Data dependency¶
A relation in which one program operation reads or writes a location whose value or ordering is affected by another operation, constraining safe reordering and parallel execution.
Core Idea¶
Data dependencies include true flow, anti-, and output dependences, distinguished from name dependence and control dependence and analyzed across statements, loop iterations, memory aliases, and execution paths. Read and write sets intersect under an execution order; the direction and distance of the conflicting accesses determine whether reordering changes values and which transformations require renaming or synchronization. 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.
Scope of Application¶
Data dependency belongs to compiler and parallel computing and is useful where the analyst can specify the typed compiler and parallel computing carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, then evaluate operations, memory objects or aliases, read and write events, execution order, path feasibility, dependence type, loop distance, and transformation claim are explicit. The scope is broad within that domain but bounded by the need for operations, memory objects or aliases, read and write events, execution order, path feasibility, dependence type, loop distance, and transformation claim 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 operations, memory objects or aliases, read and write events, execution order, path feasibility, dependence type, loop distance, and transformation claim 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. A bare label is insufficient because the name Data dependency can be used for a formal identity, an implementation, or a neighboring result unless carrier and convention are stated.
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 Data dependency. Data dependency 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¶
- Identify the carrier. State what the elements, states, objects, or observations are: the typed compiler and parallel computing 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 operations, memory objects or aliases, read and write events, execution order, path feasibility, dependence type, loop distance, and transformation claim are explicit independently of one notation or implementation.
Knowledge Transfer¶
Knowledge transfers strongly among subfields of compiler and parallel computing because they reuse the typed compiler and parallel computing carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, Read and write sets intersect under an execution order; the direction and distance of the conflicting accesses determine whether reordering changes values and which transformations require renaming or synchronization., and type the carrier, state every parameter and convention in the definition, test that operations, memory objects or aliases, read and write events, execution order, path feasibility, dependence type, loop distance, and transformation claim are explicit, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.
Relationships to Other Abstractions¶
Current abstraction Data dependency Domain-specific
Parents (1) — more general patterns this builds on
-
Data dependency is a kind of Dependency Prime
The proposed strict upward parent is
prime:dependency.
Hierarchy path (1) — routes to 1 parentless root
- Data dependency → Dependency
Neighborhood in Abstraction Space¶
Data dependency sits in a crowded region of the domain-specific corpus (7th percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.
Family — Memory Architecture & Parallel Computing (34 abstractions)
Nearest neighbors
- Shared memory — 0.94
- Parallel algorithm — 0.93
- Instruction-level parallelism — 0.93
- Parallel RAM — 0.93
- Parallel computing — 0.93
Computed from structural-signature embeddings · 2026-09-08