Leetcode frequently presents problems that test a programmer’s understanding of string manipulations and pattern recognition. Among these, the “Long Pressed Name” problem is notable due to its real-world implications related to touchscreen typing errors. This article will dive deep into the problem, elucidate its underlying logic, provide Python-based solutions, and conclude with a complexity analysis.
Table of Contents:
- Understanding the Problem Statement
- Problem Analysis
- Two-Pointer Technique
- Python Implementation
- Complexity Analysis
- Alternate Approaches
- Conclusion
1. Understanding the Problem Statement
Problem:
Your friend is typing his name into a keyboard. Sometimes, when typing a character c
, the key might get long-pressed, and the character will be typed 1 or more times. Given two strings name
and typed
, return True
if typed
can be produced by long pressing some characters (possibly zero characters) of name
, and False
otherwise.
Example:
Input: name = "alex", typed = "aaleex"
Output: True
Explanation: 'a' and 'e' in 'alex' were long pressed.
2. Problem Analysis
The main challenge is to determine if typed
is a valid long-press variation of name
. The problem can be tackled by comparing characters from both strings and checking the frequency of characters in typed
.
3. Two-Pointer Technique
The two-pointer technique shines in problems that involve comparisons within two sequences. For this problem:
i
: pointer for traversing thename
stringj
: pointer for traversing thetyped
string
We’ll move through both strings, comparing the characters at pointers i
and j
.
- If they match, move both pointers ahead.
- If they don’t match, check if
typed[j]
is the same astyped[j-1]
. If true, it indicates a long press, so only movej
ahead. - If neither of the above conditions is met, it means the characters don’t match, and there’s no evidence of a long press. Hence, return
False
.
4. Python Implementation
Here’s a Python solution using the two-pointer technique:
def isLongPressedName(name, typed):
i, j = 0, 0
while j < len(typed):
if i < len(name) and name[i] == typed[j]:
i += 1
j += 1
elif j > 0 and typed[j] == typed[j - 1]:
j += 1
else:
return False
return i == len(name)
5. Complexity Analysis
Time Complexity: O(n+m)
We might traverse both the name
and typed
strings completely, leading to a linear time complexity where n
and m
are the lengths of name
and typed
respectively.
Space Complexity: O(1)
We use only a constant amount of space, regardless of the input size.
6. Alternate Approaches
- Grouping: One could also solve this by grouping characters and comparing the groups. Use the
itertools.groupby()
function in Python to group consecutive similar characters in bothname
andtyped
. Then, compare the character and length of groups from both strings. - Regular Expressions: Create a regex pattern from the
name
string where each character is followed by a ‘+’. This indicates one or more of the character. Then, use this pattern to match thetyped
string.
7. Conclusion
The “Long Pressed Name” problem is a fantastic example of a scenario where string manipulations meet real-world applications. It mimics the challenges faced in predictive text inputs and touch typing errors. By offering a concrete use-case scenario, this problem emphasizes the importance of mastering string manipulation.