Benchmark: memoized object assignment (new objects)

HTML Preparation code:


  <script src="https://cdn.jsdelivr.net/npm/memoize-one@5.1.1/dist/memoize-one.js"></script>
  <script src="https://cdn.jsdelivr.net/npm/moize@5.4.7/dist/moize.js"></script>

Script Preparation code:

var fn = function(a, b) {
  Object.assign(a, b);
}


var memoizeOneFn = window.memoizeOne(fn);
var moizeFn = window.moize.default(fn);

var assignee = {a: 1};
var objToAssign = {foo: 'bar', bar: 'foo', foobar: { z: 26, y: 25, x: 24 }};

Tests:

baseline
fn(assignee, {...objToAssign});
memoizeOne
memoizeOneFn(assignee, {...objToAssign});
moize
moizeFn(assignee, {...objToAssign})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
baseline
memoizeOne
moize

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.

Let's break down the provided benchmark definition and explain what is being tested, compared options, pros and cons, library usage, and other considerations.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark that tests the performance of three different approaches to assign values to an object:

1. **baseline**: The original `Object.assign()` method.
2. **memoizeOneFn**: A memoized version of the original function, created using the `window.memoizeOne` library.
3. **moizeFn**: Another memoized version of the original function, created using the `window.moize.default` function from the Moize library.

**Options Compared**

The three options are compared to measure their performance in terms of executions per second (ExecutionsPerSecond) for a specific input (`objToAssign`) passed to each function.

**Pros and Cons of Each Approach**

1. **baseline**: The original `Object.assign()` method is a widely supported and well-established method for assigning values to objects. It has a small overhead due to its iterative nature, but it's generally efficient.
2. **memoizeOneFn**: Memoization can improve performance by caching results for frequently called functions. In this case, the memoized version of `Object.assign()` should be faster since it avoids redundant assignments.
3. **moizeFn**: The Moize library provides a more lightweight and efficient memoization implementation compared to `window.memoizeOne`. However, its API might be less intuitive or feature-rich.

**Library Usage**

1. `window.memoizeOne`: A library that wraps the original function with memoization functionality. It's designed for caching results of expensive function calls.
2. `window.moize.default`: A lightweight memoization library provided by Moize. It's optimized for small functions and provides a simple, intuitive API.

**Other Considerations**

* The benchmark is running on Chrome 85 on Windows 7, which might affect the performance results due to various factors like hardware, browser version, and operating system.
* The input object (`objToAssign`) is large, with multiple nested properties. This can impact the performance of each function.

**Alternatives**

Other alternatives for memoization or optimizing assignments could include:

1. **Using a custom implementation**: Instead of relying on third-party libraries, you could implement your own memoization logic to reduce overhead and dependencies.
2. **Caching mechanisms**: Other caching mechanisms like Redis or a simple in-memory cache might be more suitable depending on the specific use case.
3. **Just-In-Time (JIT) compilation**: Some JavaScript engines, like V8 (used by Chrome), support JIT compilation, which can lead to faster execution times for certain workloads.

Keep in mind that these alternatives would require additional development effort and potentially introduce complexity.

Related benchmarks:

memoized object assignment (new objects) (version: 0)

Comparing performance of: baseline vs memoizeOne vs moize

Created: 5 years ago by: Registered User

Jump to the latest result

baseline

memoizeOne

moize

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):