Benchmark: Benchmark function for list

Script Preparation code:

function listAutoComplite (list,n){
    let i = 1;
    for(; i < n; i++){
        list.value = i;
        list.next = {
            value : 0,
            next:null
        }
        list = list.next;
    }
    list.value = i;
}
var someList = {};
listAutoComplite(someList,10000);

Tests:

Array unshift
function reversePrint1(linkedList) { const result = []; while(linkedList.next != null){ result.unshift(linkedList.value); linkedList = linkedList.next; } result.unshift(linkedList.value); console.log(...result); } reversePrint1(someList);
Array push + reverse
function reversePrint2(linkedList) { const result = []; while(linkedList.next != null){ result.push(linkedList.value); linkedList = linkedList.next; } result.push(linkedList.value); console.log(...result.reverse()); } reversePrint2(someList);
just a static array,
function reversePrint3(linkedList) { let List = Object.assign(linkedList); let i = 0; while(List.next != null){ ++i; List = List.next; } const result = new Array (i+1); while(linkedList.next != null){ result[i] =linkedList.value linkedList = linkedList.next; i-- } result[i] = linkedList.value; console.log(...result); } reversePrint3(someList);
recursion
function reversePrint4(linkedList){ const result = []; function recursion(obj){ if(obj.next === null){ result.push(obj.value); return } recursion(obj.next); result.push(obj.value); } recursion(linkedList); console.log(...result); } reversePrint4(someList);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array unshift
Array push + reverse
just a static array,
recursion

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

I'll break down the benchmark and its options, highlighting their pros and cons, library usage, and special JavaScript features.

**Benchmark Overview**

The test cases create a linked list data structure, which is then used to measure performance differences in various operations:

1. `Array unshift`
2. `Array push + reverse`
3. `just a static array` (no linked list)
4. `recursion`

**Options Compared**

Each option has its strengths and weaknesses:

1. **Link List with `next` Property**: This approach creates a dynamic, flexible data structure that can grow or shrink as needed.
	* Pros: efficient memory usage, no need to create arrays of fixed size.
	* Cons: more complex implementation, potential performance issues due to frequent node creation/deletion.
2. **Static Array**: A simple, fixed-size array is used instead of a linked list.
	* Pros: easy to implement, predictable performance.
	* Cons: inefficient memory usage, cannot grow or shrink dynamically.

**Library Usage**

None of the test cases explicitly use any external libraries, but they do utilize JavaScript's built-in `Object.assign()` method (in option 3).

**Special JavaScript Features**

No special JavaScript features are used in this benchmark. However, some modern browsers may have experimental or optimized implementations of certain functions that could affect performance.

**Benchmark Results**

The results show the number of executions per second for each test case:

1. `Array unshift`: lowest execution rate (35.99/s)
2. `Array push + reverse`: moderate execution rate (238.25/s)
3. `recursion`: highest execution rate (222.71/s)
4. `just a static array`: lowest execution rate (35.99/s), similar to `Array unshift`

**Interpretation**

The results suggest that the recursive approach (`recursion`) is the fastest, likely due to its simplicity and optimized implementation in modern browsers. The linked list with `next` property and static array approaches have lower execution rates, likely due to their complexity and memory usage.

As a software engineer, it's essential to consider factors like memory efficiency, performance, and code complexity when designing data structures or algorithms for your project.

**Other Alternatives**

Some alternative approaches you might consider:

* Using an existing JavaScript library like Lodash or Ramda for array operations
* Implementing a hybrid data structure that combines the benefits of linked lists and static arrays
* Optimizing the recursive approach using memoization, caching, or other techniques to reduce function calls

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Linux; Android 9; MI MAX 3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.143 Mobile Safari/537.36

Browser/OS: Chrome Mobile 75 on Android

View result in a separate tab

Test name	Executions per second
Array unshift	36.0 Ops/sec
Array push + reverse	238.3 Ops/sec
just a static array,	261.6 Ops/sec
recursion	222.7 Ops/sec

Related benchmarks:

Benchmark function for list (version: 1)

hi Yandex

Comparing performance of: Array unshift vs Array push + reverse vs just a static array, vs recursion

Created: 5 years ago by: Registered User

Jump to the latest result

Array unshift

Array push + reverse

just a static array,

recursion

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):