The interview process consisted of an online coding round followed by a technical interview. The coding round focused on data structures and problem-solving. In the technical interview, the interviewer discussed my approach, asked follow-up questions, and tested my understanding of core concepts.
Interview questions [1]
Question 1
They asked a graph problem based on Union Find (Disjoint Set Union), where I had to detect connected components and explain path compression and union by rank.
Revise DSA specially Linked Lists and Stacks
core CS fundamentals mostly DBMS(basic) and OS
Revise sorting algorithms. Try to solve question faster if you ain't sure be frank and ask interviewer to ask something else. Be calm and confident.
I applied through college or university. The process took 1 day. I interviewed at Adobe (Rājpura, Punjab) in Aug 2025
Interview
Adobe’s internship process (₹115K stipend) began with an in-campus online assessment on HackerRank where candidates had to solve 37 questions in 90 minutes out of a total 63 questions across 6 sections (A, B, and F compulsory, one choice among C, D, and E). The paper included core CS subjects (OS, CN, DBMS) with OS questions on page replacement (LRU/MRU), threads/processes, and TLB formulas; CN questions were tricky with protocol and command-based problems; and DBMS was largely code-driven. Another section covered NALR aptitude (number systems, probability, directions, ratios, graphs, etc.). Candidates also faced 13 questions each in C++, Java, and Python, mostly predicting code outputs (C++ being easier, Java tougher with Spring-Boot/Servlets). Finally, there were 2 DSA problems—computing total XOR sum of all subarrays (optimized using prefix XOR) and finding the longest subsequence with total AND > 0 (best solved with DP tabulation). Wrong MCQs carried a ¼ mark penalty, making accuracy as important as speed.
Interview questions [1]
Question 1
1. Total XOR Sum of All Subarrays – Compute the XOR of every possible subarray and return the total sum. A prefix-XOR approach is needed to optimize beyond the brute force O(n²) solution.
2. Longest Subsequence with AND > 0 – Find the maximum-length subsequence such that the bitwise AND of all its elements remains greater than zero, best solved using a DP/tabulation approach.