这是Oracle Java中包含的Java的java.util.Arrays.binarySearch中的代码：

/**
     * Searches the specified array of ints for the specified value using the
     * binary search algorithm.  The array must be sorted (as
     * by the {@link #sort(int[])} method) prior to making this call.  If it
     * is not sorted, the results are undefined.  If the array contains
     * multiple elements with the specified value, there is no guarantee which
     * one will be found.
     *
     * @param a the array to be searched
     * @param key the value to be searched for
     * @return index of the search key, if it is contained in the array;
     *         otherwise, <tt>(-(<i>insertion point</i>) - 1)</tt>.  The
     *         <i>insertion point</i> is defined as the point at which the
     *         key would be inserted into the array: the index of the first
     *         element greater than the key, or <tt>a.length</tt> if all
     *         elements in the array are less than the specified key.  Note
     *         that this guarantees that the return value will be &gt;= 0 if
     *         and only if the key is found.
     */
    public static int binarySearch(int[] a, int key) {
        return binarySearch0(a, 0, a.length, key);
    }

    // Like public version, but without range checks.
    private static int binarySearch0(int[] a, int fromIndex, int toIndex,
                                     int key) {
        int low = fromIndex;
        int high = toIndex - 1;

        while (low <= high) {
            int mid = (low + high) >>> 1;
            int midVal = a[mid];

            if (midVal < key)
                low = mid + 1;
            else if (midVal > key)
                high = mid - 1;
            else
                return mid; // key found
        }
        return -(low + 1);  // key not found.
    }

该算法已被证明是适当的，我喜欢这样的事实，即您可以立即从结果中知道它是一个精确匹配还是插入点的提示。
下面是我将其翻译成ruby的方法：

# Inserts the specified value into the specified array using the binary
# search algorithm. The array must be sorted prior to making this call.
# If it is not sorted, the results are undefined.  If the array contains
# multiple elements with the specified value, there is no guarantee
# which one will be found.
#
# @param [Array] array the ordered array into which value should be inserted
# @param [Object] value the value to insert
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Array] the resulting array
def self.insert(array, value, from_index=0,  to_index=array.length)
  array.insert insertion_point(array, value, from_index, to_index), value
end

# Searches the specified array for an insertion point ot the specified value
# using the binary search algorithm.  The array must be sorted prior to making
# this call. If it is not sorted, the results are undefined.  If the array
# contains multiple elements with the specified value, there is no guarantee
# which one will be found.
#
# @param [Array] array the ordered array into which value should be inserted
# @param [Object] value the value to insert
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] the position where value should be inserted
def self.insertion_point(array, value, from_index=0,  to_index=array.length)
  raise(ArgumentError, 'Invalid Range') if from_index < 0 || from_index > array.length || from_index > to_index || to_index > array.length
  binary_search = _binary_search(array, value, from_index, to_index)
  if binary_search < 0
    -(binary_search + 1)
  else
    binary_search
  end
end

# Searches the specified array for the specified value using the binary
# search algorithm.  The array must be sorted prior to making this call.
# If it is not sorted, the results are undefined.  If the array contains
# multiple elements with the specified value, there is no guarantee which
# one will be found.
#
# @param [Array] array the ordered array in which the value should be searched
# @param [Object] value the value to search for
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] if > 0 position of value, otherwise -(insertion_point + 1)
def self.binary_search(array, value, from_index=0,  to_index=array.length)
  raise(ArgumentError, 'Invalid Range') if from_index < 0 || from_index > array.length || from_index > to_index || to_index > array.length
  _binary_search(array, value, from_index, to_index)
end

private
# Like binary_search, but without range checks.
#
# @param [Array] array the ordered array in which the value should be searched
# @param [Object] value the value to search for
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] if > 0 position of value, otherwise -(insertion_point + 1)
def self._binary_search(array, value, from_index, to_index)
  low = from_index
  high = to_index - 1

  while low <= high do
    mid = (low + high) / 2
    mid_val = array[mid]

    if mid_val < value
      low = mid + 1
    elsif mid_val > value
      high = mid - 1
    else
      return mid # value found
    end
  end
  -(low + 1) # value not found.
end

代码返回的值与OP为其测试数据提供的值相同。

更新2020

其实二分法的插入问题已经有了很好的研究，有左插入点和右插入点，代码可以在Wikipedia和Rosetta Code上找到，比如要找到左插入点，代码是：

BinarySearch_Left(A[0..N-1], value) {
      low = 0
      high = N - 1
      while (low <= high) {
          // invariants: value > A[i] for all i < low
                         value <= A[i] for all i > high
          mid = (low + high) / 2
          if (A[mid] >= value)
              high = mid - 1
          else
              low = mid + 1
      }
      return low
  }

需要注意的是the overflow bug，所以mid确实应该被发现为low + floor((high - low) / 2)。

之前的答案：

实际上，使用begin_index > end_index可以更好地处理它，而不是检查begin_index >= end_index，而且解决方案要干净得多：

def binary_search_helper(arr, a, begin_index, end_index)    
  if begin_index > end_index
    return begin_index
  else
    middle_index = (begin_index + end_index) / 2
    if arr[middle_index] == a
      return middle_index
    elsif a > arr[middle_index]
      return binary_search_helper(arr, a, middle_index + 1, end_index)
    else
      return binary_search_helper(arr, a, begin_index, middle_index - 1)
    end
  end
end

# for [1,3,5,7,9], searching for 6 will return index for 7 for insertion
# if exact match is found, then return that index
def binary_search(arr, a)
  return binary_search_helper(arr, a, 0, arr.length - 1)
end

而且使用迭代代替递归可能更快，也更少担心堆栈溢出。

左侧插入样品：

def binary_search(arr, target):
    left = 0
    right = len(arr) - 1
    while left <= right:
        mid = (left + right) >> 1
        if arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return left

右侧插入样品：

def binary_search(arr, target):
    left = 0
    right = len(arr) - 1
    while left <= right:
        mid = (left + right) >> 1
        if arr[mid] <= target:
            left = mid + 1
        else:
            right = mid - 1

return left # add - 1 for right most index of target

样品存在：

def binary_search(arr, target):
    left = 0
    right = len(arr) - 1
    while left <= right:
        mid = (left + right) >> 1
        if n < target:
            left = mid + 1
        elif n > target:
            right = mid - 1
        else:
            return True # or return mid for index

return False # or return -1 for not found

样本测试用例：arr = [1、2、3、4、5、5、5、5、5、6、7、8、9、10]
结果=二进制搜索（arr，5）