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compose_check
(version: 0)
Comparing performance of:
add2 vs add1_twice vs add1_twice_2 vs add2_arrow vs add1_twice_arrow vs add1_twice_2_arrow
Created:
4 years ago
by:
Guest
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Tests:
add2
function add2(x){ return (x + 1) + 1; } let res = 0; for(let i = 0; i < 10000; i++){ res = add2(res) }
add1_twice
function add1(x){ return x + 1; } function add1_twice(x){ return add1(add1(x)); } let res = 0; for(let i = 0; i < 10000; i++){ res = add1_twice(res) }
add1_twice_2
function add1(x){ return x + 1; } function twice(fn){ return function(x){ return fn(fn(x)); }; } const add1_twice_2 = twice(add1); let res = 0; for(let i = 0; i < 10000; i++){ res = add1_twice_2(res) }
add2_arrow
const add2 = (x) => (x + 1) + 1; let res = 0; for(let i = 0; i < 10000; i++){ res = add2(res) }
add1_twice_arrow
const add1 = (x) => x + 1; const add1_twice = (x) => add1(add1(x)); let res = 0; for(let i = 0; i < 10000; i++){ res = add1_twice(res) }
add1_twice_2_arrow
const add1 = (x) => x + 1; const twice = (f) => (x) => f(f(x)); const add1_twice = twice(add1); let res = 0; for(let i = 0; i < 10000; i++){ res = add1_twice(res) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (6)
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Test case name
Result
add2
add1_twice
add1_twice_2
add2_arrow
add1_twice_arrow
add1_twice_2_arrow
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Measuring the performance of JavaScript code is crucial for optimizing and fine-tuning our applications. Let's break down the provided benchmark definition and test cases to understand what's being tested. **Benchmark Definition** The `compose_check` benchmark definition is empty, which means that it doesn't specify any particular function or logic to be executed. **Test Cases** There are five test cases: 1. **add2**: This test case defines a simple function `add2(x)` that returns `(x + 1) + 1`. The test executes this function in a loop, appending the result to another variable `res`, for a total of 10,000 iterations. 2. **add1_twice**: This test case defines two functions: `add1(x)` and `add1_twice(res)`. `add1(x)` simply returns `x + 1`, while `add1_twice(res)` calls `add1` twice in a row on the input `res`. 3. **add1_twice_2**: This test case defines two functions: `add1(x)` and `twice(fn)`. The `twice` function takes another function as an argument, creates a new function that calls itself with the original argument twice, and returns this new function. 4. **add2_arrow**: Similar to `add2`, but defined using arrow function syntax (`(x) => (x + 1) + 1;`). This is equivalent to a traditional function definition (`function add2(x){...}`) 5. **add1_twice_arrow**: Similar to `add1_twice`, but defined using arrow function syntax. **Comparison** The main difference between these test cases lies in how the functions are composed and executed: * `add2` and `add2_arrow` execute a simple arithmetic operation in a loop. * `add1_twice` executes two calls to `add1` on the input `res`. * `add1_twice_2` uses a higher-order function (`twice`) to create a new function that calls itself twice. * `add1_twice_arrow` uses arrow function syntax to define and call the `add1_twice` logic. **Pros and Cons** Here's a brief overview of each approach: * **Simple loops**: These tests are straightforward and easy to understand, but they don't require any special consideration for function composition or higher-order functions. * **Function composition**: Tests like `add1_twice_2` demonstrate how to create new functions by composing existing ones. This is a fundamental concept in functional programming. * **Arrow function syntax**: Using arrow functions can simplify code and make it more concise, but it's essential to consider the nuances of this syntax when defining complex functions. **Performance Results** The performance results show that the `add2_arrow` test case is slightly faster than the traditional `add2` implementation. This might be due to the optimizations provided by the JavaScript engine for arrow function expressions. However, the differences are relatively small, and other factors like caching, optimization, and platform-specific behavior can affect the actual performance results. **Conclusion** In conclusion, this benchmark highlights the importance of understanding how functions are composed and executed in JavaScript. By examining different test cases and their approaches, we can gain insights into the trade-offs between simplicity, conciseness, and performance.
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