Find a term
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 R
195 termsRelease frequency
Release frequency is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.
DORA and DevOpsRelease health check
Release health check is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelease observability
Release observability is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.
DORA and DevOpsRelease orchestration
Release orchestration is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelease planning
Release planning is a concept used in software delivery planning to describe a condition, relationship, estimate, or decision about engineering work.
Flow and capacity planningRelease queue
A release queue is the set of completed or release-ready changes waiting to reach users through a production release process. It is downstream of implementation and review, but it remains unfinished under an end-to-end delivery definition.
Flow and capacity planningRelease readiness
Release readiness is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.
DORA and DevOpsRelease readiness review
Release readiness review is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelease readiness signal
A release readiness signal is evidence used to decide whether a software change or release is sufficiently understood, tested, and supported for its intended production boundary. It may combine quality checks, risk, review, deployment, observability, and operational information.
DORA and DevOpsRelease reversal
Release reversal is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelease rhythm
Release rhythm is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelease train
Release train is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.
DORA and DevOpsRelease window
Release window is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsRelevance evaluation
Relevance evaluation is a defined lens for examining AI system behavior with a stated task, evidence, and interpretation rule.
Evaluations and benchmarksReliability
Reliability 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 experimentationReliability testing
Reliability 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 debtRemove duplication
Remove duplication 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 debtRename refactoring
Rename refactoring 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 debtReopened review
Reopened review is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.
Code reviewRepetition control
Repetition control is a language-model concept about generation behavior and sampling. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.
LLM fundamentalsReplenishment
Replenishment is the activity of deciding which demand should enter a ready queue or delivery commitment population. It balances priority, risk, readiness, and available capacity without requiring every request to be scheduled immediately.
Flow and capacity planningRepository Comparison
Repository Comparison is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsRepository Exploration
Repository Exploration is a software-engineering concept describing how an AI coding system, its tools, or human collaborators handle a defined task.
AI coding and agentsRepository Level Code Generation
Repository Level Code Generation is a software-engineering concept describing how an AI coding system, its tools, or human collaborators handle a defined task.
AI coding and agentsRepresentative sample
Representative sample is a defined lens for examining AI system behavior with a stated task, evidence, and interpretation rule.
Evaluations and benchmarksRepresentativeness
Representativeness asks whether observations reflect the population a claim describes.
Engineering analyticsReproducibility
Reproducibility 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 experimentationRequest admission control
Request admission control 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 gatewaysRequest cancellation
Request cancellation is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.
Reliability and observabilityRequest coalescing
Request coalescing is the serving concept concerned with request coalescing during AI inference.
Inference performanceRequest correlation ID
Request correlation ID is a model-routing or gateway concept used to manage traffic selection 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 gatewaysRequest normalization
Request normalization is a model-routing or gateway concept used to manage interface consistency 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 gatewaysRequest priority
Request priority 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 gatewaysRequest rate
Request rate is the serving concept concerned with request rate during AI inference.
Inference performanceRequest scheduler
Request scheduler is the serving concept concerned with request scheduler during AI inference.
Inference performanceRequested changes
Requested changes is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.
Code reviewRequired review
Required review is a repository or branch rule that blocks integration until specified review conditions are met.
Code reviewResearch hypothesis
Research hypothesis 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 experimentationResidual connection
Residual connection 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 fundamentalsResilience budget
Resilience budget is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.
Reliability and observabilityResilience debt
Resilience 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 debtResilience testing
Resilience 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 debtResource attribute
Resource attribute is metadata identifying the entity that produced telemetry, such as service, host, process, or environment.
Reliability and observabilityResource exhaustion
Resource exhaustion is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.
Reliability and observabilityResponse cache
Response cache is the serving concept concerned with response cache during AI inference.
Inference performanceResponse for a class
A measure of the number of methods potentially executed in response to a message received by a class.
Code quality and technical debtResponse normalization
Response normalization is a model-routing or gateway concept used to manage interface consistency 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 gatewaysResponse prefilling
Response prefilling is a language-model concept about representation and similarity. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.
LLM fundamentalsRestore validation
Restore validation is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.
Reliability and observabilityRetrieval augmented generation
Retrieval augmented generation, or RAG, is an architecture that retrieves relevant documents or records and supplies them to a language model as context for generating a response. It can ground answers in a changing or private information source without retraining the model for every update.
LLM fundamentals