How to Crack HP Coding Interviews in 2026

HP coding interviews focus on practical problem-solving with a strong emphasis on foundational data structures and algorithms. The process typically involves one or two technical rounds, often conducted via a collaborative coding platform, where you'll be expected to write clean, efficient code and discuss your approach. The questions are designed to assess how you think, not just whether you get the correct answer.

By the Numbers — Difficulty Breakdown and What It Means

Based on recent patterns, the difficulty distribution is clear: 75% Easy and 25% Medium questions, with 0% Hard. This is a critical insight. HP is not trying to stump you with obscure graph theory or complex dynamic programming. Instead, they are testing for strong fundamentals, clean code, and reliability.

The absence of Hard questions means your preparation should prioritize mastery over breadth. You need to be flawless on the basics. A single buggy solution on an Easy string manipulation problem will hurt you more than an incomplete attempt at a Hard DP problem would at other companies. The focus is on correctness, efficiency for the given constraints, and clear communication.

Top Topics to Focus On

The data shows a concentrated set of high-probability topics. Depth in these areas is non-negotiable.

• String: Expect operations like reversal, palindrome checks, and character counting. Master two-pointer techniques and efficient iteration.
• Array: The most fundamental structure. Be ready for tasks involving searching, in-place modification, and subarray calculations.
• Hash Table: Your go-to tool for achieving O(1) lookups to solve problems involving frequency counting, duplicates, or complements (like Two Sum).
• Sliding Window: A crucial pattern for optimizing problems dealing with contiguous subarrays or substrings, often used with Strings and Arrays.
• Greedy: A problem-solving approach where you make the locally optimal choice at each step, often used for scheduling or interval problems.

The Sliding Window pattern is particularly powerful for combining String and Array topics. Here is a classic example: finding the length of the longest substring without repeating characters.

def length_of_longest_substring(s: str) -> int:
    char_set = set()
    left = 0
    max_length = 0

    for right in range(len(s)):
        # If duplicate found, shrink window from left
        while s[right] in char_set:
            char_set.remove(s[left])
            left += 1
        # Add new char and update max length
        char_set.add(s[right])
        max_length = max(max_length, right - left + 1)

    return max_length

Preparation Strategy — A 4-6 Week Study Plan

Given the topic focus, a targeted plan is effective.

Weeks 1-2: Foundation & Core Topics

• Days 1-7: Drill Array and Hash Table problems. Implement common operations from scratch. Solve at least 15-20 problems, focusing on Easy and Medium.
• Days 8-14: Master String manipulations and the Sliding Window pattern. Practice the example above until the logic is automatic. Complete another 15-20 problems.

Weeks 3-4: Integration & Pattern Recognition

• Focus on Greedy algorithms and problems that mix topics (e.g., a Hash Table used to optimize an Array search).
• Start doing timed practice sessions with 2-3 problems in 60 minutes to simulate the interview pace. Prioritize Medium difficulty to build confidence.

Weeks 5-6: Mock Interviews & Refinement

• Conduct at least 3-5 mock interviews with a peer or using recorded sessions. Explain your thinking out loud.
• Re-solve your initial problem set, focusing on writing bug-free code on the first try. Polish your approach to edge cases (empty strings, single-element arrays).

Key Tips

1. Prioritize Correctness Over Cleverness. With 75% Easy questions, a brute-force solution that works is often better than an optimal one with bugs. Get a working solution first, then optimize if needed and if time permits.
2. Communicate Before You Code. State your assumptions, outline your approach (e.g., "I'll use a hash map to store indices for O(1) lookups"), and discuss the time/space complexity. This shows structured thinking.
3. Test with Edge Cases. Before declaring your solution done, verbally run through tests: empty input, single element, large input, sorted/unsorted data. This demonstrates thoroughness.
4. Know Your Language's Standard Library. Be fluent in the core utilities for your chosen language (e.g., Python's collections.Counter, Java's HashMap, JavaScript's Set/Map) to avoid re-implementing basic functionality.

The HP interview is a test of fundamental proficiency. Master the core topics, practice clear communication, and write robust code. You don't need to know every algorithm—you need to execute the common ones perfectly.

Browse all HP questions on CodeJeet