A reference from Weave

Engineering & AI glossary

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

All terms

2,008 terms

  • Multilingual evaluation

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

    Evaluations and benchmarks

  • Multiple comparisons

    Multiple comparisons 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

  • Mutation score

    Mutation score 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

  • Natural experiment

    Natural experiment 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

  • Natural Language To Code

    Natural Language To Code is a software-engineering concept describing how an AI coding system, its tools, or human collaborators handle a defined task.

    AI coding and agents

  • Nearest-neighbor search

    Nearest-neighbor search 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 fundamentals

  • Negative testing

    Negative 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

  • Nesting depth

    The maximum number of control-flow or structural levels nested inside one another.

    Code quality and technical debt

  • Network partition

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

    Reliability and observability

  • Next-token prediction

    Next-token prediction 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

  • No-repeat n-gram

    No-repeat n-gram is a language-model concept about context selection and limits. 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 fundamentals

  • Normal distribution

    Normal distribution 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

  • Normalized metric

    Normalized metric transforms values for comparison across scale or exposure.

    Engineering analytics

  • North star metric

    North star metric represents a durable customer or product outcome.

    Engineering analytics

  • Notification fatigue

    Notification fatigue 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

  • Notification load

    Notification load is a developer productivity concept that helps teams understand notification load in the context of software delivery.

    Developer productivity

  • Novelty of work

    Novelty of work is a developer productivity concept that helps teams understand novelty of work in the context of software delivery.

    Developer productivity

  • Nucleus sampling

    Nucleus sampling 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 fundamentals

  • Null hypothesis

    Null 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 experimentation

  • Null rate

    Null rate measures absent or unusable values in a field.

    Engineering analytics

  • Number needed to treat

    Number needed to treat 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

  • Numerator

    Numerator defines which events sit above a rate's division line.

    Engineering analytics

  • Numerator drift

    Numerator 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

  • Objective attainment

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

    Reliability and observability

  • Objectives and key results

    Objectives and key results 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

  • Observability

    Observability is the ability to understand a system's internal behavior from the evidence it produces. In software systems, that evidence often includes logs, metrics, and traces connected to enough context to investigate unexpected behavior.

    Reliability and observability

  • Observability dashboard

    Observability dashboard is a view combining metrics, logs, traces, and context for a system question.

    Reliability and observability

  • Observability debt

    Observability 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

  • Observability signal

    Observability signal is a recorded representation of system behavior that helps a team infer what is happening inside a service.

    Reliability and observability

  • Observational study

    Observational study 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

  • Obsolete code

    Obsolete code 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

  • Odds ratio

    Odds ratio 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

  • One-hot encoding

    One-hot encoding is a language-model concept about context selection and limits. 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 fundamentals

  • One-shot prompting

    One-shot prompting 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 fundamentals

  • Open-closed principle

    A design principle that favors extending behavior through stable contracts rather than repeatedly modifying trusted code.

    Code quality and technical debt

  • OpenTelemetry

    OpenTelemetry is an open-source framework and specification set for generating, collecting, and exporting telemetry.

    Reliability and observability

  • OpenTelemetry Collector

    OpenTelemetry Collector is a vendor-neutral service that receives, processes, and exports telemetry.

    Reliability and observability

  • Operational capacity

    Operational capacity is the portion of a team's available capability used for support, incidents, maintenance, reliability, releases, and other work required to operate a service. It is part of real capacity even when it is not feature delivery.

    Flow and capacity planning

  • Operational definition

    Operational definition turns an abstract concept into repeatable observation rules.

    Engineering analytics

  • Operational readiness

    Operational 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 DevOps

  • Operational toil

    Operational toil is recurring work needed to keep a service running that tends to be manual, tactical, automatable, and without lasting improvement. Its volume often grows with the service unless the underlying need is reduced.

    Reliability and observability

  • Opportunity scoring

    Opportunity scoring is a concept used in software delivery planning to describe a condition, relationship, estimate, or decision about engineering work.

    Flow and capacity planning

  • Order sensitivity

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

    Evaluations and benchmarks

  • Organizational Segment

    Organizational Segment is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.

    Engineering analytics

  • Orphan abstraction

    An abstraction that has no clear owner, consumer, or responsibility in the current design.

    Code quality and technical debt

  • Orphaned code

    Orphaned code 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

  • OTLP

    OTLP is the OpenTelemetry Protocol for transmitting telemetry between instrumented systems, collectors, and backends.

    Reliability and observability

  • Outcome metric

    Outcome metric measures an effect on users, systems, or goals.

    Engineering analytics

  • Outcome orientation

    Outcome orientation is a developer productivity concept that helps teams understand outcome orientation in the context of software delivery.

    Developer productivity

  • Outcome-linked engineering

    Outcome-linked engineering is an approach that connects engineering decisions and delivery measures to the customer, product, business, or reliability outcomes they are intended to influence. It keeps software activity, system performance, and value evidence in the same decision context.

    Measurement and experimentation