[heesun-task] WEEK 01 Solutions

contains-duplicate/heesun-task.java

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+class Solution {
+    public boolean containsDuplicate(int[] nums) {
+        // Create a set to track seen numbers
+        Set<Integer> seen = new HashSet<>();
+
+        // Loop through the array and return true if a duplicate is found
+        for (int num : nums) {
+            if (!seen.add(num)) {
+                return true;
+            }
+        }
+
+        return false;
+    }
+}
+
+// Time Complexity: O(n) on average
+// Space Complexity: O(n)

top-k-frequent-elements/heesun-task.java

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+import java.util.HashMap;
+import java.util.Map;
+import java.util.PriorityQueue;
+
+class Solution {
+    public int[] topKFrequent(int[] nums, int k) {
+        // Count each number's frequency using a hash map.
+        Map<Integer, Integer> freq = new HashMap<>();
+        for (int num : nums) {
+            freq.put(num, freq.getOrDefault(num, 0) + 1);
+        }
+
+        // Keep the top k numbers in a min-heap ordered by frequency.
+        PriorityQueue<Integer> heap = new PriorityQueue<>(
+            (a, b) -> Integer.compare(freq.get(a), freq.get(b))
+        );
+
+        for (int num : freq.keySet()) {
+            if (heap.size() < k) {
+                heap.offer(num);
+            } else if (freq.get(num) > freq.get(heap.peek())) {
+                // Replace the least frequent number.
+                heap.poll();
+                heap.offer(num);
+            }
+        }
+
+        // Return the numbers in the heap.
+        int[] result = new int[k];
+        for (int i = 0; i < k; i++) {
+            result[i] = heap.poll();
+        }
+
+        return result;
+    }
+}
+
+// Time Complexity: O(n + u log k)
+// Space Complexity: O(u + k)
+// n = nums.length, u = number of unique numbers