var person = { name: 'John', age: 23, sex: 'Male' };
delete person.name
let { name, rest} = person
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
del | |
spread |
Test name | Executions per second |
---|---|
del | 28949808.0 Ops/sec |
spread | 8795629.0 Ops/sec |
Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.
Benchmark Definition and Preparation Code
The benchmark definition is provided in JSON format, which describes the test being run on the website. Here's what we have:
Name
field specifies the name of the benchmark: "delete vs spread need for speed".Description
field is empty, as there isn't a detailed description of the benchmark.Script Preparation Code
section sets up an object person
with properties name
, age
, and sex
. This will be used as input for the test cases.Individual Test Cases
The benchmark consists of two individual test cases:
Benchmark Definition
specifies the JavaScript code to run: delete person.name
.delete
keyword.Benchmark Definition
specifies the JavaScript code to run: let { name, ...rest} = person;
.{...}
).Comparison and Options
The two approaches compared in these tests are:
delete person.name
let { name, ...rest} = person;
These approaches have different pros and cons:
Library Usage
In this benchmark, there is no explicit library usage. However, some JavaScript engines (like V8 in Chrome or SpiderMonkey in Firefox) provide built-in support for various optimization techniques, such as:
Special JS Feature/Syntax
This benchmark doesn't use any special or advanced JavaScript features like async/await, let Constants, or modern ES modules. The focus is on basic property deletion and destructuring operations.
Other Alternatives
If you're interested in exploring other microbenchmarking tools, here are some alternatives:
In summary, the "delete vs spread need for speed" benchmark on MeasureThat.net compares two basic approaches to deleting a property from an object in JavaScript: directly using delete
and with the spread syntax. The tests aim to measure execution speeds and identify potential optimization techniques.