Benchmark: array.pop vs array[index]

Script Preparation code:

window.bigArray = (new Array(10000)).fill(null).map((el, index) => index);

Tests:

array[index]
for(let index = 0; index < 10000; index ++) { const current = bigArray[index]; console.log(current); }
array.pop()
for(let index = 0; index < 10000; index ++) { const current = bigArray.pop(); console.log(current); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array[index]
array.pop()

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data and explain what's being tested, compared, and considered.

**Benchmark Definition**

The benchmark is defined as `array.pop vs array[index]`. This test compares two approaches:

1. **Accessing an element by its index**: `array[index]`
2. **Removing and returning an element from the end of the array**: `array.pop()`

**Options Compared**

These two options are compared in terms of their performance, which is measured by the number of executions per second.

**Pros and Cons of Each Approach:**

1. **Accessing an element by its index**:
	* Pros:
		+ Faster because it directly accesses a specific element without modifying the array.
		+ More predictable and less memory-intensive.
	* Cons:
		+ May not be suitable for large arrays or frequent updates, as it can lead to slower performance due to the need to store the entire array in memory.
2. **Removing and returning an element from the end of the array** (`array.pop()`):
	* Pros:
		+ Suitable for large arrays or frequent updates, as it modifies the array on the fly without storing the entire array in memory.
	* Cons:
		+ May be slower due to the overhead of removing and returning an element.
		+ Can lead to slower performance if the array is accessed frequently.

**Library and Special JS Feature**

There doesn't appear to be any explicit library or special JavaScript feature being used in this benchmark. However, it's worth noting that some browsers may have implemented optimizations for array access patterns, which could affect the results of this benchmark.

**Other Considerations**

* **Memory allocation**: The test creates a large array (`bigArray`) and populates it with 10,000 elements using `map()`. This allocation can be a significant overhead, especially if the array is accessed frequently.
* **Cache efficiency**: The test accesses elements in a sequential manner, which may improve cache locality. However, this can also lead to slower performance due to the need for more cache misses.

**Alternatives**

If you were to design an alternative benchmark, you could consider adding other approaches or variations, such as:

* Using a different data structure (e.g., linked list, set)
* Adding noise or randomness to the benchmark inputs
* Measuring memory usage and allocation overhead
* Testing performance on smaller arrays or datasets

Keep in mind that these alternatives would require significant modifications to the benchmark definition and preparation code.

Latest run results:

Run details: (Test run date: 14 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:132.0) Gecko/20100101 Firefox/132.0

Browser/OS: Firefox 132 on Windows

View result in a separate tab

Test name	Executions per second
array[index]	32.3 Ops/sec
array.pop()	31.6 Ops/sec

Related benchmarks:

array.pop vs array[index] (version: 0)

Comparing performance of: array[index] vs array.pop()

Created: one year ago by: Guest

Jump to the latest result

array[index]

array.pop()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):