# Leetcode: Map Sum Pairs C#

Implement a MapSum class with insert, and sum methods.

For the method insert, you'll be given a pair of (string, integer). The string represents the key and the integer represents the value. If the key already existed, then the original key-value pair will be overridden to the new one.

For the method sum, you'll be given a string representing the prefix, and you need to return the sum of all the pairs' value whose key starts with the prefix.

Example 1:
Input: insert("apple", 3), Output: Null
Input: sum("ap"), Output: 3
Input: insert("app", 2), Output: Null
Input: sum("ap"), Output: 5


Please comment on performance and style

using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace TrieQuestions
{
[TestClass]
public class TrieMapSum
{
[TestMethod]
public void MapSumTest()
{
MapSum mapSum = new MapSum();
mapSum.Insert("apple", 3);
Assert.AreEqual(3, mapSum.Sum("ap"));
mapSum.Insert("app", 2);
Assert.AreEqual(5, mapSum.Sum("ap"));
}
}

public class MapSum
{
/** Initialize your data structure here. */
public MapSum()
{
}

public void Insert(string key, int val)
{
foreach (var letter in key)
{
if (!current.Edges.ContainsKey(letter))
{
}
current = current.Edges[letter];
}

current.IsTerminal = true;
current.Value = val;
}

public int Sum(string prefix)
{
int sum = 0;
foreach (var letter in prefix)
{
if (!current.Edges.ContainsKey(letter))
{
return sum;
}

current = current.Edges[letter];
}
// we use dfs for each edges of the trie;
return DFS(current);
}

private int DFS(TrieMSNode current)
{
if (current == null)
{
return 0;
}

int sum = current.IsTerminal ? current.Value : 0;
foreach (var edge in current.Edges.Values)
{
sum += DFS(edge);
}
return sum;
}
}

internal class TrieMSNode
{
public Dictionary<char, TrieMSNode> Edges { get; set; }
public bool IsTerminal;
public int Value;

public TrieMSNode()
{
Edges = new Dictionary<char, TrieMSNode>();
IsTerminal = false;
Value = 0;
}
}
}


In Insert(...) you should use TryGetValue instead of ContainsKeyfor efficiency:

  foreach (var letter in key)
{
if (!current.Edges.TryGetValue(letter, out var edge))
{
edge = current.Edges[letter] = new TrieMSNode();
}
current = edge;
}


Name your methods after what they do, not after their implementation:

DFS(...)

could be GetSumFrom(...)

public int Sum(string prefix)
{
int sum = 0;
foreach (var letter in prefix)
{
if (!current.Edges.ContainsKey(letter))
{
return sum;
}
current = current.Edges[letter];
}


Here the sum variable is redundant because it is never changed so you could just return 0 from the loop

Again the loop can be optimized:

  foreach (char letter in prefix)
{
if (!current.Edges.TryGetValue(letter, out current))
return 0;
}


DFS()


can be simplified using LINQ:

    private int GetSumFrom(TrieMSNode current)
{
if (current == null)
{
return 0;
}

return current.Edges.Aggregate(current.Value, (sum, kvp) => sum + GetSumFrom(kvp.Value));
}


You really don't have to check for IsTerminal because you know that only terminal nodes have a values different from 0.

You should test this LINQ-approach against your own plain foreach-loop, and you'll maybe find the latter fastest.

• I've upvoted because you make some good points, but I don't understand the reasoning in the first point. Surely the edge is the KeyValuePair<char, TrieMSNode>? – Peter Taylor May 21 at 6:57
• @PeterTaylor: You're right, my misinterpretation of the Dictionary concept – Henrik Hansen May 21 at 7:02

I don't have much to add to Henrik's answer at a low level, but I think you've missed the point of the exercise at a high level.

The spec could be implemented as simply as

public class MapSum
{
private readonly IDictionary<string, int> data = new Dictionary<string, int>();

public void Insert(string key, int val) => data[key] = val;

public int Sum(string prefix) => data.Sum(kvp => kvp.Key.StartsWith(prefix) ? kvp.Value : 0);
}


The reason you instead used a trie was to avoid looping over all of the entries in Sum. But in the worst case DFS will do exactly that. The efficient solution is to add a field to TrieMSNode which caches the sum of the entire subtree rooted at that node. Updating it doesn't affect the asymptotic cost of Insert, just the constant. And returning it allows you to ditch DFS entirely, so that Sum is guaranteed to run in time linear in the length of the prefix.

• Isn't your sum() implementation rather time-expensive (O(m*n)) and your storage rather memory-expensive? – Henrik Hansen May 21 at 8:09
• @HenrikHansen, I'm not proposing that OP use the code I posted. Or was your point just that the trie is actually already not quite as bad, because its Sum() is only $O(n)$? – Peter Taylor May 21 at 9:47
• Just pondering but wouldn't an ordered dictionary be faster in the average case? – MD-Tech May 21 at 14:02
• @MD-Tech, faster than what at which operation? But anyway, I doubt it: hashmaps are very fast for insertion of random data and for iteration, and they're the slowest overall implementation mentioned so far. – Peter Taylor May 21 at 14:23
• @PeterTaylor I was thinking about the prefixed sum actually. As I said I'm only pondering aloud. – MD-Tech May 21 at 14:32

The time complexity of Sum is $$\O(m n)\$$, because in the worst case it may need to enumerate all nodes.

An $$\O(m)\$$ implementation is possible with $$\O(n)\$$ extra space, and a bit of extra work in Insert:

• Add a Dictionary<string, int> to track the current values of the keys, let's call it values.
• Use TrieMSNode.Value to store the sum of all values below each node
• When inserting:
• First check if the key replaces an existing key. Let's store in int prev the previous value of the key, or 0 if there was no previous value (the key is new).
• Traverse the trie letter by letter as before, and for each node traversed, subtract prev and add val.
• Set the new value in values.

Notice that the added work in Insert does not increase the time or space complexity.

public void Insert(string key, int val)
{
var prev = values.ContainsKey(key) ? values[key] : 0;
values[key] = val;

foreach (var letter in key)
{
if (!current.Edges.ContainsKey(letter))
{
}
else
{
current.Edges[letter].Value -= prev;
current.Edges[letter].Value += val;
}
current = current.Edges[letter];
}
}


And now, the implementation of Sum can become simpler and faster:

public int Sum(string prefix)
{

Also notice that in this implementation the TrieMSNode.IsTerminal is no longer necessary.