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1. The Problem: Encode and Decode Strings

The “Encode and Decode Strings” problem asks us to design an algorithm to convert a list of strings into a single string and then convert that single string back to the original list of strings.

Design an algorithm to encode a list of strings to a string. The encoded string is then sent over the network and is decoded back to the original list of strings.

2. The Intuition: Separators vs. Length-Prefix

The core challenge is how to separate strings when they are joined together, especially if the strings themselves contain special characters.

  1. Unique Separator: Use a specific delimiter (e.g., <#string#>) to mark the end of each string. This is simple but can fail if the separator itself appears in the input strings.
  2. Length-Prefix (Neetcode approach): Prepend each string with its length and a special character (e.g., 4#word). This is much more robust because it tells the decoder exactly how many characters to read next, regardless of what’s inside the string.

3. Implementation (Version 1: Separator)

Here is the implementation using a private _separator field and standard C# string operations.

using System.Text;

public class Solution {
    private string _separator = "<#string#>";

    public string Encode(IList<string> strs) {
        var sb = new StringBuilder();
        foreach (string current in strs) {
            sb.Append(current);
            sb.Append(_separator);
        }
        return sb.ToString();
    }

    public List<string> Decode(string s) {
        var arr = s.Split(_separator).ToList();
        if (arr.Count > 0) {
            arr.RemoveAt(arr.Count - 1);
        }
        return arr;
   }
}

4. Implementation (Version 2: Length-Prefix / Neetcode)

This version follows the Neetcode approach, which uses the Length-Prefix strategy. This is more robust as it doesn’t rely on a unique separator that might appear in the data.

public class Solution {
    public string Encode(IList<string> strs) {
        string res = "";
        foreach (string s in strs) {
            res += s.Length + "#" + s;
        }
        return res;
    }

    public List<string> Decode(string s) {
        List<string> res = new List<string>();
        int i = 0;
        while (i < s.Length) {
            int j = i;
            while (s[j] != '#') {
                j++;
            }
            int length = int.Parse(s.Substring(i, j - i));
            i = j + 1;
            j = i + length;
            res.Add(s.Substring(i, length));
            i = j;
        }
        return res;
    }
}

5. Step-by-Step Breakdown (Length-Prefix)

Step 1: The Encoding Logic

For every string, we calculate its length and append it to the result followed by a delimiter (like #) and then the string itself. For example, ["lint","code"] becomes "4#lint4#code".

Step 2: Finding the Length in Decoding

During decoding, we look for the first # to find where the length indicator ends. Everything before that # is parsed into an integer representing the string’s length.

Step 3: Reading the String

Once we have the length $L$, we know exactly that the next $L$ characters belong to the original string. We extract this substring and move our pointer forward to the start of the next length indicator.

6. Complexity Analysis

Metric Complexity Why?
Time Complexity O(N) We process each character in the input once during encoding and once during decoding (where N is the total number of characters across all strings).
Space Complexity O(N) We store the encoded string and the resulting list, both of which are proportional to the total number of characters.

7. Why use these approaches?

  • Separator Version: Extremely simple to implement using built-in .NET methods. Best when you have control over the input data or can guarantee a unique separator.
  • Length-Prefix (Neetcode): Much more robust and widely used in actual network protocols (like HTTP’s Content-Length). It handles any characters in the input strings without escaping.

8. Summary

The Encode and Decode Strings problem is a classic exercise in data serialization. By choosing a clear delimiter and using efficient string building techniques, we can transform complex data structures into a format suitable for transmission and reconstruct them perfectly.

9. Further Reading

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