Max House Area
Reported by candidates from HSBC's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
You've got a HSBC OA coming in the next day or two and they're asking about Max House Area. This is a spatial reasoning problem that looks like it's testing whether you can calculate or optimize area under constraints. The pattern isn't immediately obvious from the title alone, which is exactly the kind of thing that trips candidates up. StealthCoder exists precisely for moments like this: if you blank on the approach during the live assessment, you've got a safety net that can read the problem and walk you through the logic in real time.
Pattern and pitfall
Max House Area problems typically boil down to one of two things: either you're given dimensions and constraints and need to find the maximum possible area (which is often a math or brute-force optimization problem), or you're working with a grid or 2D structure and need to find the largest rectangular region that meets certain criteria. The latter leans toward matrix scanning or prefix sums. The key pitfall is overthinking it. Many candidates assume it's dynamic programming when it's actually just careful enumeration or a mathematical formula. During your OA, read the constraints first. If they're small (grid under 1000x1000), brute force with optimization usually works. If they're abstract (e.g., 'given perimeter, maximize area'), it's math. StealthCoder can parse the exact constraints and suggest the right bucket in seconds if you get stuck.
The honest play: practice the pattern, and have StealthCoder ready for the one you didn't see coming.
You can drill Max House Area cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built for the candidate who saw this exact problem leak two days before his OA and wondered if anyone had a play.
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Max House Area FAQ
Is this a DP problem or just math?+
Without seeing the full problem, it's likely neither. Most 'max area' problems at HSBC level are either brute-force grid scans or algebraic optimization. DP would be overkill unless the problem explicitly requires breaking it into overlapping subproblems. Read the constraints first.
What if the problem is about rectangles in a 2D grid?+
Common approach: iterate through all possible top-left and bottom-right corners, compute area, track max. For larger grids, consider a histogram-based approach or prefix sums to compute rectangle sums fast. The pattern is usually matrix or prefix-sum.
How do I prep in 24 hours if I don't have the exact problem?+
Study: maximal rectangle in a grid (LeetCode 85), largest rectangle in histogram (LeetCode 84), and basic area optimization with constraints. These cover most 'max area' variants. One solid example beats guessing.
What's the trick if the problem includes obstacles or invalid regions?+
Don't recompute from scratch each time. Use prefix sums to get cumulative area in O(1) after O(n*m) preprocessing. If obstacles are sparse, mark them and skip. Read the constraint size first to decide brute-force vs. optimization.
Will they ask for the area value or the dimensions?+
Usually both or just area. Return type matters. If they want coordinates of the optimal rectangle, track indices as well as the max value. Check the expected output format in the problem statement carefully before coding.