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fib test
(version: 0)
Comparing performance of:
loop vs better?
Created:
8 years ago
by:
Guest
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Tests:
loop
function fibonacci(num){ var a = 1, b = 0, temp; while (num >= 0){ temp = a; a = a + b; b = temp; num--; } return b; } fibonacci(20);
better?
function fibonacci(n) { return Math.round( (Math.pow((1 + Math.sqrt(5)) / 2, n) - Math.pow(-2 / (1 + Math.sqrt(5)), n)) / Math.sqrt(5) ); } fibonacci(20);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
loop
better?
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
10 months ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36 Edg/138.0.0.0
Browser/OS:
Chrome 138 on Windows
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Test name
Executions per second
loop
19791720.0 Ops/sec
better?
47203452.0 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the benchmark analysis. **Benchmark Purpose** The MeasureThat.net benchmark measures the performance of the JavaScript function `fibonacci` with two different implementations: a traditional loop-based approach and a closed-form expression using mathematical constants. **Options Compared** 1. **Loop-Based Approach**: The first implementation uses a while loop to calculate the Fibonacci sequence. 2. **Closed-Form Expression**: The second implementation uses the Binet's formula to directly calculate the nth Fibonacci number, without iterating at all. **Pros and Cons of Each Approach** 1. **Loop-Based Approach** * Pros: + Easy to understand and implement for beginners. + Can be optimized with techniques like memoization or caching. * Cons: + Inefficient for large values of n, as it has a time complexity of O(n). 2. **Closed-Form Expression** * Pros: + Much faster for large values of n, due to its linear time complexity (O(log n)). + Eliminates the need for iterations. * Cons: + Requires knowledge of mathematical constants and formulas. + May be harder to understand and implement for beginners. **Library Used** In this benchmark, none. The `fibonacci` function only uses basic JavaScript arithmetic operations (e.g., addition, multiplication). **Special JS Features/Syntax** There are no specific JavaScript features or syntax used in these implementations. Both approaches use standard JavaScript programming constructs. **Other Considerations** * **Cache and Optimization**: The loop-based approach can be optimized by caching the results of previously computed Fibonacci numbers to avoid redundant calculations. * **Browser Variability**: The benchmark measures performance across different browsers (in this case, only Chrome 59). This is important because different browsers may optimize JavaScript execution differently. **Alternatives** If you want to explore alternative approaches or optimizations for the `fibonacci` function, here are a few: 1. **Iterative vs. Recursive**: Implementing the Fibonacci sequence using recursion can be faster than iteration due to the overhead of function calls. However, recursive solutions often require more memory and may cause stack overflows. 2. **Memoization and Caching**: Storing previously computed values in an array or object (memoization) can speed up computation by avoiding redundant calculations. 3. **Parallel Processing**: For very large values of n, parallel processing using Web Workers or other concurrency APIs might be beneficial to distribute the computational load across multiple threads. These alternatives require a deeper understanding of JavaScript optimization techniques and may not provide significant performance gains for smaller values of n.
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