Просмотр исходного текста страницы Open Source VHDL Verification Methodology/Пример использования OS-VVM/Пример 2

{{OS-VVM TOC}}

== Листинги 1 ==

 -- Для покрытия всех пар состояний требуется 1615 циклов
 -- покрытие A достигается за 103 циклов
 -- покрытие B достикается за 68 циклов

{{Hider|Листинг файла testbench(tb1)}}
{{Файл|tstb_tb1.vhd|
<source lang="vhdl">
-- Для покрытия всех пар состояний требуется 1615 циклов
-- покрытие A достигается за 103 циклов
-- покрытие B достикается за 68 циклов

library ieee;
use ieee.std_logic_1164.all;
use ieee.math_real.all;
use ieee.numeric_std.all;

use work.RandomPkg.all;
use work.CoveragePkg.all;

entity testbench is
end;

architecture tb1 of testbench is

  component sxema
    port (a, b : in  std_logic_vector (4 downto 1);
          d    : out std_logic_vector (8 downto 1));
  end component;

  signal a, b : std_logic_vector (4 downto 1);
  signal d    : std_logic_vector (8 downto 1);

  shared variable CovA, CovB : CovPType;
  shared variable CovD       : CovPType;
  shared variable CovCrossAB : CovPType;

begin
  p0 : sxema
    port map (
      a => a,
      b => b,
      d => d);

  RandomGenProc1 : process
    variable RndValA, RndValB         : real;           -- Random value
    variable RndA, RndB               : integer;
    variable SeedA1                   : positive := 7;  -- initialize seeds
    variable SeedA2                   : positive := 1;
    variable SeedB1                   : positive := 4;  -- initialize seeds
    variable SeedB2                   : positive := 2;
    variable i                        : natural  := 0;
    variable CovACovered, CovBCovered : natural  := 0;


  begin
    -- создание корзин для a, b, d
    CovA.AddBins(GenBin(0, 15));
    CovB.AddBins(GenBin(0, 15));
    CovD.AddBins(GenBin(0, 225));
    CovCrossAB.AddCross(GenBin(0, 15), GenBin(0, 15));

    MainCovLoop : while not (CovCrossAB.IsCovered) loop

      uniform(SeedA1, SeedA2, RndValA);      -- randomize 0.0 to 1.0
      uniform(SeedB1, SeedB2, RndValB);      -- randomize 0.0 to 1.0
      RndA := integer(trunc(RndValA*16.0));  -- scale to 0 to 15
      RndB := integer(trunc(RndValB*16.0));  -- scale to 0 to 15

      a <= std_logic_vector(to_unsigned(RndA, 4));
      b <= std_logic_vector(to_unsigned(RndB, 4));

      wait for 10 ns;

      CovA.ICover(to_integer(unsigned(a)));
      CovB.ICover(to_integer(unsigned(b)));
      CovCrossAB.ICover((to_integer(unsigned(a)), to_integer(unsigned(b))));

      CovD.ICover(to_integer(unsigned(d)));
      i := i+1;
      if (CovA.IsCovered and CovACovered = 0) then
        CovACovered := i;
      end if;

      if (CovB.IsCovered and CovBCovered = 0) then
        CovBCovered := i;
      end if;

    end loop;

    wait for 10 ns;

    CovA.WriteBin;
    CovB.WriteBin;
    CovD.WriteBin;
    CovCrossAB.WriteBin;

    CovA.WriteCovDb ("tb1_CovA.db", OpenKind             => write_mode);
    CovB.WriteCovDb ("tb1_CovB.db", OpenKind             => write_mode);
    CovD.WriteCovDb ("tb1_CovD.db", OpenKind             => write_mode);
    CovCrossAB.WriteCovDb ("tb1_CovCrossAB.db", OpenKind => write_mode);

    wait;
  end process;

end architecture tb1;
</source>}}
{{Hider|end}}



{{Hider|Листинг файла testbench(tb1a)}}
<source lang="vhdl" line highlight="57-62,70-75">
-- Для покрытия всех пар состояний требуется 1615 циклов
-- покрытие A достигается за 103 циклов
-- покрытие B достикается за 68 циклов

library ieee;
use ieee.std_logic_1164.all;
use ieee.math_real.all;
use ieee.numeric_std.all;

entity testbench is
end;

architecture tb1a of testbench is

  component sxema
    port (a, b : in  std_logic_vector (4 downto 1);
          d    : out std_logic_vector (8 downto 1));
  end component;

  signal a, b : std_logic_vector (4 downto 1);
  signal d    : std_logic_vector (8 downto 1);


  shared variable CovA, CovB : integer_vector (0 to 15) := (others => 0);
  shared variable CovCrossAB : integer_vector (0 to 255) := (others => 0);

begin
  p0 : sxema
    port map (a => a, b => b, d => d);

  RandomGenProc1 : process
    variable RndValA, RndValB         : real;           -- Random value
    variable RndA, RndB, a_i, b_i     : integer;
    variable SeedA1                   : positive := 7;  -- initialize seeds
    variable SeedA2                   : positive := 1;
    variable SeedB1                   : positive := 4;  -- initialize seeds
    variable SeedB2                   : positive := 2;
    variable i                        : natural  := 0;
    variable CovACovered, CovBCovered : natural  := 0;
    variable CovCrossABCovered        : natural  := 0;

  begin
    -- создание корзин для a, b, d

    MainCovLoop : while not (CovCrossABCovered = 1) loop

      uniform(SeedA1, SeedA2, RndValA);      -- randomize 0.0 to 1.0
      uniform(SeedB1, SeedB2, RndValB);      -- randomize 0.0 to 1.0
      RndA := integer(trunc(RndValA*16.0));  -- scale to 0 to 15
      RndB := integer(trunc(RndValB*16.0));  -- scale to 0 to 15

      a <= std_logic_vector(to_unsigned(RndA, 4));
      b <= std_logic_vector(to_unsigned(RndB, 4));

      wait for 10 ns;

      a_i := to_integer(unsigned(a));
      b_i := to_integer(unsigned(b));
      CovA(a_i) := CovA(a_i) + 1 ;
      CovB(b_i) := CovB(b_i) + 1 ;

      CovCrossAB(b_i*16+a_i) := CovCrossAB(b_i*16+a_i) + 1;

      i := i+1;

      if i = 1000000 then
        exit;
      end if;

      CovACovered := 1;
      for j in 0 to 15 loop
        if CovA(j)=0 then
          CovACovered := 0;
        end if;
      end loop;  -- j

      CovBCovered := 1;
      for j in 0 to 15 loop
        if CovB(j)=0 then
          CovBCovered := 0;
        end if;
      end loop;  -- j

      CovCrossABCovered := 1;
      for j in 0 to 255 loop
        if CovCrossAB(j)=0 then
          CovCrossABCovered := 0;
        end if;
      end loop;  -- j
      
    end loop;

    wait for 10 ns;

    wait;
  end process;

end architecture tb1a;
</source>{{Hider|end}}


==== Распределение покрытия CovA ====

<gnuplot>
set yrange [80:120]
#set logscale y
set xrange [-0.5:15.5]
set style fill solid 0.5 border
#set style histogram cluster gap 1
set boxwidth 0.8
plot  '-' using 6:2 t 'CovA' with boxes lt 2 lw 1
# 1 16 
1 96 1 1 9.600000e+03 0 0 
1 110 1 1 1.100000e+04 1 1 
1 104 1 1 1.040000e+04 2 2 
1 117 1 1 1.170000e+04 3 3 
1 110 1 1 1.100000e+04 4 4 
1 93 1 1 9.300000e+03 5 5 
1 96 1 1 9.600000e+03 6 6 
1 90 1 1 9.000000e+03 7 7 
1 100 1 1 1.000000e+04 8 8 
1 112 1 1 1.120000e+04 9 9 
1 105 1 1 1.050000e+04 10 10 
1 93 1 1 9.300000e+03 11 11 
1 98 1 1 9.800000e+03 12 12 
1 104 1 1 1.040000e+04 13 13 
1 95 1 1 9.500000e+03 14 14 
1 92 1 1 9.200000e+03 15 15 
</gnuplot>

==== Распределение покрытия CovB ====

<gnuplot>
#set yrange [80:120]
#set logscale y
set xrange [-0.5:15.5]
set style fill solid 0.5 border
#set style histogram cluster gap 1
set boxwidth 0.8
plot  '-' using 6:2 t 'CovB' with boxes lt 2 lw 1
# 1 16 
1 107 1 1 1.070000e+04 0 0 
1 114 1 1 1.140000e+04 1 1 
1 79 1 1 7.900000e+03 2 2 
1 104 1 1 1.040000e+04 3 3 
1 96 1 1 9.600000e+03 4 4 
1 99 1 1 9.900000e+03 5 5 
1 98 1 1 9.800000e+03 6 6 
1 111 1 1 1.110000e+04 7 7 
1 107 1 1 1.070000e+04 8 8 
1 78 1 1 7.800000e+03 9 9 
1 100 1 1 1.000000e+04 10 10 
1 102 1 1 1.020000e+04 11 11 
1 95 1 1 9.500000e+03 12 12 
1 112 1 1 1.120000e+04 13 13 
1 116 1 1 1.160000e+04 14 14 
1 97 1 1 9.700000e+03 15 15 
</gnuplot>

==== Распределение покрытия CovD ====

<gnuplot>
#set yrange [80:120]
set logscale y
set xrange [-0.5:225.5]
set style fill solid 0.5 border
#set style histogram cluster gap 1
set boxwidth 0.8
plot  '-' using 6:2 t 'CovD' with boxes lt 2 lw 1
# 1 226 
1 192 1 1 1.920000e+04 0 0 
1 11 1 1 1.100000e+03 1 1 
1 15 1 1 1.500000e+03 2 2 
1 14 1 1 1.400000e+03 3 3 
1 21 1 1 2.100000e+03 4 4 
1 6 1 1 6.000000e+02 5 5 
1 23 1 1 2.300000e+03 6 6 
1 21 1 1 2.100000e+03 7 7 
1 25 1 1 2.500000e+03 8 8 
1 27 1 1 2.700000e+03 9 9 
1 16 1 1 1.600000e+03 10 10 
1 11 1 1 1.100000e+03 11 11 
1 27 1 1 2.700000e+03 12 12 
1 17 1 1 1.700000e+03 13 13 
1 26 1 1 2.600000e+03 14 14 
1 32 1 1 3.200000e+03 15 15 
1 21 1 1 2.100000e+03 16 16 
1 0 1 1 0.000000e+00 17 17 
1 23 1 1 2.300000e+03 18 18 
1 0 1 1 0.000000e+00 19 19 
1 31 1 1 3.100000e+03 20 20 
1 14 1 1 1.400000e+03 21 21 
1 9 1 1 9.000000e+02 22 22 
1 0 1 1 0.000000e+00 23 23 
1 54 1 1 5.400000e+03 24 24 
1 7 1 1 7.000000e+02 25 25 
1 11 1 1 1.100000e+03 26 26 
1 10 1 1 1.000000e+03 27 27 
1 23 1 1 2.300000e+03 28 28 
1 0 1 1 0.000000e+00 29 29 
1 36 1 1 3.600000e+03 30 30 
1 0 1 1 0.000000e+00 31 31 
1 11 1 1 1.100000e+03 32 32 
1 15 1 1 1.500000e+03 33 33 
1 0 1 1 0.000000e+00 34 34 
1 8 1 1 8.000000e+02 35 35 
1 28 1 1 2.800000e+03 36 36 
1 0 1 1 0.000000e+00 37 37 
1 0 1 1 0.000000e+00 38 38 
1 15 1 1 1.500000e+03 39 39 
1 26 1 1 2.600000e+03 40 40 
1 0 1 1 0.000000e+00 41 41 
1 21 1 1 2.100000e+03 42 42 
1 0 1 1 0.000000e+00 43 43 
1 10 1 1 1.000000e+03 44 44 
1 28 1 1 2.800000e+03 45 45 
1 0 1 1 0.000000e+00 46 46 
1 0 1 1 0.000000e+00 47 47 
1 27 1 1 2.700000e+03 48 48 
1 10 1 1 1.000000e+03 49 49 
1 17 1 1 1.700000e+03 50 50 
1 0 1 1 0.000000e+00 51 51 
1 11 1 1 1.100000e+03 52 52 
1 0 1 1 0.000000e+00 53 53 
1 10 1 1 1.000000e+03 54 54 
1 12 1 1 1.200000e+03 55 55 
1 29 1 1 2.900000e+03 56 56 
1 0 1 1 0.000000e+00 57 57 
1 0 1 1 0.000000e+00 58 58 
1 0 1 1 0.000000e+00 59 59 
1 24 1 1 2.400000e+03 60 60 
1 0 1 1 0.000000e+00 61 61 
1 0 1 1 0.000000e+00 62 62 
1 13 1 1 1.300000e+03 63 63 
1 2 1 1 2.000000e+02 64 64 
1 16 1 1 1.600000e+03 65 65 
1 15 1 1 1.500000e+03 66 66 
1 0 1 1 0.000000e+00 67 67 
1 0 1 1 0.000000e+00 68 68 
1 0 1 1 0.000000e+00 69 69 
1 26 1 1 2.600000e+03 70 70 
1 0 1 1 0.000000e+00 71 71 
1 28 1 1 2.800000e+03 72 72 
1 0 1 1 0.000000e+00 73 73 
1 0 1 1 0.000000e+00 74 74 
1 8 1 1 8.000000e+02 75 75 
1 0 1 1 0.000000e+00 76 76 
1 8 1 1 8.000000e+02 77 77 
1 18 1 1 1.800000e+03 78 78 
1 0 1 1 0.000000e+00 79 79 
1 20 1 1 2.000000e+03 80 80 
1 6 1 1 6.000000e+02 81 81 
1 0 1 1 0.000000e+00 82 82 
1 0 1 1 0.000000e+00 83 83 
1 26 1 1 2.600000e+03 84 84 
1 0 1 1 0.000000e+00 85 85 
1 0 1 1 0.000000e+00 86 86 
1 0 1 1 0.000000e+00 87 87 
1 14 1 1 1.400000e+03 88 88 
1 0 1 1 0.000000e+00 89 89 
1 13 1 1 1.300000e+03 90 90 
1 18 1 1 1.800000e+03 91 91 
1 0 1 1 0.000000e+00 92 92 
1 0 1 1 0.000000e+00 93 93 
1 0 1 1 0.000000e+00 94 94 
1 0 1 1 0.000000e+00 95 95 
1 12 1 1 1.200000e+03 96 96 
1 0 1 1 0.000000e+00 97 97 
1 7 1 1 7.000000e+02 98 98 
1 7 1 1 7.000000e+02 99 99 
1 6 1 1 6.000000e+02 100 100 
1 0 1 1 0.000000e+00 101 101 
1 0 1 1 0.000000e+00 102 102 
1 0 1 1 0.000000e+00 103 103 
1 8 1 1 8.000000e+02 104 104 
1 12 1 1 1.200000e+03 105 105 
1 0 1 1 0.000000e+00 106 106 
1 0 1 1 0.000000e+00 107 107 
1 16 1 1 1.600000e+03 108 108 
1 0 1 1 0.000000e+00 109 109 
1 18 1 1 1.800000e+03 110 110 
1 0 1 1 0.000000e+00 111 111 
1 14 1 1 1.400000e+03 112 112 
1 0 1 1 0.000000e+00 113 113 
1 0 1 1 0.000000e+00 114 114 
1 0 1 1 0.000000e+00 115 115 
1 0 1 1 0.000000e+00 116 116 
1 12 1 1 1.200000e+03 117 117 
1 0 1 1 0.000000e+00 118 118 
1 0 1 1 0.000000e+00 119 119 
1 21 1 1 2.100000e+03 120 120 
1 4 1 1 4.000000e+02 121 121 
1 0 1 1 0.000000e+00 122 122 
1 0 1 1 0.000000e+00 123 123 
1 0 1 1 0.000000e+00 124 124 
1 0 1 1 0.000000e+00 125 125 
1 15 1 1 1.500000e+03 126 126 
1 0 1 1 0.000000e+00 127 127 
1 0 1 1 0.000000e+00 128 128 
1 0 1 1 0.000000e+00 129 129 
1 13 1 1 1.300000e+03 130 130 
1 0 1 1 0.000000e+00 131 131 
1 12 1 1 1.200000e+03 132 132 
1 0 1 1 0.000000e+00 133 133 
1 0 1 1 0.000000e+00 134 134 
1 11 1 1 1.100000e+03 135 135 
1 0 1 1 0.000000e+00 136 136 
1 0 1 1 0.000000e+00 137 137 
1 0 1 1 0.000000e+00 138 138 
1 0 1 1 0.000000e+00 139 139 
1 13 1 1 1.300000e+03 140 140 
1 0 1 1 0.000000e+00 141 141 
1 0 1 1 0.000000e+00 142 142 
1 15 1 1 1.500000e+03 143 143 
1 10 1 1 1.000000e+03 144 144 
1 0 1 1 0.000000e+00 145 145 
1 0 1 1 0.000000e+00 146 146 
1 0 1 1 0.000000e+00 147 147 
1 0 1 1 0.000000e+00 148 148 
1 0 1 1 0.000000e+00 149 149 
1 15 1 1 1.500000e+03 150 150 
1 0 1 1 0.000000e+00 151 151 
1 0 1 1 0.000000e+00 152 152 
1 0 1 1 0.000000e+00 153 153 
1 18 1 1 1.800000e+03 154 154 
1 0 1 1 0.000000e+00 155 155 
1 12 1 1 1.200000e+03 156 156 
1 0 1 1 0.000000e+00 157 157 
1 0 1 1 0.000000e+00 158 158 
1 0 1 1 0.000000e+00 159 159 
1 0 1 1 0.000000e+00 160 160 
1 0 1 1 0.000000e+00 161 161 
1 0 1 1 0.000000e+00 162 162 
1 0 1 1 0.000000e+00 163 163 
1 0 1 1 0.000000e+00 164 164 
1 15 1 1 1.500000e+03 165 165 
1 0 1 1 0.000000e+00 166 166 
1 0 1 1 0.000000e+00 167 167 
1 7 1 1 7.000000e+02 168 168 
1 3 1 1 3.000000e+02 169 169 
1 0 1 1 0.000000e+00 170 170 
1 0 1 1 0.000000e+00 171 171 
1 0 1 1 0.000000e+00 172 172 
1 0 1 1 0.000000e+00 173 173 
1 0 1 1 0.000000e+00 174 174 
1 0 1 1 0.000000e+00 175 175 
1 0 1 1 0.000000e+00 176 176 
1 0 1 1 0.000000e+00 177 177 
1 0 1 1 0.000000e+00 178 178 
1 0 1 1 0.000000e+00 179 179 
1 9 1 1 9.000000e+02 180 180 
1 0 1 1 0.000000e+00 181 181 
1 11 1 1 1.100000e+03 182 182 
1 0 1 1 0.000000e+00 183 183 
1 0 1 1 0.000000e+00 184 184 
1 0 1 1 0.000000e+00 185 185 
1 0 1 1 0.000000e+00 186 186 
1 0 1 1 0.000000e+00 187 187 
1 0 1 1 0.000000e+00 188 188 
1 0 1 1 0.000000e+00 189 189 
1 0 1 1 0.000000e+00 190 190 
1 0 1 1 0.000000e+00 191 191 
1 0 1 1 0.000000e+00 192 192 
1 0 1 1 0.000000e+00 193 193 
1 0 1 1 0.000000e+00 194 194 
1 12 1 1 1.200000e+03 195 195 
1 9 1 1 9.000000e+02 196 196 
1 0 1 1 0.000000e+00 197 197 
1 0 1 1 0.000000e+00 198 198 
1 0 1 1 0.000000e+00 199 199 
1 0 1 1 0.000000e+00 200 200 
1 0 1 1 0.000000e+00 201 201 
1 0 1 1 0.000000e+00 202 202 
1 0 1 1 0.000000e+00 203 203 
1 0 1 1 0.000000e+00 204 204 
1 0 1 1 0.000000e+00 205 205 
1 0 1 1 0.000000e+00 206 206 
1 0 1 1 0.000000e+00 207 207 
1 0 1 1 0.000000e+00 208 208 
1 0 1 1 0.000000e+00 209 209 
1 15 1 1 1.500000e+03 210 210 
1 0 1 1 0.000000e+00 211 211 
1 0 1 1 0.000000e+00 212 212 
1 0 1 1 0.000000e+00 213 213 
1 0 1 1 0.000000e+00 214 214 
1 0 1 1 0.000000e+00 215 215 
1 0 1 1 0.000000e+00 216 216 
1 0 1 1 0.000000e+00 217 217 
1 0 1 1 0.000000e+00 218 218 
1 0 1 1 0.000000e+00 219 219 
1 0 1 1 0.000000e+00 220 220 
1 0 1 1 0.000000e+00 221 221 
1 0 1 1 0.000000e+00 222 222 
1 0 1 1 0.000000e+00 223 223 
1 0 1 1 0.000000e+00 224 224 
1 7 1 1 7.000000e+02 225 225 
</gnuplot>

==== Распределение покрытия CovCrossAB (3D) ====
{|
!<gnuplot>
#set yrange [80:120]
#set logscale y
#set xrange [-0.5:225.5]
set style fill solid 0.5 border
#set style histogram cluster gap 1
set boxwidth 0.8
splot  '-' using 8:6:2 t 'CovCrossAB' with boxes lt 2 lw 1
# 2 256 
1 11 1 1 1.100000e+03 0 0 0 0 
1 8 1 1 8.000000e+02 0 0 1 1 
1 3 1 1 3.000000e+02 0 0 2 2 
1 5 1 1 5.000000e+02 0 0 3 3 
1 4 1 1 4.000000e+02 0 0 4 4 
1 8 1 1 8.000000e+02 0 0 5 5 
1 6 1 1 6.000000e+02 0 0 6 6 
1 4 1 1 4.000000e+02 0 0 7 7 
1 5 1 1 5.000000e+02 0 0 8 8 
1 2 1 1 2.000000e+02 0 0 9 9 
1 3 1 1 3.000000e+02 0 0 10 10 
1 5 1 1 5.000000e+02 0 0 11 11 
1 7 1 1 7.000000e+02 0 0 12 12 
1 13 1 1 1.300000e+03 0 0 13 13 
1 7 1 1 7.000000e+02 0 0 14 14 
1 5 1 1 5.000000e+02 0 0 15 15 
1 7 1 1 7.000000e+02 1 1 0 0 
1 11 1 1 1.100000e+03 1 1 1 1 
1 8 1 1 8.000000e+02 1 1 2 2 
1 9 1 1 9.000000e+02 1 1 3 3 
1 8 1 1 8.000000e+02 1 1 4 4 
1 5 1 1 5.000000e+02 1 1 5 5 
1 3 1 1 3.000000e+02 1 1 6 6 
1 11 1 1 1.100000e+03 1 1 7 7 
1 8 1 1 8.000000e+02 1 1 8 8 
1 7 1 1 7.000000e+02 1 1 9 9 
1 3 1 1 3.000000e+02 1 1 10 10 
1 3 1 1 3.000000e+02 1 1 11 11 
1 5 1 1 5.000000e+02 1 1 12 12 
1 8 1 1 8.000000e+02 1 1 13 13 
1 8 1 1 8.000000e+02 1 1 14 14 
1 6 1 1 6.000000e+02 1 1 15 15 
1 9 1 1 9.000000e+02 2 2 0 0 
1 7 1 1 7.000000e+02 2 2 1 1 
1 5 1 1 5.000000e+02 2 2 2 2 
1 6 1 1 6.000000e+02 2 2 3 3 
1 7 1 1 7.000000e+02 2 2 4 4 
1 2 1 1 2.000000e+02 2 2 5 5 
1 4 1 1 4.000000e+02 2 2 6 6 
1 9 1 1 9.000000e+02 2 2 7 7 
1 6 1 1 6.000000e+02 2 2 8 8 
1 8 1 1 8.000000e+02 2 2 9 9 
1 8 1 1 8.000000e+02 2 2 10 10 
1 6 1 1 6.000000e+02 2 2 11 11 
1 9 1 1 9.000000e+02 2 2 12 12 
1 6 1 1 6.000000e+02 2 2 13 13 
1 6 1 1 6.000000e+02 2 2 14 14 
1 6 1 1 6.000000e+02 2 2 15 15 
1 6 1 1 6.000000e+02 3 3 0 0 
1 5 1 1 5.000000e+02 3 3 1 1 
1 7 1 1 7.000000e+02 3 3 2 2 
1 10 1 1 1.000000e+03 3 3 3 3 
1 6 1 1 6.000000e+02 3 3 4 4 
1 10 1 1 1.000000e+03 3 3 5 5 
1 5 1 1 5.000000e+02 3 3 6 6 
1 9 1 1 9.000000e+02 3 3 7 7 
1 11 1 1 1.100000e+03 3 3 8 8 
1 3 1 1 3.000000e+02 3 3 9 9 
1 8 1 1 8.000000e+02 3 3 10 10 
1 10 1 1 1.000000e+03 3 3 11 11 
1 8 1 1 8.000000e+02 3 3 12 12 
1 9 1 1 9.000000e+02 3 3 13 13 
1 3 1 1 3.000000e+02 3 3 14 14 
1 7 1 1 7.000000e+02 3 3 15 15 
1 5 1 1 5.000000e+02 4 4 0 0 
1 8 1 1 8.000000e+02 4 4 1 1 
1 4 1 1 4.000000e+02 4 4 2 2 
1 6 1 1 6.000000e+02 4 4 3 3 
1 8 1 1 8.000000e+02 4 4 4 4 
1 10 1 1 1.000000e+03 4 4 5 5 
1 9 1 1 9.000000e+02 4 4 6 6 
1 7 1 1 7.000000e+02 4 4 7 7 
1 6 1 1 6.000000e+02 4 4 8 8 
1 4 1 1 4.000000e+02 4 4 9 9 
1 5 1 1 5.000000e+02 4 4 10 10 
1 8 1 1 8.000000e+02 4 4 11 11 
1 8 1 1 8.000000e+02 4 4 12 12 
1 7 1 1 7.000000e+02 4 4 13 13 
1 9 1 1 9.000000e+02 4 4 14 14 
1 6 1 1 6.000000e+02 4 4 15 15 
1 3 1 1 3.000000e+02 5 5 0 0 
1 1 1 1 1.000000e+02 5 5 1 1 
1 4 1 1 4.000000e+02 5 5 2 2 
1 9 1 1 9.000000e+02 5 5 3 3 
1 8 1 1 8.000000e+02 5 5 4 4 
1 7 1 1 7.000000e+02 5 5 5 5 
1 4 1 1 4.000000e+02 5 5 6 6 
1 6 1 1 6.000000e+02 5 5 7 7 
1 5 1 1 5.000000e+02 5 5 8 8 
1 7 1 1 7.000000e+02 5 5 9 9 
1 10 1 1 1.000000e+03 5 5 10 10 
1 3 1 1 3.000000e+02 5 5 11 11 
1 2 1 1 2.000000e+02 5 5 12 12 
1 10 1 1 1.000000e+03 5 5 13 13 
1 7 1 1 7.000000e+02 5 5 14 14 
1 7 1 1 7.000000e+02 5 5 15 15 
1 9 1 1 9.000000e+02 6 6 0 0 
1 7 1 1 7.000000e+02 6 6 1 1 
1 3 1 1 3.000000e+02 6 6 2 2 
1 6 1 1 6.000000e+02 6 6 3 3 
1 10 1 1 1.000000e+03 6 6 4 4 
1 6 1 1 6.000000e+02 6 6 5 5 
1 4 1 1 4.000000e+02 6 6 6 6 
1 4 1 1 4.000000e+02 6 6 7 7 
1 7 1 1 7.000000e+02 6 6 8 8 
1 3 1 1 3.000000e+02 6 6 9 9 
1 3 1 1 3.000000e+02 6 6 10 10 
1 9 1 1 9.000000e+02 6 6 11 11 
1 6 1 1 6.000000e+02 6 6 12 12 
1 10 1 1 1.000000e+03 6 6 13 13 
1 7 1 1 7.000000e+02 6 6 14 14 
1 2 1 1 2.000000e+02 6 6 15 15 
1 5 1 1 5.000000e+02 7 7 0 0 
1 10 1 1 1.000000e+03 7 7 1 1 
1 2 1 1 2.000000e+02 7 7 2 2 
1 5 1 1 5.000000e+02 7 7 3 3 
1 3 1 1 3.000000e+02 7 7 4 4 
1 2 1 1 2.000000e+02 7 7 5 5 
1 9 1 1 9.000000e+02 7 7 6 6 
1 10 1 1 1.000000e+03 7 7 7 7 
1 6 1 1 6.000000e+02 7 7 8 8 
1 7 1 1 7.000000e+02 7 7 9 9 
1 9 1 1 9.000000e+02 7 7 10 10 
1 3 1 1 3.000000e+02 7 7 11 11 
1 5 1 1 5.000000e+02 7 7 12 12 
1 8 1 1 8.000000e+02 7 7 13 13 
1 2 1 1 2.000000e+02 7 7 14 14 
1 4 1 1 4.000000e+02 7 7 15 15 
1 6 1 1 6.000000e+02 8 8 0 0 
1 6 1 1 6.000000e+02 8 8 1 1 
1 7 1 1 7.000000e+02 8 8 2 2 
1 9 1 1 9.000000e+02 8 8 3 3 
1 5 1 1 5.000000e+02 8 8 4 4 
1 6 1 1 6.000000e+02 8 8 5 5 
1 8 1 1 8.000000e+02 8 8 6 6 
1 6 1 1 6.000000e+02 8 8 7 7 
1 2 1 1 2.000000e+02 8 8 8 8 
1 4 1 1 4.000000e+02 8 8 9 9 
1 6 1 1 6.000000e+02 8 8 10 10 
1 8 1 1 8.000000e+02 8 8 11 11 
1 10 1 1 1.000000e+03 8 8 12 12 
1 4 1 1 4.000000e+02 8 8 13 13 
1 6 1 1 6.000000e+02 8 8 14 14 
1 7 1 1 7.000000e+02 8 8 15 15 
1 5 1 1 5.000000e+02 9 9 0 0 
1 10 1 1 1.000000e+03 9 9 1 1 
1 4 1 1 4.000000e+02 9 9 2 2 
1 7 1 1 7.000000e+02 9 9 3 3 
1 8 1 1 8.000000e+02 9 9 4 4 
1 8 1 1 8.000000e+02 9 9 5 5 
1 7 1 1 7.000000e+02 9 9 6 6 
1 6 1 1 6.000000e+02 9 9 7 7 
1 12 1 1 1.200000e+03 9 9 8 8 
1 6 1 1 6.000000e+02 9 9 9 9 
1 3 1 1 3.000000e+02 9 9 10 10 
1 5 1 1 5.000000e+02 9 9 11 11 
1 7 1 1 7.000000e+02 9 9 12 12 
1 4 1 1 4.000000e+02 9 9 13 13 
1 13 1 1 1.300000e+03 9 9 14 14 
1 7 1 1 7.000000e+02 9 9 15 15 
1 6 1 1 6.000000e+02 10 10 0 0 
1 7 1 1 7.000000e+02 10 10 1 1 
1 5 1 1 5.000000e+02 10 10 2 2 
1 6 1 1 6.000000e+02 10 10 3 3 
1 10 1 1 1.000000e+03 10 10 4 4 
1 7 1 1 7.000000e+02 10 10 5 5 
1 5 1 1 5.000000e+02 10 10 6 6 
1 5 1 1 5.000000e+02 10 10 7 7 
1 14 1 1 1.400000e+03 10 10 8 8 
1 2 1 1 2.000000e+02 10 10 9 9 
1 6 1 1 6.000000e+02 10 10 10 10 
1 10 1 1 1.000000e+03 10 10 11 11 
1 3 1 1 3.000000e+02 10 10 12 12 
1 5 1 1 5.000000e+02 10 10 13 13 
1 6 1 1 6.000000e+02 10 10 14 14 
1 8 1 1 8.000000e+02 10 10 15 15 
1 3 1 1 3.000000e+02 11 11 0 0 
1 8 1 1 8.000000e+02 11 11 1 1 
1 3 1 1 3.000000e+02 11 11 2 2 
1 5 1 1 5.000000e+02 11 11 3 3 
1 2 1 1 2.000000e+02 11 11 4 4 
1 9 1 1 9.000000e+02 11 11 5 5 
1 6 1 1 6.000000e+02 11 11 6 6 
1 5 1 1 5.000000e+02 11 11 7 7 
1 6 1 1 6.000000e+02 11 11 8 8 
1 2 1 1 2.000000e+02 11 11 9 9 
1 8 1 1 8.000000e+02 11 11 10 10 
1 4 1 1 4.000000e+02 11 11 11 11 
1 3 1 1 3.000000e+02 11 11 12 12 
1 6 1 1 6.000000e+02 11 11 13 13 
1 11 1 1 1.100000e+03 11 11 14 14 
1 12 1 1 1.200000e+03 11 11 15 15 
1 10 1 1 1.000000e+03 12 12 0 0 
1 3 1 1 3.000000e+02 12 12 1 1 
1 6 1 1 6.000000e+02 12 12 2 2 
1 4 1 1 4.000000e+02 12 12 3 3 
1 4 1 1 4.000000e+02 12 12 4 4 
1 7 1 1 7.000000e+02 12 12 5 5 
1 6 1 1 6.000000e+02 12 12 6 6 
1 6 1 1 6.000000e+02 12 12 7 7 
1 2 1 1 2.000000e+02 12 12 8 8 
1 9 1 1 9.000000e+02 12 12 9 9 
1 6 1 1 6.000000e+02 12 12 10 10 
1 9 1 1 9.000000e+02 12 12 11 11 
1 10 1 1 1.000000e+03 12 12 12 12 
1 7 1 1 7.000000e+02 12 12 13 13 
1 4 1 1 4.000000e+02 12 12 14 14 
1 5 1 1 5.000000e+02 12 12 15 15 
1 8 1 1 8.000000e+02 13 13 0 0 
1 9 1 1 9.000000e+02 13 13 1 1 
1 5 1 1 5.000000e+02 13 13 2 2 
1 6 1 1 6.000000e+02 13 13 3 3 
1 4 1 1 4.000000e+02 13 13 4 4 
1 6 1 1 6.000000e+02 13 13 5 5 
1 8 1 1 8.000000e+02 13 13 6 6 
1 10 1 1 1.000000e+03 13 13 7 7 
1 4 1 1 4.000000e+02 13 13 8 8 
1 8 1 1 8.000000e+02 13 13 9 9 
1 8 1 1 8.000000e+02 13 13 10 10 
1 9 1 1 9.000000e+02 13 13 11 11 
1 5 1 1 5.000000e+02 13 13 12 12 
1 3 1 1 3.000000e+02 13 13 13 13 
1 7 1 1 7.000000e+02 13 13 14 14 
1 4 1 1 4.000000e+02 13 13 15 15 
1 6 1 1 6.000000e+02 14 14 0 0 
1 7 1 1 7.000000e+02 14 14 1 1 
1 7 1 1 7.000000e+02 14 14 2 2 
1 5 1 1 5.000000e+02 14 14 3 3 
1 8 1 1 8.000000e+02 14 14 4 4 
1 5 1 1 5.000000e+02 14 14 5 5 
1 8 1 1 8.000000e+02 14 14 6 6 
1 5 1 1 5.000000e+02 14 14 7 7 
1 8 1 1 8.000000e+02 14 14 8 8 
1 2 1 1 2.000000e+02 14 14 9 9 
1 7 1 1 7.000000e+02 14 14 10 10 
1 7 1 1 7.000000e+02 14 14 11 11 
1 3 1 1 3.000000e+02 14 14 12 12 
1 4 1 1 4.000000e+02 14 14 13 13 
1 9 1 1 9.000000e+02 14 14 14 14 
1 4 1 1 4.000000e+02 14 14 15 15 
1 8 1 1 8.000000e+02 15 15 0 0 
1 7 1 1 7.000000e+02 15 15 1 1 
1 6 1 1 6.000000e+02 15 15 2 2 
1 6 1 1 6.000000e+02 15 15 3 3 
1 1 1 1 1.000000e+02 15 15 4 4 
1 1 1 1 1.000000e+02 15 15 5 5 
1 6 1 1 6.000000e+02 15 15 6 6 
1 8 1 1 8.000000e+02 15 15 7 7 
1 5 1 1 5.000000e+02 15 15 8 8 
1 4 1 1 4.000000e+02 15 15 9 9 
1 7 1 1 7.000000e+02 15 15 10 10 
1 3 1 1 3.000000e+02 15 15 11 11 
1 4 1 1 4.000000e+02 15 15 12 12 
1 8 1 1 8.000000e+02 15 15 13 13 
1 11 1 1 1.100000e+03 15 15 14 14 
1 7 1 1 7.000000e+02 15 15 15 15 
</gnuplot>

!
<gnuplot>
#set yrange [80:120]
#set logscale y
#set xrange [-0.5:225.5]
#set style fill solid 0.5 border
#set style histogram cluster gap 1
#set boxwidth 0.8
set grid
set hidden3d
#splot  '-' using 8:6:2 t 'CovCrossAB' with boxes lt 2 lw 1
splot  '-' using 8:6:2 t 'CovCrossAB' w l
# 2 256 
1 11 1 1 1.100000e+03 0 0 0 0 
1 8 1 1 8.000000e+02 0 0 1 1 
1 3 1 1 3.000000e+02 0 0 2 2 
1 5 1 1 5.000000e+02 0 0 3 3 
1 4 1 1 4.000000e+02 0 0 4 4 
1 8 1 1 8.000000e+02 0 0 5 5 
1 6 1 1 6.000000e+02 0 0 6 6 
1 4 1 1 4.000000e+02 0 0 7 7 
1 5 1 1 5.000000e+02 0 0 8 8 
1 2 1 1 2.000000e+02 0 0 9 9 
1 3 1 1 3.000000e+02 0 0 10 10 
1 5 1 1 5.000000e+02 0 0 11 11 
1 7 1 1 7.000000e+02 0 0 12 12 
1 13 1 1 1.300000e+03 0 0 13 13 
1 7 1 1 7.000000e+02 0 0 14 14 
1 5 1 1 5.000000e+02 0 0 15 15 

1 7 1 1 7.000000e+02 1 1 0 0 
1 11 1 1 1.100000e+03 1 1 1 1 
1 8 1 1 8.000000e+02 1 1 2 2 
1 9 1 1 9.000000e+02 1 1 3 3 
1 8 1 1 8.000000e+02 1 1 4 4 
1 5 1 1 5.000000e+02 1 1 5 5 
1 3 1 1 3.000000e+02 1 1 6 6 
1 11 1 1 1.100000e+03 1 1 7 7 
1 8 1 1 8.000000e+02 1 1 8 8 
1 7 1 1 7.000000e+02 1 1 9 9 
1 3 1 1 3.000000e+02 1 1 10 10 
1 3 1 1 3.000000e+02 1 1 11 11 
1 5 1 1 5.000000e+02 1 1 12 12 
1 8 1 1 8.000000e+02 1 1 13 13 
1 8 1 1 8.000000e+02 1 1 14 14 
1 6 1 1 6.000000e+02 1 1 15 15 

1 9 1 1 9.000000e+02 2 2 0 0 
1 7 1 1 7.000000e+02 2 2 1 1 
1 5 1 1 5.000000e+02 2 2 2 2 
1 6 1 1 6.000000e+02 2 2 3 3 
1 7 1 1 7.000000e+02 2 2 4 4 
1 2 1 1 2.000000e+02 2 2 5 5 
1 4 1 1 4.000000e+02 2 2 6 6 
1 9 1 1 9.000000e+02 2 2 7 7 
1 6 1 1 6.000000e+02 2 2 8 8 
1 8 1 1 8.000000e+02 2 2 9 9 
1 8 1 1 8.000000e+02 2 2 10 10 
1 6 1 1 6.000000e+02 2 2 11 11 
1 9 1 1 9.000000e+02 2 2 12 12 
1 6 1 1 6.000000e+02 2 2 13 13 
1 6 1 1 6.000000e+02 2 2 14 14 
1 6 1 1 6.000000e+02 2 2 15 15 

1 6 1 1 6.000000e+02 3 3 0 0 
1 5 1 1 5.000000e+02 3 3 1 1 
1 7 1 1 7.000000e+02 3 3 2 2 
1 10 1 1 1.000000e+03 3 3 3 3 
1 6 1 1 6.000000e+02 3 3 4 4 
1 10 1 1 1.000000e+03 3 3 5 5 
1 5 1 1 5.000000e+02 3 3 6 6 
1 9 1 1 9.000000e+02 3 3 7 7 
1 11 1 1 1.100000e+03 3 3 8 8 
1 3 1 1 3.000000e+02 3 3 9 9 
1 8 1 1 8.000000e+02 3 3 10 10 
1 10 1 1 1.000000e+03 3 3 11 11 
1 8 1 1 8.000000e+02 3 3 12 12 
1 9 1 1 9.000000e+02 3 3 13 13 
1 3 1 1 3.000000e+02 3 3 14 14 
1 7 1 1 7.000000e+02 3 3 15 15 

1 5 1 1 5.000000e+02 4 4 0 0 
1 8 1 1 8.000000e+02 4 4 1 1 
1 4 1 1 4.000000e+02 4 4 2 2 
1 6 1 1 6.000000e+02 4 4 3 3 
1 8 1 1 8.000000e+02 4 4 4 4 
1 10 1 1 1.000000e+03 4 4 5 5 
1 9 1 1 9.000000e+02 4 4 6 6 
1 7 1 1 7.000000e+02 4 4 7 7 
1 6 1 1 6.000000e+02 4 4 8 8 
1 4 1 1 4.000000e+02 4 4 9 9 
1 5 1 1 5.000000e+02 4 4 10 10 
1 8 1 1 8.000000e+02 4 4 11 11 
1 8 1 1 8.000000e+02 4 4 12 12 
1 7 1 1 7.000000e+02 4 4 13 13 
1 9 1 1 9.000000e+02 4 4 14 14 
1 6 1 1 6.000000e+02 4 4 15 15 

1 3 1 1 3.000000e+02 5 5 0 0 
1 1 1 1 1.000000e+02 5 5 1 1 
1 4 1 1 4.000000e+02 5 5 2 2 
1 9 1 1 9.000000e+02 5 5 3 3 
1 8 1 1 8.000000e+02 5 5 4 4 
1 7 1 1 7.000000e+02 5 5 5 5 
1 4 1 1 4.000000e+02 5 5 6 6 
1 6 1 1 6.000000e+02 5 5 7 7 
1 5 1 1 5.000000e+02 5 5 8 8 
1 7 1 1 7.000000e+02 5 5 9 9 
1 10 1 1 1.000000e+03 5 5 10 10 
1 3 1 1 3.000000e+02 5 5 11 11 
1 2 1 1 2.000000e+02 5 5 12 12 
1 10 1 1 1.000000e+03 5 5 13 13 
1 7 1 1 7.000000e+02 5 5 14 14 
1 7 1 1 7.000000e+02 5 5 15 15 

1 9 1 1 9.000000e+02 6 6 0 0 
1 7 1 1 7.000000e+02 6 6 1 1 
1 3 1 1 3.000000e+02 6 6 2 2 
1 6 1 1 6.000000e+02 6 6 3 3 
1 10 1 1 1.000000e+03 6 6 4 4 
1 6 1 1 6.000000e+02 6 6 5 5 
1 4 1 1 4.000000e+02 6 6 6 6 
1 4 1 1 4.000000e+02 6 6 7 7 
1 7 1 1 7.000000e+02 6 6 8 8 
1 3 1 1 3.000000e+02 6 6 9 9 
1 3 1 1 3.000000e+02 6 6 10 10 
1 9 1 1 9.000000e+02 6 6 11 11 
1 6 1 1 6.000000e+02 6 6 12 12 
1 10 1 1 1.000000e+03 6 6 13 13 
1 7 1 1 7.000000e+02 6 6 14 14 
1 2 1 1 2.000000e+02 6 6 15 15 

1 5 1 1 5.000000e+02 7 7 0 0 
1 10 1 1 1.000000e+03 7 7 1 1 
1 2 1 1 2.000000e+02 7 7 2 2 
1 5 1 1 5.000000e+02 7 7 3 3 
1 3 1 1 3.000000e+02 7 7 4 4 
1 2 1 1 2.000000e+02 7 7 5 5 
1 9 1 1 9.000000e+02 7 7 6 6 
1 10 1 1 1.000000e+03 7 7 7 7 
1 6 1 1 6.000000e+02 7 7 8 8 
1 7 1 1 7.000000e+02 7 7 9 9 
1 9 1 1 9.000000e+02 7 7 10 10 
1 3 1 1 3.000000e+02 7 7 11 11 
1 5 1 1 5.000000e+02 7 7 12 12 
1 8 1 1 8.000000e+02 7 7 13 13 
1 2 1 1 2.000000e+02 7 7 14 14 
1 4 1 1 4.000000e+02 7 7 15 15 

1 6 1 1 6.000000e+02 8 8 0 0 
1 6 1 1 6.000000e+02 8 8 1 1 
1 7 1 1 7.000000e+02 8 8 2 2 
1 9 1 1 9.000000e+02 8 8 3 3 
1 5 1 1 5.000000e+02 8 8 4 4 
1 6 1 1 6.000000e+02 8 8 5 5 
1 8 1 1 8.000000e+02 8 8 6 6 
1 6 1 1 6.000000e+02 8 8 7 7 
1 2 1 1 2.000000e+02 8 8 8 8 
1 4 1 1 4.000000e+02 8 8 9 9 
1 6 1 1 6.000000e+02 8 8 10 10 
1 8 1 1 8.000000e+02 8 8 11 11 
1 10 1 1 1.000000e+03 8 8 12 12 
1 4 1 1 4.000000e+02 8 8 13 13 
1 6 1 1 6.000000e+02 8 8 14 14 
1 7 1 1 7.000000e+02 8 8 15 15 

1 5 1 1 5.000000e+02 9 9 0 0 
1 10 1 1 1.000000e+03 9 9 1 1 
1 4 1 1 4.000000e+02 9 9 2 2 
1 7 1 1 7.000000e+02 9 9 3 3 
1 8 1 1 8.000000e+02 9 9 4 4 
1 8 1 1 8.000000e+02 9 9 5 5 
1 7 1 1 7.000000e+02 9 9 6 6 
1 6 1 1 6.000000e+02 9 9 7 7 
1 12 1 1 1.200000e+03 9 9 8 8 
1 6 1 1 6.000000e+02 9 9 9 9 
1 3 1 1 3.000000e+02 9 9 10 10 
1 5 1 1 5.000000e+02 9 9 11 11 
1 7 1 1 7.000000e+02 9 9 12 12 
1 4 1 1 4.000000e+02 9 9 13 13 
1 13 1 1 1.300000e+03 9 9 14 14 
1 7 1 1 7.000000e+02 9 9 15 15 

1 6 1 1 6.000000e+02 10 10 0 0 
1 7 1 1 7.000000e+02 10 10 1 1 
1 5 1 1 5.000000e+02 10 10 2 2 
1 6 1 1 6.000000e+02 10 10 3 3 
1 10 1 1 1.000000e+03 10 10 4 4 
1 7 1 1 7.000000e+02 10 10 5 5 
1 5 1 1 5.000000e+02 10 10 6 6 
1 5 1 1 5.000000e+02 10 10 7 7 
1 14 1 1 1.400000e+03 10 10 8 8 
1 2 1 1 2.000000e+02 10 10 9 9 
1 6 1 1 6.000000e+02 10 10 10 10 
1 10 1 1 1.000000e+03 10 10 11 11 
1 3 1 1 3.000000e+02 10 10 12 12 
1 5 1 1 5.000000e+02 10 10 13 13 
1 6 1 1 6.000000e+02 10 10 14 14 
1 8 1 1 8.000000e+02 10 10 15 15 

1 3 1 1 3.000000e+02 11 11 0 0 
1 8 1 1 8.000000e+02 11 11 1 1 
1 3 1 1 3.000000e+02 11 11 2 2 
1 5 1 1 5.000000e+02 11 11 3 3 
1 2 1 1 2.000000e+02 11 11 4 4 
1 9 1 1 9.000000e+02 11 11 5 5 
1 6 1 1 6.000000e+02 11 11 6 6 
1 5 1 1 5.000000e+02 11 11 7 7 
1 6 1 1 6.000000e+02 11 11 8 8 
1 2 1 1 2.000000e+02 11 11 9 9 
1 8 1 1 8.000000e+02 11 11 10 10 
1 4 1 1 4.000000e+02 11 11 11 11 
1 3 1 1 3.000000e+02 11 11 12 12 
1 6 1 1 6.000000e+02 11 11 13 13 
1 11 1 1 1.100000e+03 11 11 14 14 
1 12 1 1 1.200000e+03 11 11 15 15 

1 10 1 1 1.000000e+03 12 12 0 0 
1 3 1 1 3.000000e+02 12 12 1 1 
1 6 1 1 6.000000e+02 12 12 2 2 
1 4 1 1 4.000000e+02 12 12 3 3 
1 4 1 1 4.000000e+02 12 12 4 4 
1 7 1 1 7.000000e+02 12 12 5 5 
1 6 1 1 6.000000e+02 12 12 6 6 
1 6 1 1 6.000000e+02 12 12 7 7 
1 2 1 1 2.000000e+02 12 12 8 8 
1 9 1 1 9.000000e+02 12 12 9 9 
1 6 1 1 6.000000e+02 12 12 10 10 
1 9 1 1 9.000000e+02 12 12 11 11 
1 10 1 1 1.000000e+03 12 12 12 12 
1 7 1 1 7.000000e+02 12 12 13 13 
1 4 1 1 4.000000e+02 12 12 14 14 
1 5 1 1 5.000000e+02 12 12 15 15 

1 8 1 1 8.000000e+02 13 13 0 0 
1 9 1 1 9.000000e+02 13 13 1 1 
1 5 1 1 5.000000e+02 13 13 2 2 
1 6 1 1 6.000000e+02 13 13 3 3 
1 4 1 1 4.000000e+02 13 13 4 4 
1 6 1 1 6.000000e+02 13 13 5 5 
1 8 1 1 8.000000e+02 13 13 6 6 
1 10 1 1 1.000000e+03 13 13 7 7 
1 4 1 1 4.000000e+02 13 13 8 8 
1 8 1 1 8.000000e+02 13 13 9 9 
1 8 1 1 8.000000e+02 13 13 10 10 
1 9 1 1 9.000000e+02 13 13 11 11 
1 5 1 1 5.000000e+02 13 13 12 12 
1 3 1 1 3.000000e+02 13 13 13 13 
1 7 1 1 7.000000e+02 13 13 14 14 
1 4 1 1 4.000000e+02 13 13 15 15 

1 6 1 1 6.000000e+02 14 14 0 0 
1 7 1 1 7.000000e+02 14 14 1 1 
1 7 1 1 7.000000e+02 14 14 2 2 
1 5 1 1 5.000000e+02 14 14 3 3 
1 8 1 1 8.000000e+02 14 14 4 4 
1 5 1 1 5.000000e+02 14 14 5 5 
1 8 1 1 8.000000e+02 14 14 6 6 
1 5 1 1 5.000000e+02 14 14 7 7 
1 8 1 1 8.000000e+02 14 14 8 8 
1 2 1 1 2.000000e+02 14 14 9 9 
1 7 1 1 7.000000e+02 14 14 10 10 
1 7 1 1 7.000000e+02 14 14 11 11 
1 3 1 1 3.000000e+02 14 14 12 12 
1 4 1 1 4.000000e+02 14 14 13 13 
1 9 1 1 9.000000e+02 14 14 14 14 
1 4 1 1 4.000000e+02 14 14 15 15 

1 8 1 1 8.000000e+02 15 15 0 0 
1 7 1 1 7.000000e+02 15 15 1 1 
1 6 1 1 6.000000e+02 15 15 2 2 
1 6 1 1 6.000000e+02 15 15 3 3 
1 1 1 1 1.000000e+02 15 15 4 4 
1 1 1 1 1.000000e+02 15 15 5 5 
1 6 1 1 6.000000e+02 15 15 6 6 
1 8 1 1 8.000000e+02 15 15 7 7 
1 5 1 1 5.000000e+02 15 15 8 8 
1 4 1 1 4.000000e+02 15 15 9 9 
1 7 1 1 7.000000e+02 15 15 10 10 
1 3 1 1 3.000000e+02 15 15 11 11 
1 4 1 1 4.000000e+02 15 15 12 12 
1 8 1 1 8.000000e+02 15 15 13 13 
1 11 1 1 1.100000e+03 15 15 14 14 
1 7 1 1 7.000000e+02 15 15 15 15 
</gnuplot>
|}

== Листинги 2 ==

 -- Для покрытия всех пар состояний требуется 1615 циклов
 -- покрытие A достигается за 103 циклов
 -- покрытие B достикается за 68 циклов

{{Hider|Листинг файла testbench(tb2)}}
{{Файл|tstb_tb2.vhd|
<source lang="vhdl">
-- Для покрытия всех пар состояний требуется 1615 циклов
-- покрытие A достигается за 103 циклов
-- покрытие B достикается за 68 циклов

library ieee;
use ieee.std_logic_1164.all;
use ieee.math_real.all;
use ieee.numeric_std.all;

use work.RandomPkg.all;
use work.CoveragePkg.all;

entity testbench is
end;

architecture tb2 of testbench is

  component sxema
    port (a, b : in  std_logic_vector (4 downto 1);
          d    : out std_logic_vector (8 downto 1));
  end component;

  signal a, b : std_logic_vector (4 downto 1);
  signal d    : std_logic_vector (8 downto 1);

  shared variable RndA, RndB : RandomPType;
  shared variable CovA, CovB : CovPType;
  shared variable CovD       : CovPType;
  shared variable CovCrossAB : CovPType;

begin
  p0 : sxema
    port map (
      a => a,
      b => b,
      d => d);

  RandomGenProc1 : process
    variable SeedA1                   : positive := 7;  -- initialize seeds
    variable SeedA2                   : positive := 1;
    variable SeedB1                   : positive := 4;  -- initialize seeds
    variable SeedB2                   : positive := 2;
    variable i                        : natural  := 0;
    variable CovACovered, CovBCovered : natural  := 0;


  begin
    -- инициализация генератора псевдослучайных чисел
    RndA.InitSeed(IV => (SeedA1, SeedA2));
    RndB.InitSeed(IV => (SeedB1, SeedB2));

    -- создание корзин для a, b, d
    CovA.AddBins(GenBin(0, 15));
    CovB.AddBins(GenBin(0, 15));
    CovD.AddBins(GenBin(0, 225));
    CovCrossAB.AddCross(GenBin(0, 15), GenBin(0, 15));

    MainCovLoop : while not (CovCrossAB.IsCovered) loop

      a <= RndA.RandSlv(0, 15, 4);
      b <= RndB.RandSlv(0, 15, 4);

      wait for 10 ns;

      CovA.ICover(to_integer(unsigned(a)));
      CovB.ICover(to_integer(unsigned(b)));
      CovCrossAB.ICover((to_integer(unsigned(a)), to_integer(unsigned(b))));

      CovD.ICover(to_integer(unsigned(d)));
      i := i+1;
      if (CovA.IsCovered and CovACovered = 0) then
        CovACovered := i;
      end if;

      if (CovB.IsCovered and CovBCovered = 0) then
        CovBCovered := i;
      end if;

    end loop;

    wait for 10 ns;

    CovA.WriteBin;
    CovB.WriteBin;
    CovD.WriteBin;
    CovCrossAB.WriteBin;

    CovA.WriteCovDb ("tb2_CovA.db", OpenKind             => write_mode);
    CovB.WriteCovDb ("tb2_CovB.db", OpenKind             => write_mode);
    CovD.WriteCovDb ("tb2_CovD.db", OpenKind             => write_mode);
    CovCrossAB.WriteCovDb ("tb2_CovCrossAB.db", OpenKind => write_mode);

    wait;
  end process;

end architecture tb2;
</source>}}
{{Hider|end}}


== Листинги 3 ==

{{Hider|Листинг файла testbench(tb3)}}
{{Файл|tstb_tb3.vhd|
<source lang="vhdl">
-- Случайным образом генерит входные A и B с помощью пакета покрытия, используя перекрёстное покрытие
-- т.е. интеллектуальный тестбенч для перебора всех пар
-- Для покрытия всех пар состояний требуется 256 циклов
-- покрытие A достигается за 49 циклов
-- покрытие B достикается за 44 циклов

library ieee;
use ieee.std_logic_1164.all;
use ieee.math_real.all;
use ieee.numeric_std.all;

use work.RandomPkg.all;
use work.CoveragePkg.all;

entity testbench is
end;

architecture tb3 of testbench is

  component sxema
    port (a, b : in  std_logic_vector (4 downto 1);
          d    : out std_logic_vector (8 downto 1));
  end component;

  signal a, b : std_logic_vector (4 downto 1);
  signal d    : std_logic_vector (8 downto 1);

--  shared variable RndA, RndB : RandomPType;
  shared variable CovA, CovB, CovD : CovPType;
  shared variable CovCrossAB       : CovPType;

begin
  p0 : sxema
    port map (
      a => a,
      b => b,
      d => d);

  RandomGenProc1 : process
    variable RndA, RndB               : integer;
    variable SeedA1                   : positive := 7;  -- initialize seeds
    variable SeedA2                   : positive := 1;
    variable SeedB1                   : positive := 4;  -- initialize seeds
    variable SeedB2                   : positive := 2;
    variable i                        : natural  := 0;
    variable CovACovered, CovBCovered : natural  := 0;


  begin
    -- инициализация генератора псевдослучайных чисел
    CovCrossAB.InitSeed(CovCrossAB'instance_name);

    -- создание корзин для a, b, d
    CovA.AddBins(GenBin(0, 15));
    CovB.AddBins(GenBin(0, 15));
    CovD.AddBins(GenBin(0, 225));
    CovCrossAB.AddCross(GenBin(0, 15), GenBin(0, 15));

    MainCovLoop : while not (CovCrossAB.IsCovered) loop

      (RndA, RndB) := CovCrossAB.RandCovPoint;
      a              <= std_logic_vector(to_unsigned(RndA, 4));
      b              <= std_logic_vector(to_unsigned(RndB, 4));

      wait for 10 ns;

      CovA.ICover(to_integer(unsigned(a)));
      CovB.ICover(to_integer(unsigned(b)));
      CovCrossAB.ICover((to_integer(unsigned(a)), to_integer(unsigned(b))));

      CovD.ICover(to_integer(unsigned(d)));
      i := i+1;
      if (CovA.IsCovered and CovACovered = 0) then
        CovACovered := i;
      end if;

      if (CovB.IsCovered and CovBCovered = 0) then
        CovBCovered := i;
      end if;

    end loop;

    wait for 10 ns;

    CovA.WriteBin;
    CovB.WriteBin;
    CovD.WriteBin;
    CovCrossAB.WriteBin;

    CovA.WriteCovDb ("tb3_CovA.db", OpenKind             => write_mode);
    CovB.WriteCovDb ("tb3_CovB.db", OpenKind             => write_mode);
    CovD.WriteCovDb ("tb3_CovD.db", OpenKind             => write_mode);
    CovCrossAB.WriteCovDb ("tb3_CovCrossAB.db", OpenKind => write_mode);

    wait;
  end process;

end architecture tb3;
</source>}}
{{Hider|end}}


== Листинг 0 ==

<source lang="vhdl" line highlight="3,24-29,33-36">
library ieee;
use ieee.std_logic_1164.all;
use ieee.math_real.all;
use ieee.numeric_std.all;

entity tstb is
end;

architecture beh of tstb is

  component sxema
    port (a, b : in  std_logic_vector (4 downto 1);
          d    : out std_logic_vector (8 downto 1));
  end component;

  signal a, b : std_logic_vector (4 downto 1);
  signal d    : std_logic_vector (8 downto 1);

begin
  p0 : sxema
    port map (a => a, b => b, d => d);

  RandomGenProc1 : process
    variable RndValA, RndValB : real;           -- Random value
    variable RndA, RndB       : integer;
    variable SeedA1           : positive := 7;  -- initialize seeds
    variable SeedA2           : positive := 1;
    variable SeedB1           : positive := 4;  -- initialize seeds
    variable SeedB2           : positive := 2;
  begin

    for i in 1 to 100 loop
      uniform(SeedA1, SeedA2, RndValA);       -- randomize 0.0 to 1.0
      uniform(SeedB1, SeedB2, RndValB);       -- randomize 0.0 to 1.0
      RndA := integer(trunc(RndValA*16.0));   -- scale to 0 to 15
      RndB := integer(trunc(RndValB*16.0));   -- scale to 0 to 15

      a <= std_logic_vector(to_unsigned(RndA, 4));
      b <= std_logic_vector(to_unsigned(RndB, 4));

      wait for 10 ns;

    end loop;
    wait ;
  end process;
end;
</source>


* Листинг деклараций пакета [http://standards.ieee.org/downloads/1076/1076.2-1996/math_real.vhdl ieee.math_real] ([http://standards.ieee.org/downloads/1076/1076.2-1996/math_real-body.vhdl тело пакета])

    procedure UNIFORM(variable SEED1,SEED2:inout POSITIVE; variable X:out REAL);
        -- Purpose:
        --         Returns, in X, a pseudo-random number with uniform
        --         distribution in the open interval (0.0, 1.0).
        -- Special values:
        --         None
        -- Domain:
        --         1 <= SEED1 <= 2147483562; 1 <= SEED2 <= 2147483398
        -- Error conditions:
        --         Error if SEED1 or SEED2 outside of valid domain
        -- Range:
        --         0.0 < X < 1.0
        -- Notes:
        --         a) The semantics for this function are described by the
        --            algorithm published by Pierre L'Ecuyer in "Communications
        --            of the ACM," vol. 31, no. 6, June 1988, pp. 742-774.
        --            The algorithm is based on the combination of two
        --            multiplicative linear congruential generators for 32-bit
        --            platforms.
        --
        --         b) Before the first call to UNIFORM, the seed values
        --            (SEED1, SEED2) have to be initialized to values in the range
        --            [1, 2147483562] and [1, 2147483398] respectively.  The
        --            seed values are modified after each call to UNIFORM.
        --
        --         c) This random number generator is portable for 32-bit
        --            computers, and it has a period of ~2.30584*(10**18) for each
        --            set of seed values.
        --
        --         d) For information on spectral tests for the algorithm, refer
        --            to the L'Ecuyer article.

    function TRUNC (X : in REAL ) return REAL;
        -- Purpose:
        --         Truncates X towards 0.0 and returns truncated value
        -- Special values:
        --         TRUNC(0.0) = 0.0
        -- Domain:
        --         X in REAL
        -- Error conditions:
        --         None
        -- Range:
        --         TRUNC(X) is mathematically unbounded
        -- Notes:
        --         a) Implementations have to support at least the domain
        --                ABS(X) < REAL(INTEGER'HIGH)

== NEW ==