Benchmark: stateForId - MeasureThat.net

Tests:

ARR
const arr = ['1', '2', '3']; const updateArr = (id) => arr.includes(id) ? arr.filter((item) => item !== id) : [...arr, id]; updateArr(4);
OBJECT
const obj = { '1': true, '2': true, '3': true, }; const updateObj = (id) => obj.hasOwnProperty(id) ? delete obj[id] : {...obj, [id]: true}; updateObj(4);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
ARR
OBJECT

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark being tested on MeasureThat.net.

**Benchmark Overview**

The benchmark measures the performance of two different data structure update methods: array (`arr`) and object (`obj`). The test case "stateForId" uses these two data structures to demonstrate an id-based update operation.

**Array Update Method ("ARR")**

In this test case, a constant array `arr` is created with three initial elements. An arrow function `updateArr` is then defined to update the array based on the presence of a specific element (`id`). If `id` is found in the array, it filters out all occurrences of `id`, otherwise, it appends a new element with the value `id`.

The test case then calls `updateArr(4)` and measures the execution time.

**Object Update Method ("OBJECT")**

In this second test case, an object `obj` is created with three initial key-value pairs. An arrow function `updateObj` is defined to update the object based on the presence of a specific property (`id`). If `id` is found in the object, it deletes the corresponding property using `delete`, otherwise, it adds a new property with the value `true`.

The test case then calls `updateObj(4)` and measures the execution time.

**Comparison of Approaches**

Both methods have their pros and cons:

*   **Array Update Method ("ARR")**
    *   Pros:
        *   Lightweight data structure (no object overhead)
        *   Fast lookup and filtering operations
    *   Cons:
        *   Less intuitive for updates based on values, not indices
        *   Potential performance issues with large datasets due to array resizing
*   **Object Update Method ("OBJECT")**
    *   Pros:
        *   Intuitive for updates based on properties (e.g., `id`)
        *   Can efficiently handle large datasets using object references
    *   Cons:
        *   Heavier data structure compared to arrays
        *   Potential performance issues with property lookups and deletions

**Library/Functionality Used**

In both test cases, the following libraries/functions are used:

*   `includes()` method for array lookup (JavaScript built-in)
*   `filter()` method for array filtering (JavaScript built-in)
*   `delete` operator for object property deletion (JavaScript built-in)

No external libraries or frameworks are required.

**Special JS Features/Syntax**

The test cases utilize the following special JavaScript features:

*   Arrow functions (`() => { ... }`)
*   Template literals (`\r\nconst updateArr = (id) => arr.includes(id) ? arr.filter((item) => item !== id) : [...arr, id];`)

These features allow for concise and readable code without the need for explicit function declarations.

**Alternatives**

Other alternatives to the array and object update methods include:

*   Using `Map` or `WeakMap` data structures instead of objects
*   Utilizing `Set` data structures for fast membership testing and updates
*   Employing custom data structure implementations, such as a hybrid array-object data type

These alternatives may offer performance benefits or specific use case advantages but come with their own trade-offs in terms of complexity, memory usage, and implementation overhead.

Related benchmarks:

stateForId (version: 0)

Comparing performance of: ARR vs OBJECT

Created: 4 years ago by: Registered User

Jump to the latest result

ARR

OBJECT

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):