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Understand what engineering metrics measure, how teams collect them, and what the numbers can tell you about the work behind a release.
Terms beginning with S
24 termsSampling
Sampling selects a subset of observations for storage or analysis.
Engineering analyticsSchema validation
Schema validation checks records against structural and semantic expectations.
Engineering analyticsSegment
Segment is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsSegment Size
Segment Size is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsSegmentation Criteria
Segmentation Criteria is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsSelection bias
Selection bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsSelective significance
Selective significance is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsSemantic conventions
Semantic conventions standardize names, attributes, units, and meanings.
Engineering analyticsSemantic layer
Semantic layer models governed concepts above raw data.
Engineering analyticsService Comparison
Service Comparison is an analytical concept for separating engineering observations into populations whose differences may matter to a decision.
Engineering analyticsSmall sample size
Small sample size is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsSnapshot metric
Snapshot metric describes state at one point in time.
Engineering analyticsSoftware delivery system
A software delivery system is the connected set of workflows, tools, people, controls, and feedback loops that moves a software change from an idea or request through development and validation into production and operation.
Engineering analyticsSoftware factory
A software factory is the connected system an organization uses to design, build, test, review, release, and learn from software. It includes human responsibilities, delivery workflows, platforms, automation, quality controls, and the feedback that improves the system over time.
Engineering analyticsSoftware factory baseline
A software factory baseline is a documented snapshot of a software delivery system before an intervention or comparison. It records the work population, event definitions, time window, measures, and relevant operating conditions needed to interpret later change.
Engineering analyticsSoftware factory cadence
Software factory cadence is the recurring rhythm by which a software delivery system receives work, creates changes, gathers feedback, releases software, and reviews outcomes. It is a property of the system's flow, not a requirement that every team work to the same schedule.
Engineering analyticsSoftware factory feedback loop
A software factory feedback loop is a recurring path in which an observation about a software change or outcome informs a decision, the decision changes the system, and a later observation tests the result. Feedback may come from code review, tests, delivery, production, customers, or developers.
Engineering analyticsSoftware factory observability
Software factory observability is the ability to understand what is happening inside a software delivery system by using connected signals about work, workflow state, timing, failures, ownership, and outcomes. It supports investigation by preserving enough context to explain why a result occurred.
Engineering analyticsSoftware factory queue time
Software factory queue time is the elapsed time a software work item spends waiting for a person, decision, resource, check, environment, or next workflow stage. It is a part of total delivery time and should be defined by the queue boundary being measured.
Engineering analyticsSoftware factory rework
Software factory rework is software work performed again because an earlier change was defective, incomplete, misunderstood, rejected, or made obsolete. It includes corrective changes and repeated effort that consumes delivery capacity without representing a new independent outcome.
Engineering analyticsSoftware factory throughput
Software factory throughput is the amount of software work that reaches an agreed completion point during a defined period. The completion point may be a merged change, a production deployment, or a customer outcome, and the chosen boundary must remain consistent.
Engineering analyticsSoftware value stream
A software value stream is the sequence of activities and handoffs required to turn a software request into a usable outcome. It includes the work that creates new value and the recovery work required to restore or protect an existing service.
Engineering analyticsSource system
Source system identifies where measurement records originate.
Engineering analyticsSurvivorship bias
Survivorship bias is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analytics