Benchmark: Object Indexed Properties (Read)

Script Preparation code:

var LIMIT = 10000;

var ARRAY = [];
var OBJECT = {};
var SPARSE_ARRAY = [];
var SPARSE_OBJECT = {};

for (var i = 0; i < LIMIT; i++) {
  ARRAY[i] = i;
  OBJECT[i] = i;
  if (i % 2 === 0) {
    SPARSE_ARRAY[i] = i;
    SPARSE_OBJECT[i] = i;
  }
}

Tests:

Array
var total = 0; var target = ARRAY; for (var i = 0; i < LIMIT; i++) { total += target[i]; } return total;
Object
var total = 0; var target = OBJECT; for (var i = 0; i < LIMIT; i++) { total += target[i]; } return total;
Sparse Array
var total = 0; var target = SPARSE_ARRAY; for (var i = 0; i < LIMIT; i++) { if (i in target) { total += target[i]; } } return total;
Sparse Object
var total = 0; var target = SPARSE_OBJECT; for (var i = 0; i < LIMIT; i++) { if (i in target) { total += target[i]; } } return total;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array
Object
Sparse Array
Sparse Object

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmark test case, specifically testing the performance of accessing properties using different data structures: arrays and objects (including sparse arrays and sparse objects).

**Data Structures Compared**

Three types of data structures are compared:

1. **Arrays**: A dense array with 10,000 elements is created.
2. **Objects**: An object with 10,000 key-value pairs is created.
3. **Sparse Arrays and Objects**: Sparse versions of the above data structures are created by only setting values for every other index.

**Pros and Cons**

Here's a brief overview of each approach:

1. **Arrays**:
	* Pros: Efficient access to elements using array indexing (`array[i]`).
	* Cons: May lead to memory waste due to unused indices.
2. **Objects**:
	* Pros: Allows for flexible data structure with key-value pairs, making it suitable for various use cases.
	* Cons: Accessing properties using `object[key]` can be slower than array indexing.
3. **Sparse Arrays and Objects**:
	* Pros: Reduces memory usage by only allocating space for non-zero values.
	* Cons: May lead to slower performance due to the need to check if a property exists before accessing it (`if (i in target)`).

**Library and Special JS Features**

None of the provided benchmark test cases use external libraries. However, the `in` operator used in sparse array and object access checks is a special JavaScript feature that allows checking if a property exists on an object.

**Other Alternatives**

Alternative approaches to testing array and object access performance could include:

* Using other data structures like linked lists or trees.
* Testing with larger datasets to observe scalability differences.
* Incorporating other microbenchmarks, such as string manipulation or DOM manipulation tasks.

Keep in mind that the specific test case design and variations may be tailored to focus on certain aspects of array and object access performance.

Related benchmarks:

Object Indexed Properties (Read) (version: 0)

Comparing performance of: Array vs Object vs Sparse Array vs Sparse Object

Created: 9 years ago by: Guest

Jump to the latest result

Array

Object

Sparse Array

Sparse 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):