var arr = [1, 2, 3];
arr = [arr, 4];
var arr = [1, 2, 3];
arr.push(4);
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
spread operator | |
push function |
Test name | Executions per second |
---|---|
spread operator | 25692296.0 Ops/sec |
push function | 38238904.0 Ops/sec |
Let's break down the provided benchmark and explain what's being tested.
Benchmark Overview
The test is comparing two ways to add an element to an array in JavaScript:
...
)push()
methodOptions Compared
In this case, we only have two options compared: using the spread operator and using the push()
method.
Pros and Cons of Each Approach:
push()
for large arrays.push()
method is called on a non-array value.Library Used
There doesn't appear to be any library being used in this benchmark. The script and HTML preparation codes are empty, which suggests that the test is designed to isolate the JavaScript engine's behavior for this specific operation.
Special JS Feature/Syntax
Neither of the options being compared uses a special feature or syntax. However, it's worth noting that using the spread operator (...
) was introduced in ECMAScript 2015 (ES6) and has since become a standard part of modern JavaScript.
Other Alternatives
If you're interested in exploring other alternatives for adding elements to an array, some examples include:
Array.prototype.concat()
or Array.prototype.pushAll()
Array.from()
method_.push()
functionKeep in mind that each of these alternatives has its own trade-offs and use cases.
Benchmark Result Interpretation
The provided benchmark result shows two runs, one for each option being compared. The "ExecutionsPerSecond" value represents the number of executions per second, which is an important metric when measuring performance.
In this case, the push()
method appears to be slightly faster than using the spread operator, possibly due to its efficiency and lack of unnecessary array object creation. However, the difference may not be significant in most scenarios, and other factors like memory allocation and garbage collection might also impact performance.
It's essential to consider these results in context, taking into account the specific use case and environment where the benchmark is being used.