Benchmark: Find shortest array length3

Script Preparation code:

var arrays = Array.from({ length: 1000 }).map(() => new Array((Math.random() * 1000 | 0)).fill(0));
function min_one(arrays) {
  return Math.min(...arrays.map(arr => arr.length));
}
function min_two(arrays) {
  	var smallest = arrays[0].length;
	for (var i = 1; i < arrays.length; i++) {
      var arr_len = arrays[i].length;
      if (arr_len < smallest) smallest = arr_len;
	}
    return smallest;
}

Tests:

Math.min with spread and map
min_one(arrays);
For loop with bitwise min
min_two(arrays);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.min with spread and map
For loop with bitwise min

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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Let's dive into explaining the benchmark.

**Benchmark Definition JSON**

The provided JSON represents a JavaScript microbenchmark that tests two different approaches to find the shortest array length among multiple arrays. The benchmark is defined by two functions:

1. `min_one(arrays)`: This function uses the spread operator (`...`) and the `map()` method to calculate the minimum length of all arrays in the input.
2. `min_two(arrays)`: This function uses a traditional for loop to iterate through each array in the input and keep track of the shortest length.

**Options Compared**

The two functions compared are:

1. **Spread Operator (`...`) + Map**: This approach uses the spread operator to create an array of all lengths, and then uses the `map()` method to calculate the minimum length.
2. **Traditional For Loop**: This approach uses a traditional for loop to iterate through each array in the input and keep track of the shortest length.

**Pros and Cons**

* **Spread Operator + Map**:
	+ Pros: Concise and readable code, leverages modern JavaScript features, and can be faster due to the use of `map()`.
	+ Cons: May have higher overhead due to the creation of an intermediate array, and may not perform well for very large inputs.
* **Traditional For Loop**:
	+ Pros: Can be more intuitive and easier to understand for those familiar with traditional loop structures, and may have lower overhead for large inputs.
	+ Cons: Code can be longer and less readable, and may not leverage modern JavaScript features.

**Library Usage**

There is no explicit library usage in this benchmark. However, the `Array.from()` method is used to create an array of 1000 random arrays with length between 0 and 1000.

**Special JS Feature/Syntax**

The benchmark uses the spread operator (`...`), which is a modern JavaScript feature introduced in ECMAScript 2015 (ES6). The spread operator allows for concisely spreading elements of an array into another array or object.

**Other Considerations**

* **Cache Warm-up**: Both functions may benefit from some initial cache warm-up to reduce the overhead of repeated executions.
* **Array Size and Distribution**: The benchmark uses 1000 random arrays with length between 0 and 1000. The distribution of lengths can affect the performance of both functions.

**Alternatives**

Other alternatives for finding the shortest array length could include:

1. Using a more traditional approach with `reduce()` or `indexOf()`.
2. Utilizing libraries like Lodash or Ramda, which provide optimized functions for finding minimum values.
3. Implementing a custom algorithm using bitwise operations, as seen in the `min_two(arrays)` function.

Keep in mind that these alternatives may not be as concise or readable as the spread operator + map approach, and their performance may vary depending on the specific use case.

Related benchmarks:

Find shortest array length3 (version: 0)

Math.min with spread or for loop

Comparing performance of: Math.min with spread and map vs For loop with bitwise min

Created: 5 years ago by: Guest

Jump to the latest result

Math.min with spread and map

For loop with bitwise min

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):