Benchmark: set.has vs. array.includes but include converting as well

Script Preparation code:

var a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];

Tests:

includes
return a.includes(9)
lookup
var b = new Set(a); return b.has(9)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
includes
lookup

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:153.0) Gecko/20100101 Firefox/153.0

Browser/OS: Firefox 153 on Windows

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includes

70.6M/s

lookup

11.8M/s

View exact numbers

Test name	Executions per second
✓ includes	70,588,880 Ops/sec
lookup	11,756,405 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

The benchmark defined in the provided JSON tests the performance of two different methods for checking if a value exists in a collection: using an array's `includes` method and a `Set`'s `has` method. The benchmark aims to compare the efficiency of these two approaches in terms of execution speed.

### Options Compared

1. **Array's `includes` Method**:
   - **Benchmark Definition**: `return a.includes(9)`
   - **Test Name**: `includes`
   - This method is used to determine whether an array includes a certain value. It functions by iterating through the items in the array, which can result in a linear search.
  
2. **Set's `has` Method**:
   - **Benchmark Definition**: `var b = new Set(a); return b.has(9)`
   - **Test Name**: `lookup`
   - This method checks whether a specific value exists in a `Set`. A `Set` is a built-in JavaScript object that allows the storage of unique values, enabling quick lookups, typically on average in constant time, as it is implemented using a hash table.

### Pros and Cons

#### Array's `includes` Method:
- **Pros**:
  - Simple and straightforward syntax.
  - Suitable for small arrays or cases where performance is not critical.
  
- **Cons**:
  - Linear time complexity (O(n)), meaning that performance degrades as the size of the array grows.
  - May not be efficient for frequent lookups or large datasets.

#### Set's `has` Method:
- **Pros**:
  - Constant time complexity on average (O(1)), allowing for much faster lookup times, especially in large datasets.
  - Automatically manages unique values, eliminating duplicates.
  
- **Cons**:
  - Slightly more verbose, as it requires creating a `Set` from the array before performing lookups.
  - Some overhead is incurred from creating the `Set`, especially if the dataset is small or lookups are infrequent.

### Considerations
- This benchmark is particularly relevant in scenarios involving frequent membership checks on large datasets. For small arrays or infrequent checks, the overhead of creating a `Set` might not justify its use.
- The results from the benchmark indicate a significant performance difference. The `includes` method achieved approximately **41,927,184 executions per second**, while the `has` method resulted in about **3,890,894 executions per second**. This suggests that despite the speed of straightforward usage for `includes`, the performance degradation at scale should be considered.
- When using a `Set`, developers should be aware of the initial overhead incurred from creating the `Set` from the array, which could affect performance in cases where this operation occurs frequently or is done in a tight loop.

### Other Alternatives
Some alternative approaches to consider include:

1. **Using an Object for Lookup**: Instead of a `Set`, one could use a plain object to store keys and check for existence. This can also provide average constant time complexity for lookups.
   
2. **Array.prototype.indexOf()**: An older method which can also check for existence but performs similarly to `includes` (linear complexity).

3. **Binary Search on Sorted Arrays**: If the array can be maintained in a sorted state, binary search can be employed for faster lookups (O(log n)), though this requires additional complexity in managing the sorted order with insertions and deletions.

Choosing between these options will depend on the specific use case, including the expected size of the dataset and the frequency of membership checks required.

set.has vs. array.includes but include converting as well (version: 1)

Comparing performance of: `includes vs lookup`

Created: one year ago by: Guest

Go to the latest result

includes

lookup

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

set.has vs. array.includes but include converting as well (version: 1)

Comparing performance of: includes vs lookup

Created: one year ago by: Guest

Go to the latest result

includes

lookup

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

Related benchmarks

Comparing performance of: `includes vs lookup`