Benchmark: Object property access or saved pointer

Script Preparation code:

var data = {
    id: 1,
    a: 1,
    b: '',
    c: '',
    d: false,
    e: '',
    f: 1,
    g: {
        h: 1,
        i: 'Dannag'
    },
    k: 1,
    l: 1,
}

Tests:

Property access
let result = 0; for (const property in data) { if (typeof data[property] === 'number' && Number.isInteger(data[property])) { result += data[property]; } }
Pointer
let result = 0; for (const property in data) { const value = data[property]; if (typeof value === 'number' && Number.isInteger(value)) { result += value; } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Property access
Pointer

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.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Description**

The provided JSON represents a benchmark test case named "Object property access or saved pointer". This benchmark compares two approaches to accessing object properties in JavaScript:

1. **Property Access**: This approach uses a traditional `for...in` loop to iterate over the object's properties and checks if each value is an integer using `Number.isInteger()`.
2. **Saved Pointer**: This approach uses a variable (`value`) to store the current property value, which is then checked for being an integer.

**Options Compared**

The two approaches are compared in terms of performance, with the goal of determining which one is faster and more efficient.

**Pros and Cons**

* **Property Access**
	+ Pros:
		- Simpler code structure
		- Easier to understand and maintain
	+ Cons:
		- May involve additional overhead due to iterating over the entire object's properties
		- Could be slower due to unnecessary checks or iterations
* **Saved Pointer**
	+ Pros:
		- Reduces overhead by only checking each property value once
		- Can lead to better performance if most values are integers
	+ Cons:
		- More complex code structure, making it harder to understand and maintain
		- May not be suitable for all use cases where all properties need to be checked

**Library/Features Used**

In the benchmark definition JSON, no specific JavaScript library or feature is used. However, some features of modern JavaScript are implied:

* `for...in` loop: a built-in JavaScript construct for iterating over object properties
* `Number.isInteger()`: a built-in JavaScript method for checking if a value is an integer

**Other Considerations**

When writing performance-critical code, it's essential to consider the following factors:

* **Cache efficiency**: How does each approach affect cache behavior? Some approaches might cause more cache misses or evictions, leading to slower performance.
* **Branch prediction**: Modern CPUs rely heavily on branch prediction to improve execution speed. Some approaches might lead to more branches or unexpected jumps, making it harder for the CPU to predict the next instruction.
* **Cache locality**: How do each approach affect cache locality? Good cache locality can reduce memory access latency and improve performance.

**Alternatives**

If you're interested in exploring other JavaScript benchmarking options, consider:

1. **Google Benchmark**: A popular benchmarking library for JavaScript that provides a more extensive range of test cases and features.
2. **jsperf**: An online benchmarking tool that allows you to compare the performance of different JavaScript code snippets.
3. **Benchmarking frameworks like Jest or Mocha**, which provide built-in support for writing and running benchmarks.

Remember, when it comes to performance optimization, understanding the underlying mechanics and trade-offs is crucial.

Related benchmarks:

Object property access or saved pointer (version: 0)

Comparing performance of: Property access vs Pointer

Created: 2 years ago by: Guest

Jump to the latest result

Property access

Pointer

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):