Benchmark: stage1 collect varients v3

Script Preparation code:

var Z=()=>{},_=()=>document.createDocumentFragment(),$=(j)=>document.createTextNode(j),Q=(j)=>document.createElement(j),z=(j)=>j.cloneNode(!0),F=(j,q)=>q.appendChild(j),R=(j,q)=>q.insertBefore(j,q.firstChild),U=(j,q)=>q.parentNode.insertBefore(j,q.nextSibling),W=(j,q)=>(q.parentNode.replaceChild(j,q),j),C=(j,q)=>{new MutationObserver((A,B)=>{for(let I of A)for(let G of I.removedNodes)if(G.contains(j)){q(),B.disconnect();return}}).observe(document,{childList:!0,subtree:!0})};var P=Q("template"),Y=document.createTreeWalker(P),M=(j)=>{return P.innerHTML=j,P.content.firstChild},T=(j,q,A)=>{let B=Y,I={},G=q.length,J=0,H;B.currentNode=j;for(;J<G;J++){H=A[J];while(H--)B.nextNode();I[q[J]]=B.currentNode}return I},N=(j,q,A)=>{let B={},I=q.length,G=0,J,H=j,L;for(;G<I;G++){J=A[G];while(J--){L=H,H=H.firstChild||H.nextSibling;while(!H)L=L.parentNode,H=L.nextSibling}B[q[G]]=H}return B};var V={},X=(j)=>{let q="__"+j.type,A=j.target;while(A){if(A[q])return A[q](j);A=A.parentNode}},E=(j)=>{V[j]??=(document.addEventListener(j,X),!0)},S=(j)=>{V[j]=null,document.removeEventListener(j,X)};var w=(j)=>{let q={};return new Proxy({...j,on(A,B){return(q[A]??=[]).push(B),()=>{q[A]?.splice(q[A].indexOf(B)>>>0,1)}}},{set(A,B,I){return q[B]?.forEach((G)=>G(I,A[B])),A[B]=I,!0}})};
var h = M;
var collect = T; // original
var collect2 = N; // custom
var view=h('<div class=d1><span></span><div class=d2><span></span><div class=d3><span></span><div class=d4><span></span><div class=d5><span></span><div class=d6><span></span><div class=d7><span></span><div class=d8><span></span><div class=d9><span></span><div class=d10><span></span><div class=d11><!--></div></div></div></div></div></div></div></div></div></div></div></div>');

Tests:

collect
collect(view,['a','b','c','d'],[2,6,10,3])
collect2
collect2(view,['a','b','c','d'],[2,6,10,3])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
collect
collect2

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 12 days ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:136.0) Gecko/20100101 Firefox/136.0

Browser/OS: Firefox 136 on Linux

View result in a separate tab

Test name	Executions per second
collect	1866832.0 Ops/sec
collect2	4641848.5 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 12 days ago):

LLMs can make mistakes. Check important info.

The benchmark defined in the provided JSON is designed to compare the performance of two different functions, `collect` and `collect2`, both of which are aimed at processing an HTML structure and collecting nodes based on specific criteria. Here’s a breakdown of the options being compared, the libraries and concepts involved, as well as alternatives.

### Functions Compared

1. **`collect(view,['a','b','c','d'],[2,6,10,3])`**: This function appears to utilize a method for traversing and collecting nodes from a virtual DOM structure created from a template. The specifics of its operation are encapsulated in the `T` function (original). This approach likely employs a TreeWalker to efficiently navigate through the document fragment.

2. **`collect2(view,['a','b','c','d'],[2,6,10,3])`**: This function uses a different method for node collection, represented by the `N` function (custom). It takes a similar set of inputs but presumably implements the node traversal and collection using a different technique.

### Pros and Cons of Approaches

- **`collect` (Original)**:
  - **Pros**:
    - The method using `TreeWalker` likely offers a simple and effective way to navigate through elements without the complexity of managing multiple DOM traversals.
    - The original function may be more standard or familiar to those accustomed to DOM manipulation patterns in JavaScript.
  - **Cons**:
    - Performance may be sub-optimal depending on how deep the traversals go, especially with nested nodes.

- **`collect2` (Custom)**:
  - **Pros**:
    - This custom logic might be optimized for particular use cases or structures, potentially resulting in faster collection times.
    - There may be more flexibility in handling edge cases or specific traversal requirements.
  - **Cons**:
    - Custom logic can lead to complexity and maintenance challenges. It may also introduce bugs if the traversal logic is not as rigorously tested as a more standard approach.

### Libraries and Techniques

- **MutationObserver**: In the preparation code, a `MutationObserver` is defined, which is used to monitor changes to the DOM. This is useful for tracking when nodes are added or removed, allowing the benchmark to measure how well each function responds to dynamic changes in the document structure.

- **Proxy**: A `Proxy` is employed to intercept operations for tracking, which is a powerful feature in JavaScript that allows you to define custom behavior for fundamental operations (e.g., property access, assignment).

### Performance Metrics

The benchmark results for both functions yield the following:

- **`collect2`:** ~4,641,848.5 executions per second
- **`collect`:** ~1,866,832.0 executions per second

From this data, it is evident that `collect2` is significantly more performant in terms of execution speed.

### Other Considerations and Alternatives

- **Alternative Approaches**:
  - Using a library such as **jQuery** can simplify DOM manipulation, though it may add overhead.
  - **Virtual DOM libraries** (like React) optimize performance by minimizing actual DOM manipulations and leveraging diffing algorithms. This can change how node collections are performed.

- **Direct DOM Manipulation vs. Frameworks**: Frameworks or libraries generally handle many complexities of DOM interactions, potentially increasing performance for large applications, especially in single-page applications (SPAs). However, understanding the underlying mechanics as showcased in this benchmark is invaluable for making informed performance choices.

In summary, this benchmark compares two different node collection strategies, revealing significant variances in execution performance that can inform developers when optimizing for efficiency in DOM manipulation tasks.

Related benchmarks:

stage1 collect varients v3 (version: 1)

Comparing performance of: collect vs collect2

Created: 12 days ago by: Guest

Jump to the latest result

collect

collect2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 12 days ago):