Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Profiling (computer programming)

In software engineering, profiling (program profiling, software profiling) is a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or the frequency and duration of function calls. Most commonly, profiling information serves to aid program optimization, and…

History, Applications, Events & Art

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Profiling (computer programming). 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.

Data granularity in profiler types

36 related topics

History

9 related topics

Use of profilers

12 related topics

Gathering program events

3 related topics

Topics to explore

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

Overview

Gathering program events

Use of profilers

History

Data granularity in profiler types

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

Profiling (computer programming)

Nodes74
Edges73
Triples5
Avg. degree1.97
Density0.027027
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

program code profilers profiling instrumentation performance tools target information data profiler analysis time sampling based also statistical runtime execution call

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
system call processing.Unfortunatelyinstance ofThey can show the relative amount of time spent in user mode versus interruptible kernel mode0.80text
running kernel code to handle the interrupts incurs a minor loss of CPU cycles from the target programinstance ofThey can show the relative amount of time spent in user mode versus interruptible kernel mode0.80text
diverts cache usageinstance ofThey can show the relative amount of time spent in user mode versus interruptible kernel mode0.80text
and cannot distinguish the various tasks occurring in uninterruptible kernel codeinstance ofThey can show the relative amount of time spent in user mode versus interruptible kernel mode0.80text
the Application Response Measurement standard.Automatic source levelinstance ofsimply count events or calls to measurement APIs0.80text

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
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.