INDEX / 04 / TECHNICAL DISCIPLINE
04

Data Structures.

What shape does information take?

Investigate the representations that let programs retrieve, update and reason about data.

THE SCOPE

Trees, hash tables, indexes, graphs, persistent structures and memory models.

This starting dossier establishes a research remit and reference points for the section. It does not claim to be a comprehensive historical survey. Future articles will identify primary evidence, publication or artifact dates, competing accounts and the limits of verification.

01 / EVIDENCE LENS

The same abstraction can hide different costs

An associative map might use hashing or ordered trees; practical costs depend on workload and implementation details.

02 / EVIDENCE LENS

Structure and storage interact

Cache layout, serialization, concurrency and durability all influence how a structure performs outside textbook conditions.

03 / EVIDENCE LENS

Dates must be attached to evidence

Historical accounts should distinguish first descriptions from implementations, popularization and later refinements.

OPEN QUESTIONS / NOT ASSUMPTIONS

Questions that guide the reporting.

  1. 01Which operation and workload are being measured?
  2. 02What guarantees, if any, are offered for ordering and concurrency?
  3. 03Is the example an original historical implementation or a modern teaching reconstruction?

PRIMARY & TECHNICAL REFERENCES

Starting sources

The references below are paths into the evidence, not a claim that every historical question is settled. Each future article will provide its own direct citations and version-specific evidence.

  1. 01NIST — data-structure entries xlinux.nist.gov
  2. 02SQLite — B-tree module www.sqlite.org

VERSION RECORD / 1.0

This dossier is revisable.

2026-10-08 — Initial edition. Research scope, evidence lenses, questions and reference starting points published. No external submissions have been reviewed for this initial edition. Future substantive changes should be documented with supporting evidence.

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