How can I build this tree with O(n) space complexity?

Question

The Problem

Given a set of integers, find a subset of those integers which sum to 100,000,000.

Solution

I am attempting to build a tree containing all the combinations of the given set along with the sum. For example, if the given set looked like 0,1,2, I would build the following tree, checking the sum at each node:

                    {}
        {}                      {0}
  {}         {1}         {0}          {0,1}
{}  {2}  {1}   {1,2}  {0}   {2}   {0,1}   {0,1,2}

Since I keep both the array of integers at each node and the sum, I should only need the bottom (current) level of the tree in memory.

Issues

My current implementation will maintain the entire tree in memory and therefore uses way too much heap space.

How can I change my current implementation so that the GC will take care of my upper tree levels?

(At the moment I am just throwing a RuntimeException when I have found the target sum but this is obviously just for playing around)

public class RecursiveSolver {
    static final int target = 100000000;
    static final int[] set = new int[]{98374328, 234234123, 2341234, 123412344, etc...};

    Tree initTree() {
        return nextLevel(new Tree(null), 0);
    }

    Tree nextLevel(Tree currentLocation, int current) {
        if (current == set.length) { return null; }
        else if (currentLocation.sum == target) throw new RuntimeException(currentLocation.getText());
        else {
            currentLocation.left = nextLevel(currentLocation.copy(), current + 1);
            Tree right = currentLocation.copy();
            right.value = add(currentLocation.value, set[current]);
            right.sum = currentLocation.sum + set[current];
            currentLocation.right = nextLevel(right, current + 1);
            return currentLocation;
        }
    }

    int[] add(int[] array, int digit) {
        if (array == null) {
            return new int[]{digit};
        }
        int[] newValue = new int[array.length + 1];
        for (int i = 0; i < array.length; i++) {
            newValue[i] = array[i];
        }
        newValue[array.length] = digit;
        return newValue;
    }

    public static void main(String[] args) {
        RecursiveSolver rs = new RecursiveSolver();
        Tree subsetTree = rs.initTree();
    }
}

class Tree {
    Tree left;
    Tree right;
    int[] value;
    int sum;

    Tree(int[] value) {
        left = null;
        right = null;
        sum = 0;
        this.value = value;
        if (value != null) {
            for (int i = 0; i < value.length; i++) sum += value[i];
        }
    }

    Tree copy() {
        return new Tree(this.value);
    }
}

Answer 1

The time and space you need for building the tree here is absolutely nothing at all.

The reason is because, if you're given

• A node of the tree
• The depth of the node
• The ordered array of input elements

you can simply compute its parent, left, and right children nodes using O(1) operations. And you have access to each of those things while you're traversing the tree, so you don't need anything else.