Priority Problems: 50 Must-Solve Problems

The essential problem set for rapid interview preparation

---

Overview

This curated list of 50 problems represents the highest-value problems for SDE interview preparation. Each problem was selected based on:

• Frequency: How often similar problems appear in technical interviews
• Pattern Coverage: Ensures all essential patterns are practiced
• Skill Building: Problems build on each other progressively
• Time Efficiency: Maximum learning per hour invested

Target Completion Time: 25-30 hours total (30-40 minutes per problem)

---

How to Use This List

Recommended Approach

1. Solve in order - Problems are arranged by difficulty and dependency
2. Time yourself - Set a 35-40 minute limit per problem
3. Review solutions - After solving, study the optimal approach
4. Document patterns - Note which pattern each problem uses
5. Revisit failures - Re-solve any problem you could not complete

Progress Tracking Legend

[ ] Not started
[~] Attempted but incomplete
[x] Solved independently
[!] Solved with hints
[*] Mastered (can solve in <20 min)

Difficulty Ratings

Rating	Description	Time Target
E	Easy - Warm up	15-20 min
M	Medium - Interview standard	25-35 min
H	Hard - Stretch goal	35-45 min

---

Week 1 Problems (1-25)

Arrays and Strings (1-8)

#	Problem	Difficulty	Pattern	LeetCode	Status
1	Two Sum	E	Hash Map	#1	[ ]
2	Best Time to Buy and Sell Stock	E	Single Pass	#121	[ ]
3	Contains Duplicate	E	Hash Set	#217	[ ]
4	Maximum Subarray	M	Kadane's	#53	[ ]
5	Product of Array Except Self	M	Prefix/Suffix	#238	[ ]
6	3Sum	M	Two Pointers	#15	[ ]
7	Container With Most Water	M	Two Pointers	#11	[ ]
8	Longest Substring Without Repeating	M	Sliding Window	#3	[ ]

Key Learning Goals:

• Master two-pointer technique on sorted/unsorted arrays
• Understand sliding window for substring problems
• Recognize when to use hash maps vs sets

Hash Tables (9-12)

#	Problem	Difficulty	Pattern	LeetCode	Status
9	Valid Anagram	E	Frequency Count	#242	[ ]
10	Group Anagrams	M	Hash + Sort	#49	[ ]
11	Top K Frequent Elements	M	Frequency + Heap	#347	[ ]
12	Longest Consecutive Sequence	M	Hash Set	#128	[ ]

Key Learning Goals:

• Use frequency maps for counting problems
• Combine hash tables with sorting/heaps
• Recognize O(n) solutions using hash sets

Linked Lists (13-17)

#	Problem	Difficulty	Pattern	LeetCode	Status
13	Reverse Linked List	E	Pointer Manipulation	#206	[ ]
14	Merge Two Sorted Lists	E	Two Pointers	#21	[ ]
15	Linked List Cycle	E	Fast/Slow Pointers	#141	[ ]
16	Remove Nth Node From End	M	Two Pointers	#19	[ ]
17	Reorder List	M	Multiple Techniques	#143	[ ]

Key Learning Goals:

• Master in-place reversal
• Apply Floyd's cycle detection
• Combine multiple techniques (find middle + reverse + merge)

Stacks and Queues (18-21)

#	Problem	Difficulty	Pattern	LeetCode	Status
18	Valid Parentheses	E	Stack Matching	#20	[ ]
19	Min Stack	M	Auxiliary Stack	#155	[ ]
20	Daily Temperatures	M	Monotonic Stack	#739	[ ]
21	Largest Rectangle in Histogram	H	Monotonic Stack	#84	[ ]

Key Learning Goals:

• Recognize monotonic stack patterns
• Track auxiliary information in stacks
• Handle "next greater/smaller" problems

Binary Trees (22-25)

#	Problem	Difficulty	Pattern	LeetCode	Status
22	Invert Binary Tree	E	Recursive DFS	#226	[ ]
23	Maximum Depth of Binary Tree	E	DFS/BFS	#104	[ ]
24	Binary Tree Level Order Traversal	M	BFS	#102	[ ]
25	Validate Binary Search Tree	M	Inorder/Range	#98	[ ]

Key Learning Goals:

• Master recursive tree traversals
• Implement BFS for level-order
• Validate tree properties with constraints

---

Week 2 Problems (26-50)

Trees - Advanced (26-30)

#	Problem	Difficulty	Pattern	LeetCode	Status
26	Lowest Common Ancestor of BST	M	BST Properties	#235	[ ]
27	Lowest Common Ancestor of BT	M	Recursive DFS	#236	[ ]
28	Construct Binary Tree from Preorder and Inorder	M	Divide and Conquer	#105	[ ]
29	Serialize and Deserialize Binary Tree	H	BFS/DFS	#297	[ ]
30	Binary Tree Maximum Path Sum	H	DFS + Global Max	#124	[ ]

Key Learning Goals:

• Handle complex tree recursion
• Build trees from traversals
• Track global state during recursion

Graphs (31-36)

#	Problem	Difficulty	Pattern	LeetCode	Status
31	Number of Islands	M	DFS/BFS Grid	#200	[ ]
32	Clone Graph	M	BFS + Hash Map	#133	[ ]
33	Pacific Atlantic Water Flow	M	Multi-source BFS	#417	[ ]
34	Course Schedule	M	Topological Sort	#207	[ ]
35	Course Schedule II	M	Topological Sort	#210	[ ]
36	Graph Valid Tree	M	Union-Find	#261	[ ]

Key Learning Goals:

• Apply BFS/DFS to grids and graphs
• Detect cycles using multiple methods
• Implement Union-Find structure

Binary Search (37-39)

#	Problem	Difficulty	Pattern	LeetCode	Status
37	Search in Rotated Sorted Array	M	Modified Binary Search	#33	[ ]
38	Find Minimum in Rotated Sorted Array	M	Binary Search	#153	[ ]
39	Koko Eating Bananas	M	Binary Search on Answer	#875	[ ]

Key Learning Goals:

• Handle rotated arrays
• Apply binary search to answer spaces
• Recognize monotonic properties

Backtracking (40-42)

#	Problem	Difficulty	Pattern	LeetCode	Status
40	Subsets	M	Backtracking	#78	[ ]
41	Permutations	M	Backtracking	#46	[ ]
42	Combination Sum	M	Backtracking	#39	[ ]

Key Learning Goals:

• Master the backtracking template
• Handle duplicates and pruning
• Understand time complexity of exhaustive search

Dynamic Programming (43-50)

#	Problem	Difficulty	Pattern	LeetCode	Status
43	Climbing Stairs	E	Fibonacci DP	#70	[ ]
44	House Robber	M	1D DP	#198	[ ]
45	Coin Change	M	Unbounded Knapsack	#322	[ ]
46	Longest Increasing Subsequence	M	LIS Pattern	#300	[ ]
47	Word Break	M	String DP	#139	[ ]
48	Unique Paths	M	Grid DP	#62	[ ]
49	Longest Common Subsequence	M	2D DP	#1143	[ ]
50	Edit Distance	M	2D DP	#72	[ ]

Key Learning Goals:

• Define DP states clearly
• Implement 1D and 2D DP tables
• Optimize space when possible

---

Problem-Pattern Mapping

Quick reference for which pattern each problem uses:

By Pattern

Pattern	Problem Numbers
Two Pointers	6, 7, 14, 16
Sliding Window	8
Fast/Slow Pointers	15
Hash Map/Set	1, 3, 9, 10, 11, 12
Stack	18, 19, 20, 21
Binary Search	37, 38, 39
Tree DFS	22, 23, 25, 26, 27, 28, 30
Tree BFS	24, 29
Graph DFS/BFS	31, 32, 33
Topological Sort	34, 35
Union-Find	36
Backtracking	40, 41, 42
DP (1D)	43, 44, 45, 46, 47
DP (2D)	48, 49, 50

By Difficulty

Difficulty	Problems
Easy (11)	1, 2, 3, 9, 13, 14, 15, 18, 22, 23, 43
Medium (36)	4, 5, 6, 7, 8, 10, 11, 12, 16, 17, 19, 20, 24, 25, 26, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50
Hard (3)	21, 29, 30

---

Daily Practice Schedule

If You Have 2 Weeks

Day	Problems	Focus Area
Day 1	1-6	Arrays and Two Pointers
Day 2	7-12	Sliding Window and Hash
Day 3	13-17	Linked Lists
Day 4	18-21	Stacks
Day 5	22-25	Binary Trees
Day 6	26-30	Advanced Trees
Day 7	Review + Mock	Consolidation
Day 8	31-36	Graphs
Day 9	37-39	Binary Search
Day 10	40-42	Backtracking
Day 11	43-46	DP Basics
Day 12	47-50	DP Advanced
Day 13	Mixed Practice	Random Selection
Day 14	Review + Mock	Final Prep

If You Have 1 Week

Focus on starred problems (highest priority):

Day	Priority Problems
Day 1	1*, 4*, 6*, 8*
Day 2	13*, 15*, 18*, 20*
Day 3	24*, 25*, 27*
Day 4	31*, 34*
Day 5	40*, 41*, 42*
Day 6	44*, 45*, 49*
Day 7	Review + Mock

---

Solution Approach Notes

Problem 1: Two Sum

Pattern: Hash Map
Key Insight: Store seen numbers with their indices
Time: O(n), Space: O(n)
Edge Cases: Same element used twice, no solution

Problem 6: 3Sum

Pattern: Sort + Two Pointers
Key Insight: Fix one number, use two pointers for rest
Time: O(n^2), Space: O(1) or O(n) for sorting
Edge Cases: Duplicate triplets, all same numbers

Problem 21: Largest Rectangle in Histogram

Pattern: Monotonic Stack (Increasing)
Key Insight: For each bar, find left and right boundaries
Time: O(n), Space: O(n)
Edge Cases: Single bar, all same heights

Problem 34: Course Schedule

Pattern: Topological Sort (Kahn's Algorithm)
Key Insight: Build in-degree array, process zero-degree nodes
Time: O(V + E), Space: O(V + E)
Edge Cases: Cycle exists, single course, no prerequisites

Problem 45: Coin Change

Pattern: Unbounded Knapsack DP
Key Insight: dp[amount] = min coins to make amount
Time: O(amount * coins), Space: O(amount)
Edge Cases: Amount = 0, impossible amount

Problem 50: Edit Distance

Pattern: 2D String DP
Key Insight: dp[i][j] = min ops for word1[0:i] to word2[0:j]
Time: O(m*n), Space: O(m*n) or O(n) optimized
Edge Cases: Empty strings, identical strings

---

Progress Tracker

Week 1 Summary

Arrays/Strings:    ___/8  completed
Hash Tables:       ___/4  completed
Linked Lists:      ___/5  completed
Stacks/Queues:     ___/4  completed
Binary Trees:      ___/4  completed
Week 1 Total:      ___/25 completed

Week 2 Summary

Trees Advanced:    ___/5  completed
Graphs:            ___/6  completed
Binary Search:     ___/3  completed
Backtracking:      ___/3  completed
Dynamic Programming: ___/8  completed
Week 2 Total:      ___/25 completed

Overall Progress

Total Completed:   ___/50
Mastered (*):      ___/50
Need Review (~):   ___/50

Patterns Covered:
[ ] Two Pointers
[ ] Sliding Window
[ ] Fast/Slow Pointers
[ ] Hash Map/Set
[ ] Stack (including Monotonic)
[ ] Binary Search
[ ] Tree DFS/BFS
[ ] Graph DFS/BFS
[ ] Topological Sort
[ ] Union-Find
[ ] Backtracking
[ ] DP (1D and 2D)

---

Tips for Problem Solving

Before Coding

1. Read the problem twice
2. Identify the pattern (see Pattern Selection Flowchart)
3. Think about edge cases
4. Explain your approach verbally

During Coding

1. Start with a clear function signature
2. Write pseudocode comments first
3. Implement step by step
4. Handle edge cases explicitly

After Coding

1. Trace through with an example
2. Test edge cases
3. Analyze time and space complexity
4. Consider optimization opportunities

When Stuck

• 10 minutes: Look at the hint/pattern
• 20 minutes: Review the solution concept
• 30 minutes: Study the full solution, then implement yourself

---

Additional Resources

LeetCode Lists

• Blind 75 - Classic 75 problems
• Grind 75 - Optimized progression
• NeetCode 150 - With video explanations

Video Explanations

• NeetCode YouTube channel
• Take U Forward (Striver's A2Z)
• Back to Back SWE

Practice Platforms

• LeetCode Premium (recommended for company-tagged problems)
• Pramp (free mock interviews)
• Interviewing.io (paid mock interviews)

---

Track your progress daily and review Common Mistakes to avoid pitfalls.

---

Last updated: January 2026