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Closure Compiler is a JavaScript optimizing compiler. It parses your JavaScript, analyzes it, removes dead code and rewrites and minimizes what's left. It also checks syntax, variable references, and types, and warns about common JavaScript pitfalls. It is used in many of Google's JavaScript apps, including Gmail, Google Web Search, Google Maps, and Google Docs. This binary checks for style issues such as incorrect or missing JSDoc usage, and missing goog.require() statements. It does not do more advanced checks such as typechecking.

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/*
 * Copyright 2010 The Closure Compiler 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.javascript.jscomp;

import com.google.common.base.Function;
import com.google.common.base.Preconditions;
import com.google.javascript.jscomp.graph.LatticeElement;

import java.util.Iterator;
import java.util.List;

/**
 * Defines a way join a list of LatticeElements.
 */
interface JoinOp extends Function, L> {

  /**
   * An implementation of {@code JoinOp} that makes it easy to join to
   * lattice elements at a time.
   */
  abstract static class BinaryJoinOp
      implements JoinOp {
    @Override
    public L apply(List values) {
      Preconditions.checkArgument(!values.isEmpty());
      int size = values.size();
      if (size == 1) {
        return values.get(0);
      } else if (size == 2) {
        return apply(values.get(0), values.get(1));
      } else if (size <= 16) {
        // Do a Tree merge which request the least number of merges
        int mid = computeMidPoint(size);
        return apply(
            apply(values.subList(0, mid)),
            apply(values.subList(mid, size)));
      } else {
        // If the merge set is getting out of hand, avoid tree merges as it is
        // more memory intense. Instead, stick with linear merges that requires
        // more merges but less memory. This avoids GC trashing.
        Iterator iter = values.iterator();
        L result = iter.next(); // Never null, we have 16+ values.
        while (iter.hasNext()) {
          result = apply(result, iter.next());
        }
        return result;
      }
    }

    /**
     * Creates a new lattice that will be the join of two input lattices.
     *
     * @return The join of {@code latticeA} and {@code latticeB}.
     */
    abstract L apply(L latticeA, L latticeB);

    /**
     * Finds the midpoint of a list. The function will favor two lists of
     * even length instead of two lists of the same odd length. The list
     * must be at least length two.
     *
     * @param size Size of the list.
     */
    static int computeMidPoint(int size) {
      int midpoint = size >>> 1;
      if (size > 4) {
        /* Any list longer than 4 should prefer an even split point
         * over the true midpoint, so that [0,6] splits at 2, not 3. */
        midpoint &= -2; // (0xfffffffe) clears low bit so midpoint is even
      }
      return midpoint;
    }
  }
}