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(version: 0)
Comparing performance of:
set vs loop
Created:
8 years ago
by:
Guest
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Tests:
set
var rules = [{id: 1, name: 'test1', enabled: false}, {id: 2, name: 'test2', enabled: true}, {id: 3, name: 'test3', enabled: true}, {id: 4, name: 'test4', enabled: true}, {id: 5, name: 'test5', enabled: false}, {id: 6, name: 'test6', enabled: true}, {id: 7, name: 'test7', enabled: false}, {id: 8, name: 'test8', enabled: true}, {id: 9, name: 'test9', enabled: true}, {id: 10, name: 'test10', enabled: true}]; var enabledRuleIds = new Set(rules.reduce((enabledRules, rule) => { if(rule.enabled) { enabledRules.push(rule.id); } return enabledRules; }, []));
loop
var rules = [{id: 1, name: 'test1', enabled: false}, {id: 2, name: 'test2', enabled: true}, {id: 3, name: 'test3', enabled: true}, {id: 4, name: 'test4', enabled: true}, {id: 5, name: 'test5', enabled: false}, {id: 6, name: 'test6', enabled: true}, {id: 7, name: 'test7', enabled: false}, {id: 8, name: 'test8', enabled: true}, {id: 9, name: 'test9', enabled: true}, {id: 10, name: 'test10', enabled: true}]; var enabledRules = rules.filter(r => r.enabled);
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Suite status:
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Test case name
Result
set
loop
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 explaining the provided benchmark. **Benchmark Overview** The provided benchmark measures the execution time of two different approaches: using `Set` data structure and a loop to filter enabled rules. **Approach 1: Using Set Data Structure (Test Name: "set")** In this approach, an array of objects is created with `rules`. Each object has an `enabled` property. The code then creates a new `Set` instance from the filtered rules using the `reduce()` method and the `if (rule.enabled)` condition. **Pros:** * This approach is concise and easy to read. * It uses built-in JavaScript methods, which are optimized for performance. * Sets in JavaScript are implemented as hash tables, providing fast lookups and insertions. **Cons:** * The implementation might be less intuitive than a traditional loop-based approach for those unfamiliar with `Set` data structures. * If the input array is very large, creating a new Set instance might incur additional overhead due to memory allocation and garbage collection. **Approach 2: Using Loop-Based Filtering (Test Name: "loop")** In this approach, an array of objects is created with `rules`. Each object has an `enabled` property. The code then uses a traditional loop-based approach to filter the rules by iterating over the array and checking the `enabled` property. **Pros:** * This approach can be more intuitive for those familiar with loops and conditional statements. * It avoids potential overhead from creating a new Set instance or using built-in methods that might not be as efficient in this specific case. **Cons:** * The implementation is longer and may be less concise than the `Set` based approach. * Loop-based filtering can lead to more overhead due to repeated checks and iterations over the array. **Library Used** In both approaches, the library used is JavaScript's built-in data structures (Arrays) and methods. No external libraries are mentioned in the benchmark definition or test cases. **Special JS Feature/Syntax** The `Set` data structure is a built-in feature of JavaScript, but it was introduced in ECMAScript 2015 (ES6). If you're using an older version of JavaScript that doesn't support Sets, this approach might not work as intended. **Other Alternatives** If you wanted to explore other approaches, here are a few examples: * Using `Array.prototype.filter()` instead of a loop-based approach. * Using `map()` in combination with filtering for an alternative to the Set data structure. * Comparing different JavaScript engines or implementations, such as V8 (Google Chrome) and SpiderMonkey (Firefox). Keep in mind that each of these alternatives might introduce additional overhead or have trade-offs in terms of performance, readability, and maintainability. In conclusion, both approaches have their pros and cons. The `Set` data structure approach is concise and optimized for performance, while the loop-based filtering approach provides more control over the implementation but may incur additional overhead.
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