Roblox OA 2026 Real Experience: 2 High-Frequency Questions + Solutions + Code

With Roblox 2026 internship and full-time applications in full swing, many candidates are hitting the Online Assessment (OA) as their first major hurdle. Here’s a fresh breakdown of two common coding problems that recently appeared: a 4×4 submatrix missing value problem and a stock bot revenue maximization problem.

The questions are not extremely difficult, but small implementation details and edge cases can easily cost valuable time under pressure.

Quick Overview of Roblox Interview Process

Resume submission → Initial screening → Online Assessment → Recruiter call → 1–2 technical rounds + system design / behavioral → Offer

The OA is a key filter. Clean code, correct logic, and solid boundary handling matter a lot more than just getting something working.

Problem 1: Missing Value in 4×4 Submatrices and Rearrangement

Problem Summary

You are given a large matrix composed of multiple 4×4 blocks. Each block should contain unique numbers from 1 to 16, but exactly one number is missing.

Your tasks:

Find the missing number in each block
Sort blocks by missing value in ascending order (stable order for ties)
Reassemble the sorted blocks into a new matrix

Key Insight

Each 4×4 block should sum to 136. Subtracting the actual sum from 136 gives the missing value instantly.

Python Solution

def solution(mat):
    if not mat or not mat[0]:
        return []
    block_size = 4
    num_blocks = len(mat[0]) // block_size
    sub_matrices = []
    
    for i in range(num_blocks):
        sub = [row[block_size * i : block_size * (i + 1)] for row in mat]
        total_sum = sum(sum(row) for row in sub)
        missing = 136 - total_sum
        sub_matrices.append((missing, sub))
    
    sub_matrices.sort(key=lambda x: x[0])
    
    result = []
    for r in range(block_size):
        new_row = []
        for _, sub in sub_matrices:
            new_row.extend(sub[r])
        result.append(new_row)
    return result

Problem 2: Maximize Stock Bot Revenue

Problem Summary

You are given two arrays:

prices: daily stock prices
algo: 0 = buy, 1 = sell

You can choose one consecutive window of k days and force all of them to sell. Return the maximum possible revenue.

Key Insight

Original revenue: sell = +price, buy = -price
Changing buy → sell adds +2 × price
Use sliding window to find max gain

Python Solution

def solution(prices, algo, k):
    if not prices or k <= 0:
        return 0
    n = len(prices)
    
    original = sum(p if a == 1 else -p for p, a in zip(prices, algo))
    
    changes = [2 * p if a == 0 else 0 for p, a in zip(prices, algo)]
    
    if k > n:
        k = n
        
    max_gain = current = sum(changes[:k])
    
    for i in range(k, n):
        current += changes[i] - changes[i - k]
        if current > max_gain:
            max_gain = current
    
    return original + max_gain

Common Pitfalls

Empty input handling
k greater than array length
Stable sorting requirements
Sliding window off-by-one errors

How to Prepare After Passing Roblox OA

Clearing the OA is just the first step. The next rounds focus more on coding depth, system design, and communication.

Improve code quality: clean structure, readable variables, minimal bugs
Practice under time pressure: simulate full OAs
Review system design basics: scalability, real-time systems
Prepare behavioral stories: ownership, teamwork, problem-solving

Many candidates also choose to accelerate their preparation with structured guidance and real-time assistance. If you’re looking for targeted help with OA, coding interviews, or even live support during critical rounds, you can check:

ProgramHelp Interview Assistance Services

They provide support across OA, coding interviews, and system design rounds, which can be especially helpful when you’re aiming for top-tier offers under tight timelines.