DSA Sheet for Placements 2026: 90-Day Plan [Free]

If you are a 2026 placement aspirant wondering which DSA topics to prioritise, this guide answers that question with data, not guesswork. It covers the complete DSA sheet, topic-wise question frequency from recent drives, a 90-day prep plan, and 7 practice problems in PapersAdda format.

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What Is a DSA Sheet for Placements?

A DSA (Data Structures and Algorithms) sheet is a curated, topic-wise list of coding problems that covers the patterns companies actually test in online assessments and technical interviews. Unlike random problem dumps, a placement-focused DSA sheet is:

• Scoped, only problems types that appear in SDE-1 / Analyst hiring rounds
• Ordered, from foundational (arrays, strings) to advanced (graphs, DP)
• Pattern-driven, teaches the underlying template, not just a solution

In 2026, almost every tier-1 and tier-2 company conducts a coding round before the interview. A well-structured DSA sheet is the single highest-leverage tool you have. If you are still building foundational aptitude alongside DSA, pair this with the OA cheat sheet for campus hiring 2026.

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Topic-Wise Question Frequency Analysis (2022–2026)

The table below is compiled from verified candidate reports shared across placement forums, Glassdoor interview entries, and PapersAdda community submissions. Frequencies are estimated ranges based on 2022–2025 drives; 2026 figures are projections.

Topic	Avg. Questions per OA (2022–2024)	% OAs Including This Topic (est.)	2026 Trend
Arrays & Strings	2–3	95%	Stable
Linked Lists	1–2	70%	Stable
Stacks & Queues	1–2	65%	Stable
Binary Search	1–2	80%	Rising
Two Pointers / Sliding Window	1–2	75%	Rising
Trees & BST	1–2	72%	Stable
Graphs (BFS/DFS)	1–2	60%	Rising
Dynamic Programming	1–3	55%	Rising
Recursion & Backtracking	1	45%	Stable
Heaps / Priority Queue	1	40%	Rising
Tries & Hashing	1	35%	Stable
Greedy	1	50%	Stable

Key insight: Binary search and sliding window have seen the sharpest frequency increase from 2023 to 2025 drives at product companies (Flipkart, Swiggy, Meesho). DP appeared in 55% of tier-1 OAs in 2024–25, up from ~38% in 2022. Nail these three patterns before anything else.

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The Complete DSA Sheet, Topic-Wise Problem List

Work through these in the order listed. Each topic links to the pattern it teaches, master the pattern, then apply it across problems.

1. Arrays & Strings (Foundation, Week 1)

Problem	Pattern
Two Sum	Hashing
Best Time to Buy and Sell Stock	Kadane variant
Maximum Subarray	Kadane's algorithm
Product of Array Except Self	Prefix/suffix product
3Sum	Two pointers
Longest Substring Without Repeating Characters	Sliding window
Valid Anagram	Frequency map
Group Anagrams	Hashing
Rotate Array	In-place manipulation
Merge Intervals	Sort + greedy

For string manipulation templates, the Java cheat sheet and Python cheat sheet have ready-to-use code snippets for common operations.

2. Binary Search (Week 1–2)

Problem	Pattern
Search in Rotated Sorted Array	Modified binary search
Find Minimum in Rotated Array	Modified binary search
Kth Smallest in Matrix	Binary search on answer
Median of Two Sorted Arrays	Hard, binary search
Capacity to Ship Packages	Binary search on answer

Binary search on the answer (not index) is the pattern that differentiates average candidates from strong ones. Practice at least 5 problems of this type.

3. Linked Lists (Week 2)

Reverse linked list, detect cycle (Floyd's algorithm), merge two sorted lists, find middle node, LRU cache implementation. LRU cache is a favourite at Amazon, Uber, and Atlassian, it tests both linked list and hashing simultaneously.

4. Stacks & Queues (Week 2–3)

Valid parentheses, min stack, daily temperatures (monotonic stack), largest rectangle in histogram, sliding window maximum (deque). Monotonic stack is the single most underestimated pattern, it appears in roughly 1-in-3 medium–hard OA rounds at product companies.

5. Trees & BST (Week 3)

Inorder/preorder/postorder traversal (iterative preferred in interviews), level order BFS, lowest common ancestor, validate BST, diameter of binary tree, serialize/deserialize. If you are strong with recursion, trees feel natural, they are just recursive sub-problems on left and right children.

6. Graphs (Week 4)

BFS/DFS templates, number of islands, clone graph, detect cycle in directed/undirected graph, topological sort (Kahn's algorithm), shortest path (Dijkstra). Topological sort appeared in OAs at Razorpay, Juspay, and Thoughtworks in 2024–25.

7. Dynamic Programming (Week 4–6)

Sub-pattern	Representative Problems
1D DP	Climbing stairs, house robber, coin change
2D DP	Unique paths, edit distance, LCS
Knapsack	0/1 knapsack, partition equal subset
DP on strings	Palindromic substrings, longest palindromic subsequence
DP on intervals	Matrix chain multiplication, burst balloons

DP is where most candidates lose rank in competitive OAs. Do not skip the sub-patterns, the 1D → 2D → interval progression is the correct learning order.

For coding interview patterns more broadly, bookmark the coding interview patterns cheat sheet 2026, it covers templates for all the above in a single reference page.

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90-Day Prep Strategy for 2026 Placements

Spread your DSA prep across three phases. This timeline assumes 2–3 hours of focused practice per day.

Phase	Duration	Focus	Target Outcome
Foundation	Day 1–30	Arrays, strings, binary search, linked lists, stacks	Solve any easy + most mediums without hints
Core Patterns	Day 31–60	Trees, graphs, heaps, two pointers, sliding window	Clear OA rounds at service companies (TCS, Infosys, Wipro) + most tier-2 product
Advanced	Day 61–90	DP (all sub-patterns), backtracking, tries, greedy	Clear OA rounds at tier-1 product companies

Daily routine that works: 1 problem from the sheet (timed, 30–45 min) → read the editorial if stuck → implement the optimal solution from scratch → note the pattern. Never look at the solution before attempting.

Companies you are targeting will determine how deep into advanced patterns you need to go. The top 100 companies for placements 2026 has a tier-wise breakdown with the typical difficulty of their coding rounds.

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Platform Comparison, Where to Practice

Platform	Best For	Difficulty Control	Company Tags
LeetCode	Industry standard, most OAs mirror it	Excellent	Yes (premium)
Codeforces	Competitive programming, speed	Excellent (by rating)	No
GeeksforGeeks	Indian company questions	Good	Yes
HackerEarth	Exact OA simulation	Good	Yes
Coding Ninjas	Guided sheets with hints	Good	Partial

For 2026 campus placements, LeetCode remains the default. A realistic target: 150–180 problems (30–40 easy, 100–120 medium, 20–25 hard) is sufficient for 90% of campus OAs. Do not chase problem count, chase pattern coverage.

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Practice Questions

Common Mistakes to Avoid

1. Practising without a timer. Every company OA is time-bounded. Solving problems without time pressure builds false confidence. From week 2 onwards, enforce a 30-minute hard limit per problem.

2. Over-indexing on hard problems before mastering mediums. In 2025 OA data (based on verified candidate reports), 60–70% of problems in campus OAs were medium difficulty. Solving 30 hard problems while skipping 50 mediums is a losing strategy for campus hiring.

3. Skipping implementation of standard algorithms. Knowing Dijkstra's algorithm conceptually but not being able to code it from scratch in 20 minutes will cost you in timed rounds. Implement every algorithm in the sheet at least once without reference.

4. Ignoring edge cases in code. Empty array, single element, negative numbers, overflow, interviewers at product companies specifically check edge case handling. Build the habit of listing edge cases before writing any code.

5. Jumping between languages. Pick one language and stick to it, Java or Python for most candidates. Code written in a familiar language is 30–40% faster than code written in an unfamiliar one, and speed matters in OAs. The Java cheat sheet and Python cheat sheet both cover the standard library functions you will need.

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Related Resources

If you are building a complete placement prep stack alongside DSA, these resources are directly relevant:

• How to prepare for campus placements 2026, end-to-end roadmap covering aptitude, GD, and HR rounds
• How to prepare for placements 2026, off-campus variant with company-specific strategy
• OA cheat sheet for campus hiring 2026, quick reference for online assessment patterns
• Coding interview patterns cheat sheet 2026, all major problem patterns in one sheet
• Quantitative aptitude formulas cheat sheet 2026, for the aptitude section that precedes coding in most drives
• Top 100 companies for placements 2026, tier-wise list with package ranges and OA difficulty
• C++ cheat sheet, STL reference for competitive programmers using C++
• JavaScript cheat sheet, for roles targeting frontend or full-stack positions

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FAQs

Q: Which DSA sheet should I follow in 2026, Striver's, Love Babbar's, or a custom one?

Any structured sheet that covers the patterns in the topic list above will work. The difference between popular sheets is mostly ordering and problem selection, not coverage. What matters is completing the sheet you start, abandoning one sheet for another halfway through is the most common reason candidates end placements underprepared.

Q: How many LeetCode problems are enough for campus placements?

Based on verified candidate reports from 2024–25 drives: 150–180 problems with strong pattern understanding clears OA rounds at 90%+ of campus-visiting companies. Beyond 250 problems, the marginal benefit diminishes unless you are targeting Google, Jane Street, or similar firms with genuinely hard rounds.

Q: Can I clear placements with only Python?

Yes. Python is accepted in all major campus OAs including TCS, Infosys, Wipro, Cognizant, Capgemini, and most product companies. The only caveat: Python's slower execution speed can cause TLE on problems with large constraints (n > 10⁷) if you use O(n log n) where O(n) is expected. Know when to use PyPy if the platform supports it.

Q: Is DP mandatory for 2026 campus placements?

For tier-2 product companies and above, yes. In 2024–25 OA data, DP appeared in roughly 55% of product company drives. For service companies (TCS Digital, Infosys SP, Wipro Elite), DP is rare but not unheard of. If you are targeting only service companies, a strong foundation in arrays, binary search, and graphs is sufficient.

Q: What is the ideal split between time spent on DSA vs. other placement topics?

For a 6-month prep window: 50% DSA, 20% aptitude and reasoning, 15% core CS subjects (OS, DBMS, CN), 15% project/resume. For a 3-month window, compress to 60% DSA and deprioritise theory if your target companies do not test it. The how to prepare for placements 2026 article has a week-by-week schedule for the 3-month track.

Q: How do I handle a DSA problem I have never seen before in an OA?

Identify the pattern first, not the solution. Ask: does this involve a sorted array (binary search)? A sequence with an optimal prefix/suffix property (prefix sum or DP)? Connected nodes (graph)? Overlapping sub-problems (DP or memoisation)? Mapping this to a known pattern in the first 5 minutes of reading a problem is the skill that separates candidates who clear OAs from those who do not.

Q: Should I memorise code or understand patterns?

Understand patterns, not code. Companies rotate problem variants constantly, the exact problem you practised will rarely appear. But the sliding window template, the BFS level-order template, and the Kadane's algorithm template are reusable across hundreds of variants. Write each template from scratch at least five times until you can produce it under exam pressure without thinking.