ransomNote
and magazine
.magazine
to form the ransomNote
.ransomNote
must appear in magazine
with the same frequency or higher.ransomNote
, check if it exists in magazine
.magazine
, remove it by slicing the string (we assume each letter can only be used once).False
immediately.ransomNote
can be found and removed from magazine
, return True
.
The brute force solution is inefficient because it repeatedly searches for each character of the ransomNote
in the magazine
, which takes O(M)
time for each letter. This leads to a total time complexity of O(R * M)
, which becomes slow as the input size grows. Additionally, slicing the string every time we remove a character introduces overhead.
To fix the inefficiency, we use a hashmap (or a Counter
) to count the frequency of characters in magazine
, which allows us to check the availability of each character in constant time. Here's the process:
Counter
) to store the frequency of each character in the magazine
.O(M)
time, where M
is the length of the magazine
.ransomNote
, check if it exists in the hashmap with a positive frequency.False
.ransomNote
, return True
.
The “Ransom Note” problem is a common string manipulation task. You are given two strings: ransomNote
and magazine
. The goal is to determine whether you can construct the ransomNote
by using letters from the magazine
string. Each letter in magazine
can only be used once.
For example:
ransomNote = "a"
, magazine = "b"
→ Output: false
ransomNote = "aa"
, magazine = "aab"
→ Output: true
This problem is important because it reflects real-world scenarios like checking resource availability, verifying data integrity, or solving subset containment problems. It also introduces essential concepts like character counting, frequency analysis, and hash maps — all of which are frequently used in string and array processing tasks.
The brute-force method involves checking, for every character in ransomNote
, whether it exists in magazine
. If it does, we remove that character from magazine
(to simulate using it once). If any character is not found, we return false
.
This approach leads to poor performance because searching for a character in a string is O(M)
, and we do this for each character in ransomNote
. The total time complexity becomes O(R Ă— M)
, which is inefficient for longer strings.
The optimal way to solve this problem is by using a hash map (or Python’s collections.Counter
) to count how many times each character appears in magazine
. This allows for fast and efficient lookups while processing ransomNote
.
magazine
and record how many times it appears. This takes O(M) time.
ransomNote
, check if it exists in the hash map and whether its count is positive.
false
.
ransomNote
are accounted for, return true
.
Input: ransomNote = "aab"
, magazine = "baa"
{'b': 1, 'a': 2}
true
Time Complexity: O(M + R), where M is the length of magazine
and R is the length of ransomNote
.
Space Complexity: O(1), because the number of characters is limited (only lowercase English letters).
ransomNote
→ always return true
magazine
but non-empty ransomNote
→ always return false
"A"
and "a"
are different charactersThe “Ransom Note” problem teaches how to efficiently manage and compare frequencies between two data sources. While the brute-force method demonstrates a naïve solution, the optimized version using a hash map offers a significant performance boost and is widely applicable to many real-world problems.