Sliding Window Technique Made Easy: Master This Powerful Algorithm Pattern
· 3 min read
The Sliding Window technique is one of the most powerful algorithmic patterns for solving array and string problems efficiently. It's a must-know technique for coding interviews and can transform O(n²) solutions into elegant O(n) algorithms.
Interactive Sliding Window Visualizer
Try out different sliding window problems with our interactive visualizer below. Watch how the window slides across the input and see the algorithm in action!
Interactive Sliding Window Visualizer
Count Substring Occurrences
Find how many times a pattern appears in the string
Find how many times a pattern appears in the string
Window [0, 2]
a
b
c
a
b
c
a
b
c
a
b
c
Normal
Current Window
Match Found
Comparing
How it works:
- Create a window of size equal to pattern length
- Slide the window from left to right across the string
- At each position, compare window content with the pattern
- Count matches and continue until end of string
- Time Complexity: O(n) where n is string length
Python Implementation
🎯 Count Substring Occurrences
def count_substring(string, sub_string):
"""
Count occurrences of substring using sliding window
Time: O(n), Space: O(1)
"""
win_size = len(sub_string)
l_string = len(string)
cnt = 0
n_window_slides = l_string - win_size
for i in range(n_window_slides + 1):
curr_win = string[i:win_size + i]
if sub_string == curr_win:
cnt += 1
return cnt
# Example usage
string = "abcabcabcabc"
pattern = "abc"
result = count_substring(string, pattern)
print(f"Pattern '{pattern}' found {result} times") # Output: 4🚀 Sliding Window Tips & Tricks
🎯 When to Use
- Contiguous subarray/substring problems
- Finding optimal values (min/max)
- Pattern matching and counting
- Character frequency problems
⚡ Performance Benefits
- Reduces O(n²) to O(n) complexity
- Eliminates redundant calculations
- Uses constant extra space
- Single-pass solution
🔧 Implementation Tips
- Use hashmap for frequency tracking
- Handle edge cases (empty input)
- Choose fixed vs variable window
- Optimize window updates