Storage & Lookup Data Structures

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Abstractions about organizing data for storage and fast lookup, covering hash-based and probabilistic structures (hash tables, Bloom and quotient filters), ordered and keyed collections (sorted arrays, heaps, queues, multimaps, lookup tables), adaptive and multidimensional structures (self-organizing lists, k-d trees), and storage tiering.

21 abstractions in this family — domain-specific abstractions that sit near one another in structural-signature space (k-means over structural-signature embeddings). Each is shown with its short description.

• Bit Rate — Measure the number of binary digits represented, transferred, or processed per unit time at a declared interface, with the counted layers and overhead convention made explicit.
• Bloom Filter — A probabilistic data structure that answers set-membership from a compact bit array and k hash functions with a deliberate one-sided error — it may report false positives but never false negatives — so a negative answer is safe to act on.
• Dadda multiplier — Hardware multiplier design.
• Hash Table — Store key-value pairs in a fixed-capacity array by computing each key's index with a hash function, so the address is derived from the content and lookup, insertion, and deletion run in expected-amortised O(1) independent of collection size.
• Heap — Keep the single most extreme element instantly readable at the root of a partially ordered tree, so insert and extract cost only O(log n) under continuous churn by declining to maintain any more order than the extreme requires.
• Hierarchical Storage Management — Policy-controlled movement of addressable data among storage tiers with different access and cost characteristics, coupled to a defined retrieval path.
• K-d Tree — A k-d tree organizes multidimensional records by recursive binary splits on coordinate keys, enabling bounded-region search and pruning.
• Key–Value Database — A persistent data store organizes records as values addressed by unique keys, making key-based access its primary contract while allowing richer implementation features.
• Lookup Table — A prepared, addressable set of associations that returns a stored value or output for a supplied key instead of deriving or selecting it afresh.
• Low-Density Parity-Check Code — A linear error-correcting block code specified by sparse parity-check constraints on its valid codewords.
• Multimap — A multimap is an abstract data type that associates one key with zero or more values while preserving key-based insertion, lookup, removal, and iteration semantics beyond an ordinary one-value map.
• Parallel Array — A multi-field record sequence represented by separate field arrays whose matching positions jointly form each logical record.
• Public-Key Cryptography — Give each party a mathematically linked public/private key pair where an operation done with one key is invertible only with the other and the private key cannot feasibly be computed from the public one, so confidentiality and verifiable authorship need no pre-shared secret.
• Quadratic Assignment Problem — Optimize a one-to-one placement when the cost of one item-position choice depends on other simultaneous placements.
• Queue (FIFO Abstract Data Type) — A FIFO queue adds elements at the rear and removes the earliest still-pending element from the front, independent of its storage implementation.
• Quotient Filter — Store hashed key fingerprints as quotient-indexed, remainder-bearing runs in a compact metadata-coded table, supporting locality-friendly one-sided membership and, under compatible parameters and duplicate semantics, deletion, merge, and resize.
• Randomized Algorithm — A randomized algorithm makes internal random choices and states its output or cost guarantee over those choices for each fixed input.
• Reduction operator — A reduction operator associatively combines array elements into one result and thereby supports parallel aggregation.
• Retrieval Data Structure — Retrieval Data Structure is a recurring identity in computer science and information systems, formal models and representations, mathematics, logic, and statistics, social sciences, humanities, and arts defined by this frozen evidence: In computer science, a retrieval data structure, also known as static function, is a space-efficient dictionary-like data type composed of a collection of (key, value) pairs that allows the following operations: Construction from a collection of (key, value) pairs Retrieve the value associated with the given key or anything if the key is not contained in the.
• Self-Organizing List — An ordered sequential-access list that updates item positions from accesses, making earlier requests alter later search costs or position readouts.
• Sorted Array — A sorted array keeps comparable keys in contiguous index order, enabling binary-search lookup and contiguous ranges while making middle updates costly.