Median of Medians Java implementation, kth element in array

Median of Median algorithm implementation in Java. It also provides Kth element in array after sorting. This algorithm runs in O(n) time.

Please leave comments below for more questions and remarks.

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;

public class Solution {
 public static void main(String[] args) {
  Solution s = new Solution();
  List<Integer> a = Arrays.asList(88, 30, 11, 17, 22, 16, 39, 8, 31, 55,
    29, 63, 77, 69, 99, 90, 81, 2, 20, 53, 62, 5, 88, 33, 44, 6);
  System.out.println(s.findKthElement(a, 18));
  Collections.sort(a);
  System.out.println(a);
  System.out.println(a.get(18));
 }

 public int findKthElement(List<Integer> a, int k) {
  if (a.size() < 10) {
   Collections.sort(a);
   return a.get(k);
  }
  ArrayList<Integer> medians = new ArrayList<Integer>();
  for (int i = 0; i < a.size() - a.size() % 5; i = i + 5)
   medians.add(getMedian(a.subList(i, i + 5)));
  int v = getMedian(medians);

  ArrayList<Integer> left = getPartition(a, v, true);
  ArrayList<Integer> right = getPartition(a, v, false);

  return (left.size() + 1 == k) ? v : (left.size() > k) ? findKthElement(
    left, k) : findKthElement(right, k - left.size());
 }

 public int getMedian(List<Integer> a) {
  Collections.sort(a);
  return a.get(a.size() / 2);
 }

 public ArrayList<Integer> getPartition(List<Integer> a, int v,
   boolean isLessThan) {
  ArrayList<Integer> res = new ArrayList<Integer>();
  for (int val : a)
   if (isLessThan && val < v)
    res.add(val);
   else if (!isLessThan && val >= v)
    res.add(val);
  return res;
 }
}

Output:
62 ( value returned from algorithm)
[2, 5, 6, 8, 11, 16, 17, 20, 22, 29, 30, 31, 33, 39, 44, 53, 55, 62, 63, 69, 77, 81, 88, 88, 90, 99]
62 (kth value after sorting)