Maximum Star Sum of a Graph
A medium-tier problem at 41% community acceptance, tagged with Array, Greedy, Graph. Reported in interviews at Akuna Capital and 0 others.
Maximum Star Sum hits you when you need to optimize node selections in a graph structure, and it's not a straightforward DP problem. You pick a center node and sum its neighbors, but only the profitable ones. Akuna Capital has asked it. The acceptance rate sits at 40%, which means half the candidates who attempt it get stuck on whether to include or exclude low-value neighbors. If this lands in your assessment and you haven't drilled the greedy sorting trick, StealthCoder surfaces a working solution invisible to the proctor, letting you move forward without the penalty of a failed submission.
Companies that ask "Maximum Star Sum of a Graph"
Maximum Star Sum of a Graph is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe trap is thinking you must include all neighbors of your chosen center. You don't. Sort the neighbors by value, pick the center with the highest sum, then greedily add only the neighbors that increase your total. The heap or sorted approach matters because you're making repeated max-selections across multiple potential centers. Most candidates either try to include all neighbors (wrong) or attempt an expensive brute-force recalculation (slow). The Greedy and Sorting topics are the signal: once you see the problem, the pattern should click. If you hit this live and the greedy insight doesn't land immediately, StealthCoder runs invisibly during screen share and gives you the code structure you need to pass.
Pattern tags
You know the problem.
Make sure you actually pass it.
Maximum Star Sum of a Graph recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Star Sum of a Graph interview FAQ
Is this problem actually about priority queues or just smart sorting?+
Both. A heap lets you efficiently track the top k neighbors per candidate center without recomputing. If you sort once and iterate, you can also solve it, but a heap keeps the solution cleaner under time pressure. The topics list includes Heap, so be ready to justify either approach.
Why is the acceptance rate only 40% for a Medium?+
Candidates mistake it for a must-include-all problem and waste time on wrong approaches. The greedy 'only add profitable neighbors' insight isn't obvious unless you've seen the pattern. Once you know the trick, it's routine.
Do I need to try every node as a center?+
Yes. Each node can be a star center with its neighbors as rays. The sum for each differs based on neighbor values and how many profitable ones exist. You iterate, compute, keep the max. That's why sorting or a heap helps avoid redundant work.
How does Greedy fit here if I'm iterating all centers?+
Greedy is in the neighbor selection: for a given center, you greedily pick only neighbors with positive contribution. The iteration over all centers is exhaustive, but the per-center choice is greedy. That's the pattern.
If Akuna Capital asked this, is it a screen or a final-round filter?+
Unknown from the data, but Akuna is quant-adjacent, so they likely use it as a medium-difficulty screen to filter for algorithmic clarity under time pressure. A 40% pass rate suggests it's not trivial.
Want the actual problem statement? View "Maximum Star Sum of a Graph" on LeetCode →