter, the second parameter, and the third parameter. The parameter design rules of the test pattern include the design rules of the first parameter, the second parameter, and the third parameter. The parameter restriction region is the region in a coordinate system with the first parameter and the second parameter as coordinate axes. A preset number of target points are determined within the parameter constraint area; Multiple test graphics are generated based on the coordinates of the multiple target points.

2. The test graphic generation method according to claim 1, characterized in that, Based on the parameter design rules of the test pattern, while generating the parameter constraint region of the test pattern, a parameter range is also generated. The parameter range includes a first range for the first parameter and a second range for the second parameter. Determining a preset number of target points within the parameter constraint area includes: Based on the preset quantity, determine the first number of values ​​for the first parameter and the second number of values ​​for the second parameter, where the first number of values ​​is m and the second number of values ​​is n; Within the first range, m values ​​are taken for the first parameter, and for each value of the first parameter, n values ​​of the second parameter within the second range are taken to form m×n original points; Remove the original points located outside the parameter restriction area, and the remaining original points form candidate points; From the candidate points, select the preset number of target points.

3. The test graphic generation method according to claim 2, characterized in that, Selecting the preset number of target points from the candidate points includes: Under each value of the first parameter, candidate points are selected within the corresponding selection quantity range, so as to select the preset number of quasi-target points under m values ​​of the first parameter. The selection quantity range is the range of the number of candidate points selected. Under each value of the first parameter, all selectable values ​​within the selection quantity range are traversed to select candidate points, so as to select the preset number of quasi-target points multiple times under m values ​​of the first parameter. Multiple distributions of the second parameter values ​​are formed by selecting the preset number of quasi-target points under the m values ​​of the first parameter multiple times. The multiple value distributions are fitted with a normal distribution function, and the value distribution with the highest shape similarity is selected as the target value distribution. The target point is formed by taking the quasi-target points corresponding to the target value distribution.

4. The test graphic generation method according to claim 2, characterized in that, Within the first range, when the first parameter takes m values, a non-linear value selection method is adopted; and / or, under each value of the first parameter, when the second parameter takes n values ​​within the second range, a non-linear value selection method is adopted.

5. The test graphic generation method according to claim 1, characterized in that, The test pattern includes multiple main patterns arranged in an array. The first parameter includes the width W of the main pattern, the second parameter includes the density D of the main pattern, and the third parameter includes the spacing S of the main patterns, where D = W / (W + S).

6. The test graphic generation method according to claim 1 or 5, characterized in that, The parameter design rules include the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, and the minimum value of the third parameter within multiple preset ranges, where the preset ranges are the ranges of values ​​for the first parameter. The step of generating the parameter constraint region of the test pattern according to the parameter design rules of the test pattern includes: The maximum and minimum values ​​of each preset range are calculated with the minimum value of the third parameter corresponding to the preset range to obtain the value of the second parameter under the maximum and minimum values ​​of each preset range. Based on the maximum and minimum values ​​of the first parameter, the maximum and minimum values ​​of the second parameter, the maximum and minimum values ​​of each preset range, and the values ​​of the second parameter corresponding to the maximum and minimum values ​​of each preset range, multiple positioning points are determined on the coordinate plane determined by the first parameter and the second parameter. The multiple positioning points are connected to form the parameter restriction area.

7. The test graphic generation method according to claim 1, characterized in that, This is used to generate test patterns in a target pattern array, where the number of array positions in the target pattern array is 'a', and the preset number is a-1. The step of generating multiple test images based on the coordinates of multiple target points includes: The values ​​of all the second parameters and all the first parameters at the a-1 target points are divided into high value ranges, medium value ranges, and low value ranges according to their magnitude; The target points whose values ​​of the first parameter and the second parameter are both within the range of the middle value are arranged in the outermost array position of the target graphic array; The remaining target points and the origin of the coordinate system are arranged in the inner circle of the target graphic array, wherein the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range. Based on the arranged target points, the test pattern is generated at the corresponding array positions.

8. The test graphic generation method according to claim 7, characterized in that, Arranging the remaining target points and the origin of the coordinate system after the array position of the inner circle of the target graphic array, the method further includes: The distribution rules of the target points in the target graphic array are verified; The distribution rules include: the values ​​of the first parameter and the second parameter of the outermost target points are both located in the middle value range; among the target points in the inner circle, the values ​​of the first parameter of adjacent target points are not simultaneously located in the high value range or the low value range, and the values ​​of the second parameter of adjacent target points are not simultaneously located in the high value range or the low value range; the distribution of the second parameter of the a-1 target points in the target graphic array satisfies a normal distribution.

9. A test graphic generation device, characterized in that, The device includes: The first generation module is used to generate a parameter restriction region of the test pattern according to the parameter design rules of the test pattern. The test pattern has a first parameter, a second parameter, and a third parameter. The remaining parameter can be determined based on any two of the first parameter, the second parameter, and the third parameter. The parameter restriction region is a region in a coordinate system with the first parameter and the second parameter as coordinate axes. The determination module is used to determine a preset number of target points within the parameter restriction area; The second generation module is used to generate multiple test graphics based on the coordinates of multiple target points.

10. 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 8.

11. 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 8.

12. 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 8.

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