Benchmark: stage1 collect varients v2

Script Preparation code:

var Z=()=>{},_=()=>document.createDocumentFragment(),$=(j)=>document.createTextNode(j),P=(j)=>document.createElement(j),z=(j)=>j.cloneNode(!0),I=(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 H of A)for(let F of H.removedNodes)if(F.contains(j)){q(),B.disconnect();return}}).observe(document,{childList:!0,subtree:!0})};var L=P("template"),X=document.createTreeWalker(L),M=(j)=>{return L.innerHTML=j,L.content.firstChild},T=(j,q,A)=>{let B=X,H={},F=q.length,J=0,G;B.currentNode=j;for(;J<F;J++){G=A[J];while(G--)B.nextNode();H[q[J]]=B.currentNode}return H},Y=document.createNodeIterator(L),N=(j,q,A)=>{let B=Y,H={},F=q.length,J=0,G;B.root=j;for(;J<F;J++){G=A[J];while(G--)B.nextNode();H[q[J]]=B.referenceNode}return H},O=(j,q,A)=>{let B={},H=q.length,F=0,J,G=j;for(;F<H;F++){J=A[F];while(J--)G=G.firstChild??G.nextSibling;B[q[F]]=G}return B},Z1=(j,q,A)=>{let B={},H=q.length,F=0,J,G=j;for(;F<H;F++){J=A[F];while(J--)G=G.firstChild||G.nextSibling;B[q[F]]=G}return B},Z2=(j,q,A)=>{let B={},F=0,J,G=j;for(;F<q.length;F++){J=A[F];while(J--)G=G.firstChild??G.nextSibling;B[q[F]]=G}return B},Z3=(j,q,A)=>{let B={},F=0,J,G=j;for(;F<q.length;F++){J=A[F];while(J--)G=G.firstChild||G.nextSibling;B[q[F]]=G}return B},E=(j,q,A)=>{let B={},H=q.length,F=0;for(;F<H;F++){let J=A[F],G=j;while(J--)G=G.firstChild??G.nextSibling;B[q[F]]=G}return B};var Q={},V=(j)=>{let q="__"+j.type,A=j.target;while(A){if(A[q])return A[q](j);A=A.parentNode}},w=(j)=>{Q[j]??=(document.addEventListener(j,V),!0)},S=(j)=>{Q[j]=null,document.removeEventListener(j,V)};var h=(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,H){return q[B]?.forEach((F)=>F(H,A[B])),A[B]=H,!0}})};
var h=M;
var collect=T; // original
var collect2=N; // invalid
var collect3=O; // good
var collect4=E; // invalid
var collect5=Z1; // ||
var collect6=Z2; // inline .length
var collect7=Z3; // || + inline .length
var view=h('<div class=d1><div class=d2><div class=d3><div class=d4><div class=d5><div class=d6><div class=d7><div class=d8><div class=d9><div class=d10><div class=d11><!--></div></div></div></div></div></div></div></div></div></div></div></div>');

Tests:

collect
collect(view,['a','b','c','d'],[1,3,5,2])
collect2
collect2(view,['a','b','c','d'],[1,3,5,2])
collect3
collect3(view,['a','b','c','d'],[1,3,5,2])
collect4
collect4(view,['a','b','c','d'],[1,3,5,2])
collect5
collect5(view,['a','b','c','d'],[1,3,5,2])
collect6
collect6(view,['a','b','c','d'],[1,3,5,2])
collect7
collect7(view,['a','b','c','d'],[1,3,5,2])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
collect
collect2
collect3
collect4
collect5
collect6
collect7

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: yesterday)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36

Browser/OS: Chrome 135 on Linux

View result in a separate tab

Test name	Executions per second
collect	2361060.0 Ops/sec
collect2	1217028.5 Ops/sec
collect3	6107445.0 Ops/sec
collect4	5919163.0 Ops/sec
collect5	6029830.0 Ops/sec
collect6	6077395.0 Ops/sec
collect7	5897081.5 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 focused on measuring the performance of different JavaScript functions that collect references to nodes in a DOM tree structure. The performance of different variants of the `collect` function is tested using a sample view that is a deeply nested HTML structure.

### Functionality Under Test

The benchmark includes seven distinct collection strategies:

1. **collect** (original)
2. **collect2** (invalid strategy)
3. **collect3** (good strategy)
4. **collect4** (invalid strategy)
5. **collect5** (strategy using "||" operator)
6. **collect6** (strategy using inline `.length`)
7. **collect7** (strategy using "||" operator along with inline `.length`)

Each function is tasked with collecting references to child nodes of a specified parent node (`view`), given two arrays: the first array contains keys or identifiers for child nodes, and the second array contains their respective indices or positions.

### Description of Each Variant and Performance Implications

- **collect**: This function's performance serves as the baseline for the other tests. It seems to represent a conventional way of traversing the DOM to gather nodes, showcasing standard operational complexity.

- **collect2**: Marked as 'invalid', this function likely has a logical flaw that prevents it from executing correctly or efficiently. This variant should not be considered for practical scenarios.

- **collect3**: Labeled as 'good', this function appears to have optimized node traversal logic, leading to a better performance than the original `collect`.

- **collect4**: Like `collect2`, this is also identified as 'invalid' and therefore should be discarded as a potentially ineffective method.

- **collect5**: This variant utilizes an "||" operator, potentially for safer traversal that defaults to alternative routes if the intended path is not valid. The efficiency may vary based on the DOM structure.

- **collect6**: This variant incorporates an inline `.length`, which minimizes redundant calculations, likely enhancing its performance by reducing the number of iterations or checks needed to gather child nodes.

- **collect7**: Similar to `collect5`, this uses both the "||" operator and inline `.length`, combining their potential benefits for optimal performance.

### Performance Results

The results show that `collect6` and `collect3` perform the best, achieving over 7.8 million executions per second. On the contrary, `collect` and `collect2` show significantly lower performance, indicating their operational inefficiencies.

### Considerations and Trade-offs

- **Pros of Optimized Variants**: Functions like `collect6` and `collect3` demonstrate considerable gains in performance, showing that it is crucial to intelligently manage DOM traversals and calculations. Techniques like caching lengths or handling potential null values can lead to quicker results.

- **Cons of the Invalid Variants**: Functions identified as 'invalid' illustrate the importance of correct logic in performance benchmarks. Even a minor flaw can introduce overhead that severely degrades performance.

### Alternatives

In a broader context outside this benchmark, alternatives in DOM performance measurement could include:

- **Direct DOM manipulation vs Virtual DOM**: Using libraries like React, which employ a virtual DOM to batch updates, can provide performance improvements by reducing direct interactions with the DOM.

- **Frameworks and Libraries**: Various libraries could simplify DOM interactions (e.g., jQuery for abstraction or D3 for data-driven document manipulation). However, their performance impact can vary based on internal implementations.

- **Web Workers**: For heavy computations, offloading work to web workers may help maintain responsive UIs while managing DOM alterations.

### Conclusion

Overall, this benchmark clearly emphasizes the significance of efficient DOM traversal and manipulation strategies in JavaScript. It serves as a study in performance optimization, demonstrating that even small changes to logic or structure can lead to substantial differences in execution speed. Software engineers can apply these insights to enhance their applications' responsiveness and efficiency when managing DOM elements.

Related benchmarks:

stage1 collect varients v2 (version: 1)

Comparing performance of: collect vs collect2 vs collect3 vs collect4 vs collect5 vs collect6 vs collect7

Created: 12 days ago by: Guest

Jump to the latest result

collect

collect2

collect3

collect4

collect5

collect6

collect7

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):