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Weighted Micro Function Points

Weighted Micro Function Points (WMFP) is a modern software sizing algorithm which is a successor to solid ancestor scientific methods as COCOMO, COSYSMO, maintainability index, cyclomatic complexity, function points, and Halstead complexity. It produces more accurate results than traditional software sizing methodologies, while requiring less…

Measurement & Science

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Research this topic

Explore the main themes, entities and connections around Weighted Micro Function Points. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Measured elements

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Weighted Micro Function Points

Nodes17
Edges16
Triples6
Avg. degree1.88
Density0.117647
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

software wmfp elements sizing source code algorithm complexity cocomo function effort score analysis micro ancestor methods methodologies measurement measured also

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
separating code into classesinstance ofMeasures the amount of effort spent on the program structure0.80text
functions Inline datainstance ofMeasures the amount of effort spent on the program structure0.80text
COCOMOinstance ofwhen compared to traditional sizing models0.80text
are more complex to a degree that they cannot realistically be evaluated by handinstance ofwhen compared to traditional sizing models0.80text
even on smaller projectsinstance ofwhen compared to traditional sizing models0.80text
and require a software to analyze the source codeinstance ofwhen compared to traditional sizing models0.80text

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
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