Data structures and algorithms form the backbone of every coding round in campus placements. Whether you are appearing for TCS, Infosys SP, Wipro, or Accenture, mastering the right set of DSA topics directly determines your coding round performance.
Which DSA Topics Are Actually Tested in Placements
Placement coding rounds are not LeetCode Hard sessions. The distribution based on reported student experiences: Arrays and Strings (35%), Mathematical Problems (20%), Basic Sorting and Searching (15%), Recursion and Basic DP (15%), Stacks, Queues, and Linked Lists (10%), Trees and Graphs (5%). Focus your energy proportionally.
Arrays: The Most Important Topic
Every placement coding round has at least one array problem. Core array techniques: two-pointer method (solves pair-sum, container with most water, remove duplicates), sliding window (maximum sum subarray, longest substring), prefix sum (range queries, subarray sum equals k), and sorting-based approaches (find all triplets, merge intervals).
Strings: High Frequency, Manageable Difficulty
Master: check anagram (character frequency map), check palindrome (two-pointer), find all permutations (backtracking), KMP algorithm for pattern matching, longest common subsequence, and Roman numeral conversions. String problems are reliably solvable with hashmaps and two-pointer techniques.
Sorting and Searching
Know the time complexity of all major algorithms: Bubble O(n²), Merge O(n log n), Quick O(n log n) average, Heap O(n log n). Binary search is tested far more than any sorting algorithm in placement rounds — master its variants: first and last occurrence, search in rotated sorted array, find square root using binary search.
Dynamic Programming: Smart Priority
Full DP mastery is not required for most placement tests. Focus on 5 canonical DP problems that cover 80% of what appears: 0/1 Knapsack, Longest Common Subsequence, Coin Change, Fibonacci with memoisation, and Climbing Stairs. Understand the principle of optimal substructure and overlapping subproblems — these are the conceptual tests that appear in interviews even when full coding is not required.
Recursion and Backtracking
Recursion appears in pattern printing, tree traversals, and combinatorial problems. Master the standard recursive structure: base case, recursive case, and how the call stack works. Backtracking is tested in: N-Queens, generate all subsets, generate all permutations, and Sudoku solver. These are SP-level problems — important for Infosys SP and Accenture technical tracks.
Big O Notation: What Interviewers Expect
Every technical interview includes “What is the time complexity of your solution?” Know common complexities: O(1) constant, O(log n) binary search, O(n) linear scan, O(n log n) merge sort, O(n²) nested loops, O(2ⁿ) exponential recursion. Practice stating the complexity of your solutions before the interviewer asks — it signals strong CS fundamentals.
Recommended Study Schedule
Week 1: Arrays and strings (solve 20 problems). Week 2: Sorting, searching, and hashing (solve 15 problems). Week 3: Recursion and basic DP (solve 15 problems). Week 4: Mock coding tests under timed conditions (solve 2 problems daily in 75 minutes). Review and fix weak areas throughout.