A reference from Weave

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 M

128 terms

  • Main branch health

    Main branch health 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

  • Maintainability risk

    The likelihood that future changes to a software area will be costly, error-prone, or difficult to validate.

    Code quality and technical debt

  • Maintainability testing

    Maintainability 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

  • Maintenance work

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

    Developer productivity

  • Maker schedule

    Maker schedule 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

  • Mann-Whitney U test

    Mann-Whitney U test 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

  • Manual instrumentation

    Manual instrumentation records domain-specific events explicitly.

    Engineering analytics

  • Margin of error

    Margin of error 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

  • Marginal AI cost

    Marginal AI cost is the additional expense caused by one more request, token, user, or workflow. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.

    Token costs and AI ROI

  • Masked language modeling

    Masked language modeling 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

  • Masked span corruption

    Masked span corruption 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

  • Maturity benchmark

    Maturity benchmark is an analytical concept for using reference values to understand engineering performance, variation, or capability.

    Engineering analytics

  • Max concurrent requests

    Max concurrent requests is the serving concept concerned with max concurrent requests during AI inference.

    Inference performance

  • Max pooling

    Max pooling 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

  • Max tokens

    Max tokens is the serving concept concerned with max tokens during AI inference.

    Inference performance

  • Maximum generation length

    Maximum generation length 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

  • Mean cycle time

    Mean cycle time is calculated by adding the cycle times in a selected population and dividing by the number of items. It can summarize a dataset, but a few long-running items may pull it away from what most work experiences.

    Flow and capacity planning

  • Mean pooling

    Mean pooling 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

  • Mean time to mitigate

    Mean time to mitigate 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

  • Mean time to resolve

    Mean time to resolve 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

  • Mean time to restore

    Mean time to restore is the average elapsed time needed to restore a service after an incident or failure. The result depends on which events count, how recovery is defined, and whether the distribution is summarized by a mean or another statistic.

    DORA and DevOps

  • Measurement bias

    Measurement bias describes systematic distortion in what a metric represents.

    Engineering analytics

  • Measurement context

    Measurement context what context makes an engineering measure interpretable.

    Engineering analytics

  • Measurement error

    Measurement error 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

  • Measurement framework

    Measurement framework governs how engineering measures are chosen and interpreted.

    Engineering analytics

  • Measurement interval

    Measurement interval sets the time span or cadence of collection and comparison.

    Engineering analytics

  • Measurement invariance

    Measurement invariance 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

  • Measurement plan

    Measurement plan records the decision, population, events, calculations, and owners.

    Engineering analytics

  • Mechanistic interpretability

    Mechanistic interpretability 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

  • Mediation analysis

    Mediation analysis 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

  • Meeting hygiene

    Meeting hygiene 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

  • Meeting load

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

    Developer productivity

  • Memory bandwidth

    Memory bandwidth is the serving concept concerned with memory bandwidth during AI inference.

    Inference performance

  • Memory bound inference

    Memory bound inference is the serving concept concerned with memory bound inference during AI inference.

    Inference performance

  • Memory pressure

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

    Reliability and observability

  • Mentoring

    Mentoring 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

  • Mentoring contribution

    Mentoring contribution is a developer productivity concept that helps teams understand mentoring contribution in the context of software delivery.

    Developer productivity

  • Merge commit

    Merge commit is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review

  • Merge conflict

    Merge conflict is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review

  • Merge queue

    Merge queue is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review

  • Merge readiness

    Merge readiness is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review

  • Merge to deploy time

    Merge to deploy time 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

  • Metadata normalization

    Metadata 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 gateways

  • Method length

    The amount of source text or statements contained in a method or function.

    Code quality and technical debt

  • Metric Anomaly

    Metric Anomaly is an analytical concept that helps describe, summarize, or interpret engineering evidence under a stated measurement design.

    Engineering analytics

  • Metric Baseline

    Metric Baseline is an analytical concept that helps describe, summarize, or interpret engineering evidence under a stated measurement design.

    Engineering analytics

  • Metric Comparison

    Metric Comparison is an analytical concept that helps describe, summarize, or interpret engineering evidence under a stated measurement design.

    Engineering analytics

  • Metric Context

    Metric Context is an analytical concept that helps describe, summarize, or interpret engineering evidence under a stated measurement design.

    Engineering analytics

  • Metric contract

    Metric contract is an analytical concept that helps describe, summarize, or interpret engineering evidence under a stated measurement design.

    Engineering analytics

  • Metric definition

    Metric definition 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