Benchmark: Array push optimization test

HTML Preparation code:

<!--your preparation HTML code goes here-->

Tests:

1
const items = new Array(16); let len = 0; while (len < 8) { items[len++] = Math.random(); } items.length = len;
2
const items = []; let len = 0; while (len < 8) { items[len++] = Math.random(); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 days ago)

User agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/60.5 Safari/605.1.15

Browser/OS: Safari 60 on Ubuntu

View result in a separate tab

Test name	Executions per second
1	11924426.0 Ops/sec
2	18461194.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 20 days ago):

LLMs can make mistakes. Check important info.

The benchmark you provided is designed to compare two different approaches for adding elements to an array in JavaScript, specifically focusing on performance metrics such as execution speed. Here’s a breakdown of the tests conducted, their setups, and considerations for each approach:

### Benchmark Details

#### Test Cases
1. **Test Case 1 (Benchmark Definition 1)**:
   ```javascript
   const items = new Array(16);
   let len = 0;
   while (len < 8) {
       items[len++] = Math.random();
   }
   items.length = len;
   ```
   - **Description**: This method initializes an array `items` with a fixed size of 16 and uses a `while` loop to fill the first 8 elements with random numbers. After adding the elements, it explicitly sets the `length` property of the array to `len`.

2. **Test Case 2 (Benchmark Definition 2)**:
   ```javascript
   const items = [];
   let len = 0;
   while (len < 8) {
       items[len++] = Math.random();
   }
   ```
   - **Description**: This method initializes an empty array `items` and uses a similar `while` loop to populate it with 8 random numbers but does not set the array length afterwards. The length property will automatically adjust as elements are added.

### Performance Outcomes
According to the benchmark results:
- **Test Case 1** (fixed-size array): `8427153` executions per second.
- **Test Case 2** (dynamic array): `12023221` executions per second.

### Comparison of Approaches

1. **Memory Allocation**:
   - **Fixed Size (Test Case 1)**: Pre-allocating an array of size 16 can provide performance benefits in certain scenarios since it allocates memory once. However, if the larger size is unnecessary, this could lead to wasted space.
   - **Dynamic Size (Test Case 2)**: Dynamically allocating space on-the-fly allows for flexibility. The JavaScript engine optimizes memory management, leading to potentially faster operations as the array grows organically without excess pre-allocation.

2. **Array Length Management**:
   - In Test Case 1, the length must be explicitly managed. This might offer slightly more control over the array but adds a small overhead.
   - In Test Case 2, the `length` property is automatically managed by JavaScript, simplifying the code and potentially making it faster.

### Pros and Cons
- **Test Case 1 (Fixed Size)**:
  - **Pros**: Can lead to less frequent memory reallocation if many elements are added, as the size is predetermined.
  - **Cons**: Unused allocated space when the array isn’t fully utilized can be wasteful, and modifying the length is an additional operation.

- **Test Case 2 (Dynamic Size)**:
  - **Pros**: More flexible and easier to implement; less overhead since JavaScript handles the memory allocation.
  - **Cons**: Depending on how many elements you expect to add, frequent resizing (when the array grows beyond its capacity) can incur performance costs.

### Considerations
- The performance results show that for small-sized arrays (like in these tests), the JavaScript engine is likely optimized for handling dynamic arrays efficiently, making the dynamic allocation method faster in this context.
- For large-scale applications, the choice between these approaches should be based on expected usage patterns, including array size and performance profiling.

### Alternatives
- **Using Array Methods**: Instead of manual `while` loops, higher-order functions like `Array.from()` or `map()` could be explored for initialization. However, this approach may lead to more overhead due to function calls and is generally less efficient for large arrays.
- **Typed Arrays**: For scenarios dealing with large sets of numeric data, Typed Arrays (such as `Float32Array`) offer better performance and memory efficiency.
- **Predefined Arrays with Slicing**: Using methods like `slice` to create arrays could also be an alternative, but that injects overhead for duplication and doesn’t necessarily lead to performance improvements for the task at hand.

This analysis should give a clearer understanding of the benchmarking process and guide future decisions about array handling in JavaScript concerning performance and functionality.

Related benchmarks:

Array push optimization test (version: 2)

Comparing performance of: 1 vs 2

Created: 20 days ago by: Registered User

Jump to the latest result

1

2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 20 days ago):