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Level ancestor problem

A rooted-tree query problem asking for a node’s ancestor at a specified depth after preprocessing the tree.

Version
v1 · 2026-09-08 · History
Domain-specific #
5307
Origin domain
data structures
Subdomain
data structures

Core Idea

Depth-from-root and distance-up formulations require conversion; algorithms trade preprocessing time, query time, memory, static or dynamic updates and computational model. Preprocessing stores jump, decomposition or succinct-navigation information so a query can move from a node to the unique node on its root path at the requested level. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.

The load-bearing residual is not the broad topic of data structures. It is the domain-specific identity determined by the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit.

Scope of Application

Level ancestor problem belongs to data structures and is useful where the analyst can specify the typed data structures carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, then evaluate the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit. The scope is broad within that domain but bounded by the need for the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit. The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.

Clarity

The abstraction clarifies a crowded vocabulary by making the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test.

Manages Complexity

Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Level ancestor problem. Level ancestor problem compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.

Abstract Reasoning

  1. Identify the carrier. State what the elements, states, objects, or observations are: the typed data structures carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets. Reject examples whose alleged carrier belongs to a different problem. 2. Lock the constitutive rule. Express the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit independently of one notation or implementation.

Knowledge Transfer

Knowledge transfers strongly among subfields of data structures because they reuse the typed data structures carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, Preprocessing stores jump, decomposition or succinct-navigation information so a query can move from a node to the unique node on its root path at the requested level., and type the carrier, state every parameter and convention in the definition, test that the rooted tree and size, depth convention, query arguments and invalid-query behavior, preprocessing algorithm and time, storage, query algorithm and time, update model and computational assumptions are explicit, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.

Relationships to Other Abstractions

Local relationship map for Level ancestor problemParents appear above the current abstraction, mutual partners to the right, and children below. Node labels state whether each abstraction is prime or domain-specific; colors identify relation types.Level ancestorproblemDOMAINPrime abstraction: Search and Retrieval — is a kind ofSearch andRetrievalPRIME

Current abstraction Level ancestor problem Domain-specific

Parents (1) — more general patterns this builds on

  • Level ancestor problem is a kind of Search and Retrieval Prime

    The proposed strict upward parent is prime:search_and_retrieval.

Hierarchy paths (4) — routes to 3 parentless roots

Neighborhood in Abstraction Space

Level ancestor problem sits in a crowded region of the domain-specific corpus (36th percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.

Family — Tree Data Structures & Algorithms (9 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-09-08