Throne Inheritance
A medium-tier problem at 65% community acceptance, tagged with Hash Table, Tree, Depth-First Search. Reported in interviews at Snowflake and 0 others.
You're building a system to track kingdom succession. That's what Throne Inheritance is: a design problem wrapped in a tree, where you need to handle births, deaths, and real-time heir queries. It's not a pure algorithm grind. You're designing a data structure that stays efficient under updates. Snowflake has asked it. Sixty-five percent acceptance means it's medium-hard but not a surprise filter. The trap is overthinking the tree traversal or trying to compute heirs on every query instead of maintaining them smartly. If you hit this live and blank on the design pattern, StealthCoder surfaces a working structure in seconds.
Companies that ask "Throne Inheritance"
Throne Inheritance 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. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core trick is building a tree (representing family lineage) with efficient heir lookup. You'll track parent-child relationships, handle new births by inserting nodes, and remove people from succession when they die. The naive approach recomputes heirs every query by walking the tree in depth-first order. That works, but wastes time if queries outnumber updates. The real pattern is maintaining a pruned tree where deaths don't physically remove nodes; they just mark people as dead, so you can skip them during traversal. Hash tables store the family structure, DFS walks it in birth order to find the nth heir. The acceptance rate (65%) reflects that candidates either nail the design immediately or struggle with tree mutations. StealthCoder handles both the data structure shape and the traversal order so you don't waste live time debugging off-by-one heir counts.
Pattern tags
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Throne Inheritance 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. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Throne Inheritance interview FAQ
What's the actual trick to this problem?+
You need to maintain a tree structure that represents lineage while efficiently answering "who is the nth heir?" queries after births and deaths. The trick is not recomputing heirs from scratch every query. Use DFS on the tree in birth order and skip dead nodes. Hash tables store children lists for each person so lookups are fast.
Is this still asked by top companies?+
Snowflake has asked it. It's a design problem, not a pure algorithm grind, so it appeals to companies that care about system thinking. It's less common than array or string problems but hits hard when it appears because candidates often undersell their solution or over-engineer it.
Why is the acceptance rate 65%?+
It's marked medium difficulty and the 65% acceptance reflects a clean split: candidates who see the tree structure and DFS order quickly pass, while those who try to optimize too early or mishandle edge cases (like dead nodes in the middle of a line) stumble. The design itself is not complex, but the mutation logic trips people up.
How does this relate to depth-first search and hash tables?+
DFS gives you the correct heir order by walking the tree in birth sequence. Hash tables store the family structure (parent maps to list of children) so you don't have to search for relatives every time. Together they let you answer queries fast without rebuilding the tree each time.
What's the most common mistake candidates make?+
Deleting nodes from the tree when someone dies instead of just marking them dead. Actual deletion shifts the heir count and forces recomputation. Another trap is not respecting the birth order when multiple children exist. The problem is small enough that you can brute force it, but that fails on large families with many updates.
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