Benchmark: Odd sorrting#2 - MeasureThat.net

Tests:

best practice
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3]; const odd = arr.filter((x) => x % 2).sort((a,b) => a - b); arr.map((x) => x % 2 ? odd.shift() : x);
Array methods
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3]; let indexes = [], values = []; arr.map((el, index) => { if(el % 2 !== 0) { indexes.push(index); values.push(el); } }) let filtered = arr.filter((el,i) => { // console.log(el); // console.log(i); return el % 2 === 0; }) indexes.sort((a,b) => { return a-b;}); values.sort((a,b) => { return a-b;}) for(let i=0; i<values.length; i++) { filtered.splice(indexes[i], 0 , values[i]) }
for x2
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3]; let arrOdd = [] for(let i = 0; i<arr.length; i++) { if(arr[i] % 2 !== 0) { arrOdd.push(arr[i]); arr[i] = null; } } arrOdd.sort((a,b) => {return a-b}); for(let i = 0; i<arr.length; i++) { if(arr[i] == null) { arr[i] = arrOdd.shift(); } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
best practice
Array methods
for x2

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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I'll break down the benchmark and explain what's being tested, along with the pros and cons of each approach.

**Benchmark Overview**

The benchmark measures the performance of three different ways to sort an array in ascending order while removing duplicates:

1. **Best Practice**: Using built-in JavaScript methods (`sort()` and `map()`) in a single line of code.
2. **Array Methods**: Breaking down the sorting process into multiple steps using separate arrays for indices and values.
3. **For Loop**: Using a traditional for loop to remove duplicates and sort the array.

**What's Being Tested**

* The performance of each approach on various browsers (Firefox 107) on different devices (Desktop, Mac OS X 10.15).
* The number of executions per second (ExecutionsPerSecond) is reported for each benchmark.

**Approach 1: Best Practice**

Pros:

* Concise and readable code.
* Leverages built-in JavaScript methods, which are optimized for performance.

Cons:

* May not be as efficient as other approaches due to the overhead of function calls and method invocations.

**Implementation**
```javascript
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3];
arr.map((x) => x % 2 ? odd.shift() : x);
```
Note that the `odd` variable is not defined in this code snippet, which suggests that the benchmark might be missing some context or preparation code.

**Approach 2: Array Methods**

Pros:

* More explicit and understandable code.
* Allows for better control over the sorting process.

Cons:

* Requires more lines of code, which can lead to slower performance due to function call overhead.

**Implementation**
```javascript
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3];
let indexes = [], values = [];
arr.map((el, index) => {
  if (el % 2 !== 0) {
    indexes.push(index);
    values.push(el);
  }
});
indexes.sort((a, b) => a - b);
values.sort((a, b) => a - b);
for (let i = 0; i < values.length; i++) {
  filtered.splice(indexes[i], 0, values[i]);
}
```
**Approach 3: For Loop**

Pros:

* No function call overhead.
* Can be more efficient for large datasets.

Cons:

* Requires more lines of code and is less readable.
* May not be as suitable for smaller datasets or more complex scenarios.

**Implementation**
```javascript
const arr = [-6, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -4, -5, -3];
let arrOdd = [];
for (let i = 0; i < arr.length; i++) {
  if (arr[i] % 2 !== 0) {
    arrOdd.push(arr[i]);
    arr[i] = null;
  }
}
arrOdd.sort((a, b) => a - b);
for (let i = 0; i < arr.length; i++) {
  if (arr[i] === null) {
    arr[i] = arrOdd.shift();
  }
}
```
**Libraries and Special Features**

The benchmarks do not appear to rely on any specific libraries or special features of JavaScript. However, the `map()` method is used in all three implementations, which is a built-in JavaScript method.

**Alternatives**

Other approaches to sorting an array while removing duplicates could include:

* Using a data structure like a Set or Map to keep track of unique elements.
* Utilizing a sorting algorithm like Quicksort or Merge Sort.
* Leveraging libraries like Lodash or Ramda for functional programming utilities.

Keep in mind that the performance differences between these approaches may vary depending on the specific use case, dataset size, and browser or device being used.

Related benchmarks:

Odd sorrting#2 (version: 0)

Comparing performance of: best practice vs Array methods vs for x2

Created: 3 years ago by: Guest

Jump to the latest result

best practice

Array methods

for x2

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):