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Benchmark

As explained in The Art of Code

A microbenchmark is a controlled performance measurement of a small code operation or component.

A microbenchmark measures a small code operation or component in isolation. It provides a focused way to compare runtime behavior when efficient code and small memory footprints matter. section 8.5.2

Choose a framework suited to the language:

Use profiling when a small measurement is not enough: profilers can reveal CPU behavior and memory allocation, while object-layout tools inspect actual memory footprints. section 8.5.2

How The Art of Code covers it

How deep it goes
Defines isolated measurement and names frameworks, then defers deeper CPU, allocation, and memory-layout analysis to profilers and JOL.
Examples
Names JMH, BenchmarkDotNet, pytest-benchmark, language-specific profilers, and the Java Object Layout toolkit.
What you can do after
Apply it via JMH, BenchmarkDotNet, or pytest-benchmark to measure small operations, then use profilers for deeper diagnosis.
How it connects
Connects microbenchmarking with dynamic analysis, profiling, energy consumption, efficient code, and memory footprint.

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This explainer was generated by Manning's knowledge graph from the text of The Art of Code. The section links point to the parts of the book it draws on.