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isNaN vs Object
(version: 0)
Comparing performance of:
isNaN vs Object
Created:
3 years ago
by:
Guest
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Tests:
isNaN
const nums = '0123456789'; let i = 0; while (++i < 10000) isNaN(nums[i % 10]);
Object
const obj = {'0':1,'1':1,'2':1,'3':1,'4':1,'5':1,'6':1,'7':1,'8':1,'9':1}; const nums = '0123456789'; let i = 0; while (++i < 10000) obj[nums[i % 10]];
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
isNaN
Object
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the world of JavaScript microbenchmarks! **Benchmark Overview** MeasureThat.net allows users to create and run JavaScript microbenchmarks, which are small pieces of code that measure the performance of specific parts of an application. The benchmark in question compares two approaches: `isNaN` and object lookups. **Options Compared** The two options being compared are: 1. **isNaN**: This function checks if a given value is Not a Number (NaN). In this case, it's used to iterate over the digits '0' through '9', incrementing a counter for each iteration. 2. **Object Lookup**: This approach uses an object to store the numbers '0' through '9' as keys and their values are arbitrary. The benchmark iterates over the same range of numbers, looking up each digit in the object. **Pros and Cons** ### isNaN Pros: * Lightweight: `isNaN` is a simple function that only checks if a value is NaN. * Fast: This approach has low overhead since it doesn't require accessing an object or performing any additional operations. Cons: * Limited to numeric values: `isNaN` only works with numeric values, which might limit its usefulness for non-numeric tests. ### Object Lookup Pros: * Flexible: This approach can be used to test a wide range of values, not just numbers. * Efficient: Accessing an object is often faster than calling a function like `isNaN`. Cons: * Heavier: Creating and accessing an object requires more resources than simply checking if a value is NaN. **Library Usage** In this benchmark, no libraries are explicitly mentioned. However, it's worth noting that some JavaScript environments might use built-in optimizations or caching mechanisms for certain functions, which could affect the results. **Special JS Features/Syntax** None of the test cases explicitly utilize special JavaScript features like async/await, Promises, or Web Workers. **Other Considerations** When interpreting these results, keep in mind: * The benchmark is running on a Chrome 104 browser on a desktop platform. * The test is designed to measure the performance of the two approaches over a range of iterations (10,000 times). **Alternative Approaches** If you wanted to create similar benchmarks, consider exploring other approaches, such as: 1. Using `Number.isNaN` instead of `isNaN`. 2. Comparing string manipulation techniques (e.g., regex vs. substring). 3. Investigating the performance of different data structures (e.g., arrays vs. objects). By experimenting with these alternative approaches, you can gain a deeper understanding of JavaScript's performance characteristics and optimize your code for specific use cases.
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