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Multiple args VS Object arg
(version: 0)
Comparing performance of:
Multi args (1) vs Multi args (2) vs Single arg (1) vs Single arg (2)
Created:
6 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
function multiArgs(a, b, c, d, e, f, g, h) { return a + b + c + d + e + f + g + h } function multiArgs2(...args) { return args.reduce((acc, val) => acc += val, 0) } function singleArg(obj) { return obj.a + obj.b + obj.c + obj.d + obj.e + obj.f + obj.g + obj.h } function singleArg2(obj) { return Object.values(obj).reduce((acc, val) => acc += val, 0) }
Tests:
Multi args (1)
for (let i = 0; i < 10000; ++i) { multiArgs(1, 2, 3, 4, 5, 6, 7, 8) }
Multi args (2)
for (let i = 0; i < 10000; ++i) { multiArgs2(1, 2, 3, 4, 5, 6, 7, 8) }
Single arg (1)
for (let i = 0; i < 10000; ++i) { singleArg({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: 7, h: 8 }) }
Single arg (2)
for (let i = 0; i < 10000; ++i) { singleArg2({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: 7, h: 8 }) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (4)
Previous results
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Test case name
Result
Multi args (1)
Multi args (2)
Single arg (1)
Single arg (2)
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to help explain the benchmark. **Overview** The benchmark measures the performance of three different approaches for calculating the sum of eight numbers: 1. **Multi-argument function**: `multiArgs(a, b, c, d, e, f, g, h)` 2. **Rest parameter function**: `multiArgs2(...args)` 3. **Object property access function**: `singleArg(obj)` **Options Compared** The benchmark compares the performance of each approach on a dataset of 10000 iterations with different input values. * The multi-argument function takes individual arguments, while the rest parameter function uses an array of arguments. * The object property access function accesses properties of an object to calculate the sum. **Pros and Cons** 1. **Multi-argument function**: This approach is straightforward but may not be as efficient due to the overhead of passing separate arguments. * Pros: Easy to understand, no dependencies required. * Cons: May be slower due to argument passing overhead. 2. **Rest parameter function**: This approach uses an array of arguments and can be more efficient than the multi-argument function. * Pros: More concise, potentially faster execution time. * Cons: Requires JavaScript support for rest parameters (introduced in ECMAScript 2015). 3. **Object property access function**: This approach accesses properties of an object to calculate the sum. * Pros: No dependencies required, easy to understand. * Cons: May not be as efficient due to object lookup overhead. **Other Considerations** * The benchmark assumes that JavaScript is used as the programming language for performance measurement. If you're using a different language or environment, you might need to adjust the test cases accordingly. * Modern JavaScript engines often have optimizations and caching mechanisms that can impact performance. This benchmark may not be representative of real-world scenarios. **Library and Special JS Features** There are no libraries involved in this benchmark. No special JavaScript features like async/await or ES6 classes are used. **Alternatives** If you're looking for alternative approaches, consider the following: 1. **Built-in functions**: JavaScript has built-in functions like `reduce()` (for arrays) and `Object.values()`. These might be more efficient than using custom functions. 2. **Native arithmetic operations**: Using native arithmetic operations (e.g., addition) can often be faster than using JavaScript functions. The provided benchmark allows users to compare the performance of different approaches on a microbenchmarking scale, providing insights into optimization techniques for specific use cases.
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