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diff --git a/libraries/zxing/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java b/libraries/zxing/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java
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+/*
+ * Copyright 2007 ZXing authors
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.google.zxing.common.reedsolomon;
+
+/**
+ * <p>Implements Reed-Solomon decoding, as the name implies.</p>
+ *
+ * <p>The algorithm will not be explained here, but the following references were helpful
+ * in creating this implementation:</p>
+ *
+ * <ul>
+ * <li>Bruce Maggs.
+ * <a href="http://www.cs.cmu.edu/afs/cs.cmu.edu/project/pscico-guyb/realworld/www/rs_decode.ps">
+ * "Decoding Reed-Solomon Codes"</a> (see discussion of Forney's Formula)</li>
+ * <li>J.I. Hall. <a href="www.mth.msu.edu/~jhall/classes/codenotes/GRS.pdf">
+ * "Chapter 5. Generalized Reed-Solomon Codes"</a>
+ * (see discussion of Euclidean algorithm)</li>
+ * </ul>
+ *
+ * <p>Much credit is due to William Rucklidge since portions of this code are an indirect
+ * port of his C++ Reed-Solomon implementation.</p>
+ *
+ * @author Sean Owen
+ * @author William Rucklidge
+ * @author sanfordsquires
+ */
+public final class ReedSolomonDecoder {
+
+  private final GenericGF field;
+
+  public ReedSolomonDecoder(GenericGF field) {
+    this.field = field;
+  }
+
+  /**
+   * <p>Decodes given set of received codewords, which include both data and error-correction
+   * codewords. Really, this means it uses Reed-Solomon to detect and correct errors, in-place,
+   * in the input.</p>
+   *
+   * @param received data and error-correction codewords
+   * @param twoS number of error-correction codewords available
+   * @throws ReedSolomonException if decoding fails for any reason
+   */
+  public void decode(int[] received, int twoS) throws ReedSolomonException {
+    GenericGFPoly poly = new GenericGFPoly(field, received);
+    int[] syndromeCoefficients = new int[twoS];
+    boolean dataMatrix = field.equals(GenericGF.DATA_MATRIX_FIELD_256);
+    boolean noError = true;
+    for (int i = 0; i < twoS; i++) {
+      // Thanks to sanfordsquires for this fix:
+      int eval = poly.evaluateAt(field.exp(dataMatrix ? i + 1 : i));
+      syndromeCoefficients[syndromeCoefficients.length - 1 - i] = eval;
+      if (eval != 0) {
+        noError = false;
+      }
+    }
+    if (noError) {
+      return;
+    }
+    GenericGFPoly syndrome = new GenericGFPoly(field, syndromeCoefficients);
+    GenericGFPoly[] sigmaOmega =
+        runEuclideanAlgorithm(field.buildMonomial(twoS, 1), syndrome, twoS);
+    GenericGFPoly sigma = sigmaOmega[0];
+    GenericGFPoly omega = sigmaOmega[1];
+    int[] errorLocations = findErrorLocations(sigma);
+    int[] errorMagnitudes = findErrorMagnitudes(omega, errorLocations, dataMatrix);
+    for (int i = 0; i < errorLocations.length; i++) {
+      int position = received.length - 1 - field.log(errorLocations[i]);
+      if (position < 0) {
+        throw new ReedSolomonException("Bad error location");
+      }
+      received[position] = GenericGF.addOrSubtract(received[position], errorMagnitudes[i]);
+    }
+  }
+
+  private GenericGFPoly[] runEuclideanAlgorithm(GenericGFPoly a, GenericGFPoly b, int R)
+      throws ReedSolomonException {
+    // Assume a's degree is >= b's
+    if (a.getDegree() < b.getDegree()) {
+      GenericGFPoly temp = a;
+      a = b;
+      b = temp;
+    }
+
+    GenericGFPoly rLast = a;
+    GenericGFPoly r = b;
+    GenericGFPoly sLast = field.getOne();
+    GenericGFPoly s = field.getZero();
+    GenericGFPoly tLast = field.getZero();
+    GenericGFPoly t = field.getOne();
+
+    // Run Euclidean algorithm until r's degree is less than R/2
+    while (r.getDegree() >= R / 2) {
+      GenericGFPoly rLastLast = rLast;
+      GenericGFPoly sLastLast = sLast;
+      GenericGFPoly tLastLast = tLast;
+      rLast = r;
+      sLast = s;
+      tLast = t;
+
+      // Divide rLastLast by rLast, with quotient in q and remainder in r
+      if (rLast.isZero()) {
+        // Oops, Euclidean algorithm already terminated?
+        throw new ReedSolomonException("r_{i-1} was zero");
+      }
+      r = rLastLast;
+      GenericGFPoly q = field.getZero();
+      int denominatorLeadingTerm = rLast.getCoefficient(rLast.getDegree());
+      int dltInverse = field.inverse(denominatorLeadingTerm);
+      while (r.getDegree() >= rLast.getDegree() && !r.isZero()) {
+        int degreeDiff = r.getDegree() - rLast.getDegree();
+        int scale = field.multiply(r.getCoefficient(r.getDegree()), dltInverse);
+        q = q.addOrSubtract(field.buildMonomial(degreeDiff, scale));
+        r = r.addOrSubtract(rLast.multiplyByMonomial(degreeDiff, scale));
+      }
+
+      s = q.multiply(sLast).addOrSubtract(sLastLast);
+      t = q.multiply(tLast).addOrSubtract(tLastLast);
+    }
+
+    int sigmaTildeAtZero = t.getCoefficient(0);
+    if (sigmaTildeAtZero == 0) {
+      throw new ReedSolomonException("sigmaTilde(0) was zero");
+    }
+
+    int inverse = field.inverse(sigmaTildeAtZero);
+    GenericGFPoly sigma = t.multiply(inverse);
+    GenericGFPoly omega = r.multiply(inverse);
+    return new GenericGFPoly[]{sigma, omega};
+  }
+
+  private int[] findErrorLocations(GenericGFPoly errorLocator) throws ReedSolomonException {
+    // This is a direct application of Chien's search
+    int numErrors = errorLocator.getDegree();
+    if (numErrors == 1) { // shortcut
+      return new int[] { errorLocator.getCoefficient(1) };
+    }
+    int[] result = new int[numErrors];
+    int e = 0;
+    for (int i = 1; i < field.getSize() && e < numErrors; i++) {
+      if (errorLocator.evaluateAt(i) == 0) {
+        result[e] = field.inverse(i);
+        e++;
+      }
+    }
+    if (e != numErrors) {
+      throw new ReedSolomonException("Error locator degree does not match number of roots");
+    }
+    return result;
+  }
+
+  private int[] findErrorMagnitudes(GenericGFPoly errorEvaluator, int[] errorLocations, boolean dataMatrix) {
+    // This is directly applying Forney's Formula
+    int s = errorLocations.length;
+    int[] result = new int[s];
+    for (int i = 0; i < s; i++) {
+      int xiInverse = field.inverse(errorLocations[i]);
+      int denominator = 1;
+      for (int j = 0; j < s; j++) {
+        if (i != j) {
+          //denominator = field.multiply(denominator,
+          //    GenericGF.addOrSubtract(1, field.multiply(errorLocations[j], xiInverse)));
+          // Above should work but fails on some Apple and Linux JDKs due to a Hotspot bug.
+          // Below is a funny-looking workaround from Steven Parkes
+          int term = field.multiply(errorLocations[j], xiInverse);
+          int termPlus1 = (term & 0x1) == 0 ? term | 1 : term & ~1;
+          denominator = field.multiply(denominator, termPlus1);
+        }
+      }
+      result[i] = field.multiply(errorEvaluator.evaluateAt(xiInverse),
+          field.inverse(denominator));
+      // Thanks to sanfordsquires for this fix:
+      if (dataMatrix) {
+        result[i] = field.multiply(result[i], xiInverse);
+      }
+    }
+    return result;
+  }
+
+}