A reference from Weave

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Understand the metrics, models, and methods behind modern engineering. Clear definitions, practical examples, and a closer look at what the numbers actually mean.

Terms beginning with D

176 terms

  • Dark launch

    Dark launch is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Dashboard

    Dashboard curates measures, context, and navigation for a decision.

    Engineering analytics

  • Dashboard hygiene

    Dashboard hygiene keeps metric views accurate, current, and understandable.

    Engineering analytics

  • Data accuracy

    Data accuracy asks whether records reflect the real event or value.

    Engineering analytics

  • Data availability

    Data availability measures whether an expected data asset can be accessed and used.

    Engineering analytics

  • Data catalog

    Data catalog inventories assets with owners, schemas, lineage, freshness, and access.

    Engineering analytics

  • Data collector

    Data collector receives, processes, and forwards observations.

    Engineering analytics

  • Data consistency

    Data consistency keeps related fields and records compatible across sources.

    Engineering analytics

  • Data contamination

    Data contamination is a defined lens for examining AI system behavior with a stated task, evidence, and interpretation rule.

    Evaluations and benchmarks

  • Data contract

    Data contract agrees schema, meaning, quality, ownership, and change handling.

    Engineering analytics

  • Data contract testing

    Data contract testing how to test a data contract before it breaks analytics.

    Engineering analytics

  • Data debt

    Data debt is a software maintenance concern describing a condition that can make future changes, verification, operation, or ownership harder. Its practical importance depends on supported behavior, rate of change, and the consequences of delay.

    Code quality and technical debt

  • Data deduplication

    Data deduplication is a language-model concept about mechanism and information flow. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Data dictionary

    Data dictionary documents field meanings, types, units, and allowed values.

    Engineering analytics

  • Data filtering

    Data filtering is a language-model concept about serving behavior and operational tradeoffs. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Data lineage

    Data lineage traces a result through sources, joins, transformations, and presentation.

    Engineering analytics

  • Data migration

    Data migration is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Data mixture

    Data mixture is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Data mixture weighting

    Data mixture weighting is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Data observability

    Data observability monitors freshness, volume, schema, distribution, and quality behavior.

    Engineering analytics

  • Data parallelism

    Data parallelism is the serving concept concerned with data parallelism during AI inference.

    Inference performance

  • Data quality

    Data quality is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation

  • Data reconciliation

    Data reconciliation is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability

  • Data residency routing

    Data residency routing is a model-routing or gateway concept used to manage policy enforcement for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.

    Model routing and gateways

  • Data timeliness

    Data timeliness measures whether data arrives in time for its decision.

    Engineering analytics

  • Data validity

    Data validity checks permitted structure, type, range, format, and rules.

    Engineering analytics

  • Data warehouse

    Data warehouse combines operational records for historical analysis.

    Engineering analytics

  • Data-flow analysis

    A static-analysis technique that tracks how values move through a program.

    Code quality and technical debt

  • Database backfill

    Database backfill is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Database migration

    Database migration is a software maintenance concern describing a condition that can make future changes, verification, operation, or ownership harder. Its practical importance depends on supported behavior, rate of change, and the consequences of delay.

    Code quality and technical debt

  • Dead code

    Code that cannot execute or whose result is never needed by the program.

    Code quality and technical debt

  • Dead letter queue

    Dead letter queue is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability

  • Deadline propagation

    Deadline propagation is a model-routing or gateway concept used to manage reliable request governance for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.

    Model routing and gateways

  • Decision latency

    Decision latency is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Decision log

    Decision log is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Decision table testing

    Decision table testing is a software testing or test-design practice used to gather evidence about a defined risk, behavior, boundary, or operating condition. It makes the question under test explicit, identifies the inputs and observations that matter, and gives a team a repeatable basis for deciding whether the result is acceptable.

    Code quality and technical debt

  • Decision-making

    Decision-making is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Declarative infrastructure

    Declarative infrastructure is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps

  • Decode phase

    Decode phase is the serving concept concerned with decode phase during AI inference.

    Inference performance

  • Decoder-only model

    Decoder-only model is a language-model concept about training behavior and measurement. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.

    LLM fundamentals

  • Deduplication

    Deduplication handles multiple records that represent one event or entity.

    Engineering analytics

  • Deep work

    Deep work is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Defect density

    The number of confirmed defects relative to a defined amount of software or change.

    Code quality and technical debt

  • Defect removal efficiency

    The proportion of defects found and removed before release compared with defects found before and after release.

    Code quality and technical debt

  • Deferred maintenance

    Deferred maintenance is a software maintenance concern describing a condition that can make future changes, verification, operation, or ownership harder. Its practical importance depends on supported behavior, rate of change, and the consequences of delay.

    Code quality and technical debt

  • Definition drift

    Definition drift is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.

    Engineering analytics

  • Definition of done

    A definition of done is an explicit policy for the conditions a work item must satisfy before it is considered complete. It can include implementation, review, testing, documentation, security, and release requirements.

    Flow and capacity planning

  • Definition of ready

    Definition of ready is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.

    Developer productivity

  • Degraded mode

    Degraded mode is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability

  • Delayed data

    Delayed data is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.

    Engineering analytics