126 problems across 18 patterns. Master them all. See all patterns
Two Pointers
Valid Palindrome
What's the time complexity?
O(n²) O(n)
Hash Map
O(1) lookup for complement
12 Completed
Sliding Window

Build pattern recognition for coding interviews through interactive MCQs, not passive video watching

Two Pointers
Valid Palindrome
What's the time complexity?
O(n²) O(n)
Hash Map
O(1) lookup for complement
12 Completed
Sliding Window

Stop memorizing LeetCode solutions. LeetEye breaks down each problem into focused questions that teach you why patterns work, so you can recognize and apply them to new problems instantly. 5 minutes per problem. No account required.

See how it works →

Learn anywhere, anytime

Each problem takes just 5 minutes. Perfect for commutes, lunch breaks, or quick study sessions. Build intuition in small, focused bursts instead of hour-long grinding sessions.

Explore features

Built for engineers preparing for interviews at

The problem with grinding LeetCode

Hours of passive watching

YouTube tutorials feel productive but don't build real problem-solving skills.

Memorizing, not understanding

You remember solutions but can't recognize when to apply them to new problems.

Interview anxiety

You've solved this type before, but under pressure you can't recall the pattern.

The LeetEye Approach

Train your pattern recognition,
not your memory.

LeetEye breaks down each problem into focused MCQs that teach you why solutions work, not just what they are.

Python solutions that click

After mastering the pattern, see clean Python implementations that match exactly what you learned. No confusing alternative approaches.

def twoSum(nums, target):
seen = {} # O(1) lookup
for i, num in enumerate(nums):
comp = target - num
if comp in seen:
return [seen[comp], i]
seen[num] = i
def isPalindrome(s):
l, r = 0, len(s) - 1
while l < r:
while l < r and not s[l].isalnum():
l += 1
if s[l].lower() != s[r].lower():
return False
def maxSubArray(nums):
max_sum = cur_sum = nums[0]
for num in nums[1:]:
cur_sum = max(num, cur_sum + num)
max_sum = max(max_sum, cur_sum)
return max_sum
# Kadane's Algorithm O(n)
def search(nums, target):
l, r = 0, len(nums) - 1
while l <= r:
mid = (l + r) // 2
if nums[mid] == target: return mid
elif nums[mid] < target: l = mid + 1
else: r = mid - 1

Understand the "why"

Each MCQ targets a specific insight: why hash maps beat nested loops, when to use two pointers, what makes a problem greedy.

Interactive MCQs

Every problem broken into bite-sized questions that test your understanding of the pattern, not just the answer.

5-minute sessions

Perfect for commutes, lunch breaks, or quick practice. Build intuition in small, focused bursts.

Concept deep-dives

Stuck on a pattern? Tap to review comprehensive guides on hash maps, two pointers, and more.

Track your progress

See which patterns you've mastered and which need more practice. Spaced repetition keeps you sharp.

Random challenge mode

Test yourself with random problems across all patterns. Perfect for simulating real interview conditions.

How LeetEye works

Three steps to building lasting pattern recognition

01

Choose a pattern

Start with foundational patterns like Hash Maps or Two Pointers, then progress to advanced topics like Dynamic Programming and Graphs.

02

Answer focused MCQs

Each problem is broken into questions that guide your thinking: "What's the key insight?" "Which data structure?" "What's the time complexity?"

03

See the pattern click

After answering, see the clean Python solution and understand exactly why it works. Review concept guides to deepen understanding.

Master 18 essential patterns

Hash Maps
Two Pointers
Sliding Window
Binary Search
Linked Lists
Stacks
Trees
Tries
Backtracking
Heaps
Graphs
Dynamic Programming
Greedy
Intervals
Bit Manipulation
Union Find
Topological Sort
Dijkstra's

Support Us

LeetEye is completely free, built by the creators of ShedboxAI

If LeetEye helps you land your dream job, consider buying us a coffee. Your support helps us keep building free tools for developers.

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