Benchmark: computed vs mutation

Tests:

compute
let obj = [], result = {}, count = 0 let int = setInterval(qwe, 1) function qwe () { if (count > 2000) { clearInterval(int) } count++ obj.push(count) return obj.forEach((item) => { result[item] = `rand${item}` }) }
mutate
let obj = [], result = {}, count = 0 let int = setInterval(qwe, 1) function qwe () { if (count > 2000) { clearInterval(int) } count++ obj.push(count) if (count % 2 === 0) { result[count] = `rand${count}` } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
compute
mutate

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

The provided JSON represents two microbenchmarks on JavaScript, specifically comparing the performance of "computed" and "mutation" approaches.

**Benchmark Definition:**

The benchmark definition is not explicitly stated in the provided JSON, but based on the test cases, we can infer that it's testing the difference between these two approaches:

* **Computed**: In this approach, a new object `result` is created for each iteration of the loop, and its properties are set using object literals (`obj.forEach((item) => { result[item] = `rand${item}` })`). This approach creates a new object reference on each iteration.
* **Mutation**: In this approach, the same `result` object is reused and its properties are modified using the `count % 2 === 0` condition. This approach modifies an existing object reference.

**Options Compared:**

The two options being compared are:

1. **Computed**: Creating a new object for each iteration of the loop.
2. **Mutation**: Reusing the same object and modifying its properties on each iteration.

**Pros and Cons:**

* **Computed:**
	+ Pros:
		- Less memory overhead, as a new object is created for each iteration.
		- Easier to reason about and predict the behavior, as a new object reference is used.
	+ Cons:
		- Can lead to performance issues due to the creation of multiple objects.
* **Mutation:**
	+ Pros:
		- Less memory overhead, as only one object reference exists.
		- Can be more efficient in terms of memory allocation and deallocation.
	+ Cons:
		- More complex to reason about and predict the behavior, as an existing object reference is modified.

**Other Considerations:**

* **Cache Locality:** In the "Computed" approach, each iteration creates a new object, which can lead to cache locality issues. The browser's cache might not be able to keep up with the rapid creation of objects, leading to slower performance.
* **Garbage Collection:** In the "Mutation" approach, the same object reference is reused, which can lead to garbage collection overhead when the object needs to be released.

**Library and Special JS Features:**

In neither test case does the provided JSON include any libraries or special JavaScript features. The code is self-contained and uses only built-in JavaScript features.

**Alternatives:**

Some alternative approaches that could have been tested in this benchmark include:

* **Using a mutable object with array literals:** Instead of using `obj.push(count)`, an array literal could be used to create a new array on each iteration, and then the properties of the resulting array could be set.
* **Using a different data structure:** Other data structures like sets or maps could have been used instead of objects, potentially changing the performance characteristics.

It's worth noting that these alternatives might not change the general trend of the results, but they could provide additional insights into the performance trade-offs involved.

Related benchmarks:

computed vs mutation (version: 1)

Comparing performance of: compute vs mutate

Created: 7 years ago by: Registered User

Jump to the latest result

compute

mutate

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):