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Blinkit Placement Papers 2025

This page is a working set of Blinkit placement papers from 2025: from student reports questions, the 2025 online assessment pattern, and step-by-step solutions. Use it to see what Blinkit actually asked in the latest cycle, how hard the rounds were, and which themes (DSA, system design, aptitude, or role-specific topics) mattered most. Practice the problems below under timed conditions, then cross-check with the interview and preparation guides if you are targeting an upcoming Blinkit drive.

Section Questions Time Difficulty
Coding Problems 2-3 90 min Medium-Hard

Blinkit Placement Papers 2025 - actual questions & solutions

Section titled “Blinkit Placement Papers 2025 - actual questions & solutions”

This section contains practice questions styled on Blinkit placement papers 2025 (recent-cycle pattern), with worked solutions. Use them as timed sectional drills - from student reports drives vary by college and role, so treat this as a high-signal practice bank, not an official paper dump.

Show solution

Problem Statement: Given a string, return it reversed.

Example:

Input: "placement"
Output: "tnemecalp"

Solution (Java):

public String reverse(String s) {
return new StringBuilder(s).reverse().toString();
}

Time Complexity: O(n)
Space Complexity: O(n)

Show solution

Problem Statement: Merge two sorted linked lists and return a new sorted list.

Example:

Input: 1→2→4 , 1→3→4
Output: 1→1→2→3→4→4

Solution (Java):

public ListNode mergeTwoLists(ListNode a, ListNode b) {
ListNode dummy = new ListNode(0), cur = dummy;
while (a != null && b != null) {
if (a.val <= b.val) { cur.next = a; a = a.next; }
else { cur.next = b; b = b.next; }
cur = cur.next;
}
cur.next = (a != null) ? a : b;
return dummy.next;
}

Time Complexity: O(n + m)
Space Complexity: O(1)

Show solution

Problem Statement: You can climb 1 or 2 steps. How many distinct ways to climb n stairs?

Example:

Input: n = 4
Output: 5

Solution (Java):

public int climbStairs(int n) {
if (n <= 2) return n;
int a = 1, b = 2;
for (int i = 3; i <= n; i++) {
int c = a + b; a = b; b = c;
}
return b;
}

Time Complexity: O(n)
Space Complexity: O(1)

Show solution

Problem Statement: Given a string of brackets, determine if it is valid.

Example:

Input: "()[]{}"
Output: true

Solution (Java):

public boolean isValid(String s) {
Deque<Character> st = new ArrayDeque<>();
Map<Character, Character> pair = Map.of(')', '(', ']', '[', '}', '{');
for (char c : s.toCharArray()) {
if (pair.containsValue(c)) st.push(c);
else if (st.isEmpty() || st.pop() != pair.get(c)) return false;
}
return st.isEmpty();
}

Time Complexity: O(n)
Space Complexity: O(n)

Show solution

Problem Statement: Return the level-order traversal of a binary tree.

Example:

Input: [3,9,20,null,null,15,7]
Output: [[3],[9,20],[15,7]]

Solution (Java):

public List<List<Integer>> levelOrder(TreeNode root) {
List<List<Integer>> res = new ArrayList<>();
if (root == null) return res;
Queue<TreeNode> q = new ArrayDeque<>();
q.add(root);
while (!q.isEmpty()) {
int sz = q.size();
List<Integer> level = new ArrayList<>();
for (int i = 0; i < sz; i++) {
TreeNode n = q.poll();
level.add(n.val);
if (n.left != null) q.add(n.left);
if (n.right != null) q.add(n.right);
}
res.add(level);
}
return res;
}

Time Complexity: O(n)
Space Complexity: O(n)

Show solution

Problem Statement: Find the longest common prefix string amongst an array of strings.

Example:

Input: ["flower","flow","flight"]
Output: "fl"

Solution (Java):

public String longestCommonPrefix(String[] strs) {
if (strs.length == 0) return "";
String pref = strs[0];
for (int i = 1; i < strs.length; i++) {
while (!strs[i].startsWith(pref)) {
pref = pref.substring(0, pref.length() - 1);
if (pref.isEmpty()) return "";
}
}
return pref;
}

Time Complexity: O(S)
Space Complexity: O(1)

Show solution

Problem Statement: Find the contiguous subarray with the largest sum.

Example:

Input: [-2, 1, -3, 4, -1, 2, 1, -5, 4]
Output: 6 // [4, -1, 2, 1]

Solution (Java):

public int maxSubArray(int[] nums) {
int best = nums[0], cur = nums[0];
for (int i = 1; i < nums.length; i++) {
cur = Math.max(nums[i], cur + nums[i]);
best = Math.max(best, cur);
}
return best;
}

Time Complexity: O(n)
Space Complexity: O(1)

Q8: Virtual memory is typically implemented using?

Solution:

OS uses demand paging (and sometimes segmentation) to implement virtual memory.

Answer: Demand paging

Q9: Which normal form removes transitive dependency?

Solution:

1NF: atomic values. 2NF: no partial dependency. 3NF: no transitive dependency.

Answer: 3NF

Q10: Worst-case time complexity of quicksort is?

Solution:

Unbalanced partitions (already sorted with bad pivot) → O(n²).

Answer: O(n²)

Q11: Which SQL clause filters grouped rows after GROUP BY?

Solution:

HAVING filters aggregates; WHERE filters rows before grouping.

Answer: HAVING

Key insights from 2025 Blinkit Online Assessment

Section titled “Key insights from 2025 Blinkit Online Assessment”
  1. Coding Section is Critical: Must solve 2-3 coding problems correctly to advance
  2. Quick Commerce Architecture Focus: Strong emphasis on quick commerce systems, inventory allocation, delivery optimization, logistics
  3. Time Management: 2-3 problems in 90 minutes requires excellent speed and accuracy
  4. Success Rate: Only 10-15% cleared OA and advanced to interviews
  5. Platform: Blinkit assessment platform or HackerRank
  6. Focus Areas: Arrays, trees, graphs, dynamic programming, quick commerce architecture, inventory allocation
  7. Enhanced Emphasis: Optimal solutions, quick commerce architecture, and inventory allocation system design

Based on recent candidate experiences from 2025 Blinkit interviews:

2025 Interview Process:

  1. Online Assessment (90 minutes): 2-3 coding problems
  2. Technical Phone Screen (45-60 minutes): Coding problems, algorithm discussions, quick commerce concepts, inventory allocation
  3. Onsite/Virtual Interviews (4-5 rounds, 45-60 minutes each):
  • Coding rounds (2-3): Algorithms, data structures, problem-solving
  • System Design rounds: Quick commerce architecture, inventory allocation systems, delivery optimization, logistics systems
  • Behavioral rounds: Problem-solving approach, quick commerce passion, impact

2025 Interview Trends:

  • Increased emphasis on quick commerce architecture and inventory allocation system design
  • More focus on optimal solutions and modern quick commerce technologies
  • Enhanced behavioral questions about innovation and quick commerce passion
  • Questions about quick commerce architecture and inventory allocation systems

Common 2025 Interview Topics:

  • Coding: Arrays, strings, trees, graphs, dynamic programming, inventory allocation algorithms
  • System Design: Quick commerce architecture, inventory allocation systems, delivery optimization, logistics systems
  • Behavioral: Problem-solving, quick commerce passion, teamwork, impact
  • Blinkit Technologies: Quick commerce architecture, inventory allocation systems, delivery optimization, logistics systems

Success Tips:

  • Strong coding performance is essential - solve problems optimally
  • Understand quick commerce concepts, inventory allocation, and quick commerce architecture
  • Practice system design for quick commerce architecture and inventory allocation systems
  • Prepare examples demonstrating problem-solving and quick commerce passion
  • Learn Blinkit’s products and quick commerce technologies
  • Practice explaining your thought process clearly

For detailed interview experiences from 2025, visit Blinkit Interview Experience page.

  1. Master Coding Fundamentals: Focus on solving 2-3 coding problems correctly - arrays, trees, graphs, DP
  2. Quick Commerce Architecture Expertise: Strong understanding of quick commerce architecture, inventory allocation systems, delivery optimization
  3. Practice Previous Year Papers: Solve Blinkit OA papers from 2020-2025 to understand evolving patterns
  4. Time Management: Practice completing 2-3 coding problems in 90 minutes
  5. LeetCode Practice: Solve 200+ LeetCode problems focusing on arrays, strings, trees, graphs (medium-hard difficulty)
  6. Quick Commerce Focus: Practice problems related to quick commerce systems and inventory allocation
  7. System Design Mastery: Learn quick commerce architecture design, inventory allocation systems, delivery optimization
  8. Blinkit Technologies: Learn quick commerce architecture, inventory allocation systems, delivery optimization, logistics systems
  9. Behavioral Preparation: Prepare examples using STAR format - problem-solving, quick commerce passion, impact
  10. Mock Tests: Take timed practice tests to improve speed and accuracy

Zomato · Swiggy · Flipkart · Paytm · Phonepe · Razorpay


Practice 2025 papers to stay updated with latest patterns and prepare effectively!