How to Improve Your Algorithmic Thinking
Algorithmic thinking is crucial for solving complex coding problems efficiently. Whether you're preparing for coding interviews, competitive programming, or just sharpening your problem-solving skills, here’s a structured approach to improving your algorithmic thinking.
1️⃣ Master the Fundamentals of Data Structures & Algorithms 📚
Before tackling problems, ensure you understand these key concepts:
✔ Data Structures: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Hash Tables
✔ Algorithms: Sorting (Merge Sort, Quick Sort), Searching (Binary Search), Recursion, Dynamic Programming (DP), Greedy Algorithms
💡 Example: Knowing hash tables helps solve problems involving fast lookups (e.g., finding duplicates in an array).
2️⃣ Practice Pattern Recognition 🔍
✔ Recognize common problem types:
- Sliding Window → Optimal for subarray problems
- Two Pointers → Great for sorted arrays & linked lists
- Backtracking → Used in permutations & combinations
- Dynamic Programming (DP) → When problems involve overlapping subproblems
✔ Solve problems by category – Don't just solve problems randomly; instead, focus on one pattern at a time.
💡 Example: Leetcode 121 (Best Time to Buy and Sell Stock) → A classic Kadane’s Algorithm problem.
3️⃣ Develop a Structured Problem-Solving Approach 🧠
1️⃣ Understand the Problem – Read carefully, identify input/output constraints.
2️⃣ Break it Down – Decompose it into smaller subproblems.
3️⃣ Think of Brute Force First – Find the simplest approach before optimizing.
4️⃣ Identify an Optimal Strategy – Use pattern recognition & known algorithms.
5️⃣ Implement & Optimize – Code the solution, analyze complexity, and refine.
💡 Example: For Graph Traversal problems:
- Brute Force → DFS (Depth-First Search)
- Optimized → BFS (Breadth-First Search) for shortest path
4️⃣ Solve a Variety of Problems Regularly 🏋️♂️
✔ Use structured platforms:
- Beginner: LeetCode (Easy), CodeSignal, HackerRank
- Intermediate: LeetCode (Medium), Codeforces
- Advanced: AtCoder, Codeforces (Div 2 & 1), Google Kickstart
✔ Aim for at least 1-2 problems per day to build consistency.
💡 Suggested Leetcode List:
🔹 Easy: Two Sum, Valid Parentheses, Merge Two Sorted Lists
🔹 Medium: Longest Substring Without Repeating Characters, 3Sum, Binary Tree Zigzag Level Order Traversal
🔹 Hard: Edit Distance, Maximum Flow, N-Queens
5️⃣ Learn to Optimize with Time & Space Complexity ⏳
✔ Always analyze Big-O complexity after solving a problem.
✔ Try to reduce nested loops, use hash tables for O(1) lookups, and optimize recursive solutions with memoization.
✔ Compare different approaches (e.g., DP vs. Greedy).
💡 Example:
- Brute force approach → O(N²) (nested loops)
- Optimized approach → O(N log N) (sorting + two pointers)
6️⃣ Read & Analyze Other People’s Solutions 📖
✔ Study top-rated solutions on platforms like LeetCode Discuss, GeeksForGeeks, and Codeforces Editorials.
✔ Understand different coding styles and optimizations used by top programmers.
💡 Example: You might solve a problem in O(N²), but a top solution may use O(N log N) with sorting + binary search.
7️⃣ Compete & Challenge Yourself 🚀
✔ Join coding competitions:
- Beginner: Google Kickstart, Codeforces (Div 3), Leetcode Contests
- Intermediate: Codeforces (Div 2), AtCoder
- Advanced: ICPC, Google Code Jam, TopCoder
✔ Competing improves problem-solving under pressure and exposes you to unique problems.
💡 Example: Competitive programmers like Gennady Korotkevich (tourist) are exceptional due to regular contests & problem-solving practice.
💡 TL;DR – Algorithmic Thinking Roadmap
✅ Master Data Structures & Algorithms – Understand key concepts.
✅ Recognize Problem-Solving Patterns – Sliding Window, DP, Two Pointers.
✅ Follow a Structured Approach – Read, break down, optimize.
✅ Practice Consistently – Solve 1-2 problems daily on LeetCode or Codeforces.
✅ Analyze Time Complexity – Optimize solutions for efficiency.
✅ Study Others’ Code – Learn from top solutions & coding editorials.
✅ Join Coding Contests – Compete to improve speed and problem-solving.