894. All Possible Full Binary Trees - Explanation

Prerequisites

Before attempting this problem, you should be comfortable with:

Binary Trees - Understanding tree structure and node creation
Recursion - Breaking down problems by combining solutions to subproblems
Dynamic Programming (Memoization) - Caching results to avoid redundant computation

1. Recursion

Intuition

A full binary tree has every node with either 0 or 2 children. If we have n nodes, one becomes the root, and we split the remaining n-1 nodes between the left and right subtrees. Each subtree must also be a full binary tree.

We try all possible ways to distribute n-1 nodes between left and right. For each valid split, we recursively generate all possible left subtrees and all possible right subtrees, then combine each left-right pair under a new root.

Algorithm

Base cases: If n == 0, return an empty list. If n == 1, return a list with a single node.
For l from 0 to n-1:
- Set r = n - 1 - l (remaining nodes for the right subtree).
- Recursively get all full binary trees with l nodes for the left.
- Recursively get all full binary trees with r nodes for the right.
- For each combination of left and right subtree, create a new root and add it to the res.
Return the res list.

# Definition for a binary tree node.
# class TreeNode:
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution:
    def allPossibleFBT(self, n: int) -> List[Optional[TreeNode]]:
        def backtrack(n):
            if n == 0:
                return []
            if n == 1:
                return [TreeNode(0)]

            res = []
            for l in range(n):
                r = n - 1 - l
                leftTrees, rightTrees = backtrack(l), backtrack(r)

                for t1 in leftTrees:
                    for t2 in rightTrees:
                        res.append(TreeNode(0, t1, t2))
            return res

        return backtrack(n)

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     int val;
 *     TreeNode left;
 *     TreeNode right;
 *     TreeNode() {}
 *     TreeNode(int val) { this.val = val; }
 *     TreeNode(int val, TreeNode left, TreeNode right) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
public class Solution {
    public List<TreeNode> allPossibleFBT(int n) {
        return backtrack(n);
    }

    private List<TreeNode> backtrack(int n) {
        if (n == 0) {
            return new ArrayList<>();
        }
        if (n == 1) {
            return Arrays.asList(new TreeNode(0));
        }

        List<TreeNode> res = new ArrayList<>();
        for (int l = 0; l < n; l++) {
            int r = n - 1 - l;
            List<TreeNode> leftTrees = backtrack(l);
            List<TreeNode> rightTrees = backtrack(r);

            for (TreeNode t1 : leftTrees) {
                for (TreeNode t2 : rightTrees) {
                    res.add(new TreeNode(0, t1, t2));
                }
            }
        }
        return res;
    }
}

/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode() : val(0), left(nullptr), right(nullptr) {}
 *     TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
 *     TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}
 * };
 */
class Solution {
public:
    vector<TreeNode*> allPossibleFBT(int n) {
        return backtrack(n);
    }

private:
    vector<TreeNode*> backtrack(int n) {
        if (n == 0) {
            return {};
        }
        if (n == 1) {
            return {new TreeNode(0)};
        }

        vector<TreeNode*> res;
        for (int l = 0; l < n; l++) {
            int r = n - 1 - l;
            vector<TreeNode*> leftTrees = backtrack(l);
            vector<TreeNode*> rightTrees = backtrack(r);

            for (auto& t1 : leftTrees) {
                for (auto& t2 : rightTrees) {
                    res.push_back(new TreeNode(0, t1, t2));
                }
            }
        }
        return res;
    }
};

/**
 * Definition for a binary tree node.
 * class TreeNode {
 *     constructor(val = 0, left = null, right = null) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
class Solution {
    /**
     * @param {number} n
     * @return {TreeNode[]}
     */
    allPossibleFBT(n) {
        const backtrack = (n) => {
            if (n === 0) {
                return [];
            }
            if (n === 1) {
                return [new TreeNode(0)];
            }

            let res = [];
            for (let l = 0; l < n; l++) {
                let r = n - 1 - l;
                let leftTrees = backtrack(l);
                let rightTrees = backtrack(r);

                for (let t1 of leftTrees) {
                    for (let t2 of rightTrees) {
                        res.push(new TreeNode(0, t1, t2));
                    }
                }
            }
            return res;
        };

        return backtrack(n);
    }
}

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     public int val;
 *     public TreeNode left;
 *     public TreeNode right;
 *     public TreeNode(int val=0, TreeNode left=null, TreeNode right=null) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
public class Solution {
    public IList<TreeNode> AllPossibleFBT(int n) {
        return Backtrack(n);
    }

    private IList<TreeNode> Backtrack(int n) {
        if (n == 0) {
            return new List<TreeNode>();
        }
        if (n == 1) {
            return new List<TreeNode> { new TreeNode(0) };
        }

        List<TreeNode> res = new List<TreeNode>();
        for (int l = 0; l < n; l++) {
            int r = n - 1 - l;
            IList<TreeNode> leftTrees = Backtrack(l);
            IList<TreeNode> rightTrees = Backtrack(r);

            foreach (TreeNode t1 in leftTrees) {
                foreach (TreeNode t2 in rightTrees) {
                    res.Add(new TreeNode(0, t1, t2));
                }
            }
        }
        return res;
    }
}

/**
 * Definition for a binary tree node.
 * type TreeNode struct {
 *     Val int
 *     Left *TreeNode
 *     Right *TreeNode
 * }
 */
func allPossibleFBT(n int) []*TreeNode {
    var backtrack func(n int) []*TreeNode
    backtrack = func(n int) []*TreeNode {
        if n == 0 {
            return []*TreeNode{}
        }
        if n == 1 {
            return []*TreeNode{{Val: 0}}
        }

        res := []*TreeNode{}
        for l := 0; l < n; l++ {
            r := n - 1 - l
            leftTrees := backtrack(l)
            rightTrees := backtrack(r)

            for _, t1 := range leftTrees {
                for _, t2 := range rightTrees {
                    res = append(res, &TreeNode{Val: 0, Left: t1, Right: t2})
                }
            }
        }
        return res
    }

    return backtrack(n)
}

/**
 * Example:
 * var ti = TreeNode(5)
 * var v = ti.`val`
 * Definition for a binary tree node.
 * class TreeNode(var `val`: Int) {
 *     var left: TreeNode? = null
 *     var right: TreeNode? = null
 * }
 */
class Solution {
    fun allPossibleFBT(n: Int): List<TreeNode?> {
        fun backtrack(n: Int): List<TreeNode?> {
            if (n == 0) return emptyList()
            if (n == 1) return listOf(TreeNode(0))

            val res = mutableListOf<TreeNode?>()
            for (l in 0 until n) {
                val r = n - 1 - l
                val leftTrees = backtrack(l)
                val rightTrees = backtrack(r)

                for (t1 in leftTrees) {
                    for (t2 in rightTrees) {
                        res.add(TreeNode(0).apply {
                            left = t1
                            right = t2
                        })
                    }
                }
            }
            return res
        }

        return backtrack(n)
    }
}

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     public var val: Int
 *     public var left: TreeNode?
 *     public var right: TreeNode?
 *     public init() { self.val = 0; self.left = nil; self.right = nil; }
 *     public init(_ val: Int) { self.val = val; self.left = nil; self.right = nil; }
 *     public init(_ val: Int, _ left: TreeNode?, _ right: TreeNode?) {
 *         self.val = val
 *         self.left = left
 *         self.right = right
 *     }
 * }
 */
class Solution {
    func allPossibleFBT(_ n: Int) -> [TreeNode?] {
        func backtrack(_ n: Int) -> [TreeNode?] {
            if n == 0 { return [] }
            if n == 1 { return [TreeNode(0)] }

            var res = [TreeNode?]()
            for l in 0..<n {
                let r = n - 1 - l
                let leftTrees = backtrack(l)
                let rightTrees = backtrack(r)

                for t1 in leftTrees {
                    for t2 in rightTrees {
                        res.append(TreeNode(0, t1, t2))
                    }
                }
            }
            return res
        }

        return backtrack(n)
    }
}

Time & Space Complexity

Time complexity: $O(2 ^ n)$
Space complexity: $O(n * 2 ^ n)$

2. Recursion (Optimal)

Intuition

A full binary tree with n nodes only exists when n is odd. Every full binary tree has one root plus pairs of nodes in the subtrees, so the total must be odd. This lets us prune impossible cases immediately.

Additionally, we only need to try odd values for the left subtree size since each subtree must also form a valid full binary tree (requiring an odd count). This cuts the search space roughly in half.

Algorithm

If n is even, return an empty list (impossible to form a full binary tree).
If n == 1, return a list with a single node.
For left from 1 to n-1, stepping by 2 (odd values only):
- Recursively get all full binary trees with left nodes.
- Recursively get all full binary trees with n - 1 - left nodes.
- Combine each pair under a new root and add to the res.
Return the res list.

# Definition for a binary tree node.
# class TreeNode:
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution:
    def allPossibleFBT(self, n: int) -> List[Optional[TreeNode]]:
        if n % 2 == 0:
            return []
        if n == 1:
            return [TreeNode(0)]

        res = []
        for left in range(1, n, 2):
            leftSubTree = self.allPossibleFBT(left)
            rightSubTree = self.allPossibleFBT(n - 1 - left)
            for l in leftSubTree:
                for r in rightSubTree:
                    root = TreeNode(0, l, r)
                    res.append(root)
        return res

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     int val;
 *     TreeNode left;
 *     TreeNode right;
 *     TreeNode() {}
 *     TreeNode(int val) { this.val = val; }
 *     TreeNode(int val, TreeNode left, TreeNode right) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
public class Solution {
    public List<TreeNode> allPossibleFBT(int n) {
        if (n % 2 == 0) {
            return new ArrayList<>();
        }
        if (n == 1) {
            return Arrays.asList(new TreeNode(0));
        }

        List<TreeNode> res = new ArrayList<>();
        for (int left = 1; left < n; left += 2) {
            List<TreeNode> leftSubTree = allPossibleFBT(left);
            List<TreeNode> rightSubTree = allPossibleFBT(n - 1 - left);
            for (TreeNode l : leftSubTree) {
                for (TreeNode r : rightSubTree) {
                    TreeNode root = new TreeNode(0, l, r);
                    res.add(root);
                }
            }
        }
        return res;
    }
}

/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode() : val(0), left(nullptr), right(nullptr) {}
 *     TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
 *     TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}
 * };
 */
class Solution {
public:
    vector<TreeNode*> allPossibleFBT(int n) {
        if (n % 2 == 0) {
            return {};
        }
        if (n == 1) {
            return {new TreeNode(0)};
        }

        vector<TreeNode*> res;
        for (int left = 1; left < n; left += 2) {
            vector<TreeNode*> leftSubTree = allPossibleFBT(left);
            vector<TreeNode*> rightSubTree = allPossibleFBT(n - 1 - left);
            for (auto& l : leftSubTree) {
                for (auto& r : rightSubTree) {
                    TreeNode* root = new TreeNode(0, l, r);
                    res.push_back(root);
                }
            }
        }
        return res;
    }
};

/**
 * Definition for a binary tree node.
 * class TreeNode {
 *     constructor(val = 0, left = null, right = null) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
class Solution {
    /**
     * @param {number} n
     * @return {TreeNode[]}
     */
    allPossibleFBT(n) {
        if (n % 2 === 0) {
            return [];
        }
        if (n === 1) {
            return [new TreeNode(0)];
        }

        let res = [];
        for (let left = 1; left < n; left += 2) {
            let leftSubTree = this.allPossibleFBT(left);
            let rightSubTree = this.allPossibleFBT(n - 1 - left);
            for (let l of leftSubTree) {
                for (let r of rightSubTree) {
                    let root = new TreeNode(0, l, r);
                    res.push(root);
                }
            }
        }
        return res;
    }
}

public class Solution {
    public IList<TreeNode> AllPossibleFBT(int n) {
        if (n % 2 == 0) {
            return new List<TreeNode>();
        }
        if (n == 1) {
            return new List<TreeNode> { new TreeNode(0) };
        }

        List<TreeNode> res = new List<TreeNode>();
        for (int left = 1; left < n; left += 2) {
            IList<TreeNode> leftSubTree = AllPossibleFBT(left);
            IList<TreeNode> rightSubTree = AllPossibleFBT(n - 1 - left);
            foreach (TreeNode l in leftSubTree) {
                foreach (TreeNode r in rightSubTree) {
                    res.Add(new TreeNode(0, l, r));
                }
            }
        }
        return res;
    }
}

func allPossibleFBT(n int) []*TreeNode {
    if n%2 == 0 {
        return []*TreeNode{}
    }
    if n == 1 {
        return []*TreeNode{{Val: 0}}
    }

    res := []*TreeNode{}
    for left := 1; left < n; left += 2 {
        leftSubTree := allPossibleFBT(left)
        rightSubTree := allPossibleFBT(n - 1 - left)
        for _, l := range leftSubTree {
            for _, r := range rightSubTree {
                res = append(res, &TreeNode{Val: 0, Left: l, Right: r})
            }
        }
    }
    return res
}

class Solution {
    fun allPossibleFBT(n: Int): List<TreeNode?> {
        if (n % 2 == 0) return emptyList()
        if (n == 1) return listOf(TreeNode(0))

        val res = mutableListOf<TreeNode?>()
        for (left in 1 until n step 2) {
            val leftSubTree = allPossibleFBT(left)
            val rightSubTree = allPossibleFBT(n - 1 - left)
            for (l in leftSubTree) {
                for (r in rightSubTree) {
                    res.add(TreeNode(0).apply {
                        this.left = l
                        right = r
                    })
                }
            }
        }
        return res
    }
}

Time & Space Complexity

Time complexity: $O(2 ^ n)$
Space complexity: $O(n * 2 ^ n)$

3. Dynamic Programming (Top-Down)

Intuition

The recursive solution recomputes the same subproblems multiple times. For example, when building trees of size 7, we compute trees of size 3 several times across different branches.

By caching results in a hash map or array, we ensure each subproblem is solved only once. The first time we compute all trees for a given n, we store them. Future calls simply return the cached dp result.

Algorithm

Create a memoization map dp to store results for each n.
Define a recursive function dfs(n):
- If n is even, return an empty list.
- If n == 1, return a list with a single node.
- If dp[n] exists, return it.
- For left from 1 to n-1, stepping by 2:
  - Recursively get left and right subtrees.
  - Combine all pairs under new roots.
- Store the res in dp[n] and return it.
Call dfs(n) and return the result.

# Definition for a binary tree node.
# class TreeNode:
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution:
    def allPossibleFBT(self, n: int) -> List[Optional[TreeNode]]:
        dp = {}

        def dfs(n):
            if n % 2 == 0:
                return []
            if n == 1:
                return [TreeNode(0)]
            if n in dp:
                return dp[n]

            res = []
            for left in range(1, n, 2):
                leftSubTree = dfs(left)
                rightSubTree = dfs(n - 1 - left)
                for l in leftSubTree:
                    for r in rightSubTree:
                        res.append(TreeNode(0, l, r))

            dp[n] = res
            return res

        return dfs(n)

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     int val;
 *     TreeNode left;
 *     TreeNode right;
 *     TreeNode() {}
 *     TreeNode(int val) { this.val = val; }
 *     TreeNode(int val, TreeNode left, TreeNode right) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
public class Solution {
    private List<TreeNode>[] dp;

    public List<TreeNode> allPossibleFBT(int n) {
        dp = new ArrayList[n + 1];
        return dfs(n);
    }

    private List<TreeNode> dfs(int n) {
        if (n % 2 == 0) {
            return new ArrayList<>();
        }
        if (n == 1) {
            return Arrays.asList(new TreeNode(0));
        }
        if (dp[n] != null) {
            return dp[n];
        }

        List<TreeNode> res = new ArrayList<>();
        for (int left = 1; left < n; left += 2) {
            List<TreeNode> leftSubTree = dfs(left);
            List<TreeNode> rightSubTree = dfs(n - 1 - left);
            for (TreeNode l : leftSubTree) {
                for (TreeNode r : rightSubTree) {
                    res.add(new TreeNode(0, l, r));
                }
            }
        }

        return dp[n] = res;
    }
}

/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode() : val(0), left(nullptr), right(nullptr) {}
 *     TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
 *     TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}
 * };
 */
class Solution {
private:
    vector<vector<TreeNode*>> dp;

public:
    vector<TreeNode*> allPossibleFBT(int n) {
        dp.resize(n + 1);
        return dfs(n);
    }

    vector<TreeNode*> dfs(int n) {
        if (n % 2 == 0) {
            return {};
        }
        if (n == 1) {
            return {new TreeNode(0)};
        }
        if (!dp[n].empty()) {
            return dp[n];
        }

        vector<TreeNode*> res;
        for (int left = 1; left < n; left += 2) {
            vector<TreeNode*> leftSubTree = dfs(left);
            vector<TreeNode*> rightSubTree = dfs(n - 1 - left);
            for (auto& l : leftSubTree) {
                for (auto& r : rightSubTree) {
                    res.push_back(new TreeNode(0, l, r));
                }
            }
        }

        return dp[n] = res;
    }
};

/**
 * Definition for a binary tree node.
 * class TreeNode {
 *     constructor(val = 0, left = null, right = null) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
class Solution {
    /**
     * @param {number} n
     * @return {TreeNode[]}
     */
    allPossibleFBT(n) {
        let dp = new Array(n + 1);

        const dfs = (n) => {
            if (n % 2 === 0) {
                return [];
            }
            if (n === 1) {
                return [new TreeNode(0)];
            }
            if (dp[n]) {
                return dp[n];
            }

            let res = [];
            for (let left = 1; left < n; left += 2) {
                let leftSubTree = dfs(left);
                let rightSubTree = dfs(n - 1 - left);
                for (let t1 of leftSubTree) {
                    for (let t2 of rightSubTree) {
                        res.push(new TreeNode(0, t1, t2));
                    }
                }
            }

            return (dp[n] = res);
        };

        return dfs(n);
    }
}

public class Solution {
    private IList<TreeNode>[] dp;

    public IList<TreeNode> AllPossibleFBT(int n) {
        dp = new IList<TreeNode>[n + 1];
        return Dfs(n);
    }

    private IList<TreeNode> Dfs(int n) {
        if (n % 2 == 0) {
            return new List<TreeNode>();
        }
        if (n == 1) {
            return new List<TreeNode> { new TreeNode(0) };
        }
        if (dp[n] != null) {
            return dp[n];
        }

        List<TreeNode> res = new List<TreeNode>();
        for (int left = 1; left < n; left += 2) {
            IList<TreeNode> leftSubTree = Dfs(left);
            IList<TreeNode> rightSubTree = Dfs(n - 1 - left);
            foreach (TreeNode l in leftSubTree) {
                foreach (TreeNode r in rightSubTree) {
                    res.Add(new TreeNode(0, l, r));
                }
            }
        }

        dp[n] = res;
        return res;
    }
}

func allPossibleFBT(n int) []*TreeNode {
    dp := make([][]*TreeNode, n+1)

    var dfs func(n int) []*TreeNode
    dfs = func(n int) []*TreeNode {
        if n%2 == 0 {
            return []*TreeNode{}
        }
        if n == 1 {
            return []*TreeNode{{Val: 0}}
        }
        if dp[n] != nil {
            return dp[n]
        }

        res := []*TreeNode{}
        for left := 1; left < n; left += 2 {
            leftSubTree := dfs(left)
            rightSubTree := dfs(n - 1 - left)
            for _, l := range leftSubTree {
                for _, r := range rightSubTree {
                    res = append(res, &TreeNode{Val: 0, Left: l, Right: r})
                }
            }
        }

        dp[n] = res
        return res
    }

    return dfs(n)
}

class Solution {
    fun allPossibleFBT(n: Int): List<TreeNode?> {
        val dp = arrayOfNulls<List<TreeNode?>>(n + 1)

        fun dfs(n: Int): List<TreeNode?> {
            if (n % 2 == 0) return emptyList()
            if (n == 1) return listOf(TreeNode(0))
            if (dp[n] != null) return dp[n]!!

            val res = mutableListOf<TreeNode?>()
            for (left in 1 until n step 2) {
                val leftSubTree = dfs(left)
                val rightSubTree = dfs(n - 1 - left)
                for (l in leftSubTree) {
                    for (r in rightSubTree) {
                        res.add(TreeNode(0).apply {
                            this.left = l
                            right = r
                        })
                    }
                }
            }

            dp[n] = res
            return res
        }

        return dfs(n)
    }
}

class Solution {
    func allPossibleFBT(_ n: Int) -> [TreeNode?] {
        var dp = [[TreeNode?]?](repeating: nil, count: n + 1)

        func dfs(_ n: Int) -> [TreeNode?] {
            if n % 2 == 0 { return [] }
            if n == 1 { return [TreeNode(0)] }
            if let cached = dp[n] { return cached }

            var res = [TreeNode?]()
            for left in stride(from: 1, to: n, by: 2) {
                let leftSubTree = dfs(left)
                let rightSubTree = dfs(n - 1 - left)
                for l in leftSubTree {
                    for r in rightSubTree {
                        res.append(TreeNode(0, l, r))
                    }
                }
            }

            dp[n] = res
            return res
        }

        return dfs(n)
    }
}

Time & Space Complexity

Time complexity: $O(2 ^ n)$
Space complexity: $O(n * 2 ^ n)$

4. Dynamic Programming (Bottom-Up)

Intuition

Instead of recursing from n down and caching, we can build solutions bottom-up. We start with the base case (n=1), then iteratively compute solutions for n=3, 5, 7, ... up to the target.

For each odd value, we combine previously computed smaller trees to form larger ones. Since we only ever need results for smaller odd numbers, and we compute them in order, all dependencies are satisfied when we need them.

Algorithm

If n is even, return an empty list.
Create an array dp where dp[i] will store all full binary trees with i nodes.
Initialize dp[1] with a single node.
For nodes from 3 to n, stepping by 2:
- For left from 1 to nodes-1, stepping by 2:
  - Set right = nodes - 1 - left.
  - For each tree in dp[left] and each tree in dp[right]:
    - Create a new root combining them and add to dp[nodes].
Return dp[n].

# Definition for a binary tree node.
# class TreeNode:
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution:
    def allPossibleFBT(self, n: int) -> List[Optional[TreeNode]]:
        if n % 2 == 0:
            return []

        dp = [[] for _ in range(n + 1)]
        dp[1] = [TreeNode(0)]

        for nodes in range(3, n + 1, 2):
            res = []
            for left in range(1, nodes, 2):
                right = nodes - 1 - left
                for t1 in dp[left]:
                    for t2 in dp[right]:
                        res.append(TreeNode(0, t1, t2))
            dp[nodes] = res

        return dp[n]

/**
 * Definition for a binary tree node.
 * public class TreeNode {
 *     int val;
 *     TreeNode left;
 *     TreeNode right;
 *     TreeNode() {}
 *     TreeNode(int val) { this.val = val; }
 *     TreeNode(int val, TreeNode left, TreeNode right) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
public class Solution {
    public List<TreeNode> allPossibleFBT(int n) {
        if (n % 2 == 0) {
            return new ArrayList<>();
        }

        List<TreeNode>[] dp = new ArrayList[n + 1];
        for (int i = 0; i <= n; i++) {
            dp[i] = new ArrayList<>();
        }
        dp[1].add(new TreeNode(0));

        for (int nodes = 3; nodes <= n; nodes += 2) {
            List<TreeNode> res = new ArrayList<>();
            for (int left = 1; left < nodes; left += 2) {
                int right = nodes - 1 - left;
                for (TreeNode t1 : dp[left]) {
                    for (TreeNode t2 : dp[right]) {
                        res.add(new TreeNode(0, t1, t2));
                    }
                }
            }
            dp[nodes] = res;
        }

        return dp[n];
    }
}

/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode() : val(0), left(nullptr), right(nullptr) {}
 *     TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
 *     TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}
 * };
 */
class Solution {
public:
    vector<TreeNode*> allPossibleFBT(int n) {
        if (n % 2 == 0) {
            return {};
        }

        vector<vector<TreeNode*>> dp(n + 1);
        dp[1].push_back(new TreeNode(0));

        for (int nodes = 3; nodes <= n; nodes += 2) {
            vector<TreeNode*> res;
            for (int left = 1; left < nodes; left += 2) {
                int right = nodes - 1 - left;
                for (auto& t1 : dp[left]) {
                    for (auto& t2 : dp[right]) {
                        res.push_back(new TreeNode(0, t1, t2));
                    }
                }
            }
            dp[nodes] = res;
        }

        return dp[n];
    }
};

/**
 * Definition for a binary tree node.
 * class TreeNode {
 *     constructor(val = 0, left = null, right = null) {
 *         this.val = val;
 *         this.left = left;
 *         this.right = right;
 *     }
 * }
 */
class Solution {
    /**
     * @param {number} n
     * @return {TreeNode[]}
     */
    allPossibleFBT(n) {
        if (n % 2 === 0) {
            return [];
        }

        let dp = Array.from({ length: n + 1 }, () => []);
        dp[1] = [new TreeNode(0)];

        for (let nodes = 3; nodes <= n; nodes += 2) {
            let res = [];
            for (let left = 1; left < nodes; left += 2) {
                let right = nodes - 1 - left;
                for (let t1 of dp[left]) {
                    for (let t2 of dp[right]) {
                        res.push(new TreeNode(0, t1, t2));
                    }
                }
            }
            dp[nodes] = res;
        }

        return dp[n];
    }
}

public class Solution {
    public IList<TreeNode> AllPossibleFBT(int n) {
        if (n % 2 == 0) {
            return new List<TreeNode>();
        }

        IList<TreeNode>[] dp = new IList<TreeNode>[n + 1];
        for (int i = 0; i <= n; i++) {
            dp[i] = new List<TreeNode>();
        }
        dp[1].Add(new TreeNode(0));

        for (int nodes = 3; nodes <= n; nodes += 2) {
            List<TreeNode> res = new List<TreeNode>();
            for (int left = 1; left < nodes; left += 2) {
                int right = nodes - 1 - left;
                foreach (TreeNode t1 in dp[left]) {
                    foreach (TreeNode t2 in dp[right]) {
                        res.Add(new TreeNode(0, t1, t2));
                    }
                }
            }
            dp[nodes] = res;
        }

        return dp[n];
    }
}

func allPossibleFBT(n int) []*TreeNode {
    if n%2 == 0 {
        return []*TreeNode{}
    }

    dp := make([][]*TreeNode, n+1)
    for i := range dp {
        dp[i] = []*TreeNode{}
    }
    dp[1] = []*TreeNode{{Val: 0}}

    for nodes := 3; nodes <= n; nodes += 2 {
        res := []*TreeNode{}
        for left := 1; left < nodes; left += 2 {
            right := nodes - 1 - left
            for _, t1 := range dp[left] {
                for _, t2 := range dp[right] {
                    res = append(res, &TreeNode{Val: 0, Left: t1, Right: t2})
                }
            }
        }
        dp[nodes] = res
    }

    return dp[n]
}

class Solution {
    fun allPossibleFBT(n: Int): List<TreeNode?> {
        if (n % 2 == 0) return emptyList()

        val dp = Array<MutableList<TreeNode?>>(n + 1) { mutableListOf() }
        dp[1].add(TreeNode(0))

        for (nodes in 3..n step 2) {
            val res = mutableListOf<TreeNode?>()
            for (left in 1 until nodes step 2) {
                val right = nodes - 1 - left
                for (t1 in dp[left]) {
                    for (t2 in dp[right]) {
                        res.add(TreeNode(0).apply {
                            this.left = t1
                            this.right = t2
                        })
                    }
                }
            }
            dp[nodes] = res
        }

        return dp[n]
    }
}

Time & Space Complexity

Time complexity: $O(2 ^ n)$
Space complexity: $O(n * 2 ^ n)$

Common Pitfalls

Forgetting That Full Binary Trees Require Odd Node Counts

A full binary tree can only exist when n is odd. Each node either has 0 or 2 children, so starting with 1 root and adding pairs means the total is always odd. Failing to check this leads to wasted computation or incorrect results.

# Wrong: missing the odd check
def allPossibleFBT(n):
    if n == 1:
        return [TreeNode(0)]
    # Will waste time on even n values

Reusing Tree Nodes Across Different Results

When combining left and right subtrees, you must create a new root node for each combination. Reusing the same node object causes all trees to share structure, corrupting the results.

# Wrong: reusing same root node
root = TreeNode(0)
for l in leftTrees:
    for r in rightTrees:
        root.left, root.right = l, r
        res.append(root)  # All entries point to same node!

Iterating Over Even Values for Subtree Sizes

In a full binary tree, both left and right subtrees must also be full binary trees, meaning they need odd node counts. Iterating over all values instead of only odd values wastes time and produces empty results for even sizes.

# Wrong: iterating all values
for left in range(1, n):  # Includes even values
    ...

# Correct: step by 2 to only use odd values
for left in range(1, n, 2):
    ...