var a = [];
for (var ai = 0; ai < 10e3; ai++) {
a.push(String(Math.random()));
}
var o = {};
var e = document.createElement('span');
var l = e.classList;
for (var oi = 0; oi < a.length; oi++) {
o[a[oi]] = true;
}
var oResult = Object.keys(o);
o = {};
for (var li = 0; li < a.length; li++) {
l.add([a[li]]);
}
var oResult = Array.prototype.slice(l);
e.className = '';
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
object | |
class list |
Test name | Executions per second |
---|---|
object | 141.9 Ops/sec |
class list | 0.2 Ops/sec |
Benchmark Explanation
The provided JSON represents a JavaScript microbenchmark test case on the MeasureThat.net website. The benchmark is designed to measure the performance of two different approaches for removing duplicates from an array of strings.
Approaches Compared
There are two approaches compared in this benchmark:
o
) to keep track of unique elements encountered so far. It iterates through the input array a
, and for each element, it checks if the element is already present in the object o
. If not, it adds the element to the object. Finally, it returns a new array containing only the unique elements.l
) to keep track of unique elements encountered so far. It iterates through the input array a
, and for each element, it adds the element as an array to the class list l
. Finally, it returns a new array containing all the elements in the class list.Pros and Cons
However, there are some potential drawbacks:
Library and Special JS Features
In this benchmark, no libraries are explicitly mentioned. However, it's worth noting that both approaches use modern JavaScript features such as:
for...of
loop)class
keyword)The class list API used in the Class List Approach is a proprietary feature of Chrome and only works in modern browsers.
Alternative Approaches
Other alternative approaches to remove duplicates from an array of strings might include:
Set
data structure, which is supported by most modern browsers.Map
object, which can provide a more efficient solution for larger datasets.In conclusion, both approaches have their pros and cons, and the choice of approach depends on the specific use case, performance requirements, and compatibility with different browsers.