Calculate Min Satellites Required
Reported by candidates from Google's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
You've got a Google OA in your inbox from December 2024, and satellite coverage is on the table. This one looks like a geometry or greedy problem at first glance, but it's really about coverage and optimization. The trap is thinking locally when you need to think about global coverage. You're looking for the minimum number of satellites to cover all target locations, and the geometry is just the wrapper. If you blank during the live OA, StealthCoder will read the exact constraints and hand you the pattern in seconds.
Pattern and pitfall
The core challenge is a coverage minimization problem. You're given target locations (likely as coordinates) and need to place satellites such that all targets fall within their coverage radius. This is a classic greedy + geometry hybrid. Sort targets by position, then greedily place each satellite as far right as possible while still covering the leftmost uncovered target. The key insight is that you never need to backtrack. Once you place a satellite, it's final. The geometry part is calculating whether a point falls within a circle or the coverage zone, but the actual algorithm is greedy selection. Common mistake: trying to optimize satellite positions mathematically when a sweep-line greedy approach solves it in linear time. StealthCoder becomes valuable here if you freeze on the greedy step or miscalculate overlap during the live assessment.
Drill it cold or hedge it with StealthCoder. Either way, don't walk into the OA hoping you remember the trick.
You can drill Calculate Min Satellites Required 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. Made for the candidate who got the OA invite this morning and has 72 hours, not six months.
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Google reuses patterns across OAs. Made for the candidate who got the OA invite this morning and has 72 hours, not six months. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Calculate Min Satellites Required FAQ
Is this actually a geometry problem or a greedy algorithm?+
It's greedy first, geometry second. The hard part is the greedy strategy: sort targets, then place satellites to cover as much as possible without backtracking. Geometry just calculates coverage zones. If you start writing a complex coordinate geometry solution, you're overthinking it.
What's the time complexity I should aim for?+
O(n log n) from sorting, then O(n) for the greedy pass. Don't write anything quadratic. If your solution is O(n^2), you're re-solving coverage for every satellite placement instead of building up incrementally.
How do I handle the coverage radius calculation?+
It depends on the input format. If satellites cover a circular zone, use Euclidean distance. If it's a 1D line (targets on a line, satellites project coverage), it's simpler. Read the exact constraint and don't over-generalize. Test with the examples first.
Will they ask me to optimize satellite positions too?+
Possibly. That's where the geometry gets real. You may need to calculate the optimal position for each satellite given a set of targets it must cover. This is usually solved by finding the leftmost and rightmost target, then placing the satellite such that both are covered.
Is this question still being asked at Google in late 2024?+
Yes, as of December 2024. Satellite and coverage problems are evergreen at Google because they're real infrastructure questions. The pattern doesn't go stale. Focus on the greedy + geometry combo.