Design-1

HashSet.java

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+// Time Complexity : add, remove, contains = O(1)
+// Space Complexity : O(n * m) where n = buckets, m = bucketItems
+// Did this code successfully run on Leetcode : yes
+// Any problem you faced while coding this : no
+
+
+// Your code here along with comments explaining your approach
+class MyHashSet {
+
+    //If element is present then it is true else false
+    private boolean[][] storage;
+    //size of array
+    private int buckets;
+    //size of nested array
+    private int bucketItems;
+
+    //Hash 1
+    public int bucket(int key) {
+        //we get location in array
+        return key % buckets;
+    }
+
+    //Hash 2 :- input will never have same hash1 and hash2 hence no collision
+    public int bucketItem(int key) {
+        //we get location in nested array
+        return key / bucketItems;
+    }
+
+    public MyHashSet() {
+
+        //we take square root of 10^6 which is range of inputs
+        this.buckets = 1000;
+        this.bucketItems = 1000;
+
+        //We do not give nested array size because if there is no element in that index we will not create the nested array thereby saving space
+        storage = new boolean[buckets][];
+    }
+
+    public void add(int key) {
+
+        int location = bucket(key);
+
+        //if the array location is empty we will create nested array and add the element
+        if(storage[location] == null) {
+
+            if(location == 0) {
+
+                //We do +1 here because for eg:- if the input is 10^6. The size of array is 1000 which is 0 to 999 and nested array is also 0-999. but if input is 10^6, we wont be able to store the value in nested array as 10^6 / 1000 = 1000. 
+                storage[location] = new boolean[bucketItems + 1];
+
+            }else {
+                storage[location] = new boolean[bucketItems];
+            }
+        }
+
+        //location in the nested array
+        int nesLocation = bucketItem(key);
+        storage[location][nesLocation] = true;
+    }
+
+    public void remove(int key) {
+
+        int location = bucket(key);
+
+        //It means this element is not present in hash set
+        if(storage[location] == null)
+            return;
+
+        //If it is present we will find the exact location in nested array
+        int nesLocation = bucketItem(key);
+
+        //If there was an element in the index it would be true
+        storage[location][nesLocation] = false;
+
+    }
+
+    public boolean contains(int key) {
+
+        int location = bucket(key);
+
+        //It means this element is not present in hash set
+        if(storage[location] == null)
+            return false;
+
+        //Find the exact location of key
+        int nesLocation = bucketItem(key);
+
+        //If there is an element it is true else false
+        return storage[location][nesLocation];
+    }
+}
+
+/**
+ * Your MyHashSet object will be instantiated and called as such:
+ * MyHashSet obj = new MyHashSet();
+ * obj.add(key);
+ * obj.remove(key);
+ * boolean param_3 = obj.contains(key);
+ */

MinStack.java

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+// Time Complexity : Push = O(1), Pop = O(1), top = O(1), getMin = O(1)
+// Space Complexity : O(n) where n = number of elements in the stack
+// Did this code successfully run on Leetcode : yes
+// Any problem you faced while coding this : no
+
+
+// Your code here along with comments explaining your approach
+class MinStack {
+
+    int min;
+    Stack<Integer> stack;
+    Stack<Integer> minStack;
+
+    public MinStack() {
+
+        this.min = Integer.MAX_VALUE;
+        stack = new Stack<>();
+        minStack = new Stack<>();
+    }
+
+    public void push(int val) {
+
+        //If we get a new value which is smaller than current min
+        //We will save it as current min. But we also save previous min because we need it if we pop current min in future
+        //Even if new val == min we save it
+        if(min >= val) {
+            minStack.push(min);
+            min = val;
+        }
+
+        stack.push(val);
+    }
+
+    public void pop() {
+
+        int popped = stack.pop();
+
+        //If we are popping the minimum value then our minimum will be previous min
+        if(popped == min) {
+            //Store prev min in min
+            min = minStack.pop();
+        }
+    }
+
+    public int top() {
+
+        //get the top element from stack
+        return stack.peek();
+    }
+
+    public int getMin() {
+
+        //we store current minimum in min
+        return min;
+    }
+}
+
+/**
+ * Your MinStack object will be instantiated and called as such:
+ * MinStack obj = new MinStack();
+ * obj.push(val);
+ * obj.pop();
+ * int param_3 = obj.top();
+ * int param_4 = obj.getMin();
+ */