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map vs ifelse vs switch test
(version: 0)
Comparing performance of:
map vs if/else vs swticth
Created:
4 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
const statusMap = new Map([ [0, 'zero'], [1, 'one'], [2, 'two'], [3, 'three'], [4, 'four'], ]); function getStatusByMap(value) { return statusMap.get(value); }; function getStatusBySwitch(value) { switch (value) { case 0: return 'zero'; case 1: return 'one'; case 2: return 'two'; case 3: return 'three'; case 4: return 'four'; default: return 'Undefined'; } }; function getStatusByIfElse(value) { if (value === 0) { return 'Initializing'; } else if (value === 1) { return 'zero'; } else if (value === 2) { return 'one'; } else if (value === 3) { return 'two'; } else if (value === 4) { return 'Error'; } }; var i = 0; var count = 1000; var a;
Tests:
map
for (i = 0; i < count; i++) { getStatusByMap(i % 5) }
if/else
for (i = 0; i < count; i++) { getStatusByIfElse(i % 5) }
swticth
for (i = 0; i < count; i++) { getStatusBySwitch(i % 5) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
map
if/else
swticth
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
8 months ago
)
User agent:
Mozilla/5.0 (Android 14; Mobile; rv:143.0) Gecko/143.0 Firefox/143.0
Browser/OS:
Firefox Mobile 143 on Android
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Embed Benchmark Result
Test name
Executions per second
map
244571.0 Ops/sec
if/else
45900.2 Ops/sec
swticth
206497.9 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Benchmark Overview** The provided JSON represents a JavaScript microbenchmark test, specifically measuring the performance of three different approaches to map data: `Map`, `if/else` conditional statements, and a custom `switch` statement. **Approach 1: Map Data Structure** The first approach uses a `Map` data structure to store and retrieve values. The `getStatusByMap` function takes an integer value as input and returns the corresponding string value from the map. **Pros:** * Fast lookups: Maps provide O(1) average time complexity for lookups, making them suitable for large datasets. * Memory efficiency: Maps use less memory compared to other data structures like arrays or objects. **Cons:** * Limited access methods: Map has limited access methods (e.g., `get()`, `set()`), which may limit its flexibility in certain scenarios. * No built-in ordering: Maps do not maintain any natural order, which can make it harder to perform operations that rely on order, like sorting or indexing. **Approach 2: if/else Conditional Statements** The second approach uses a series of nested `if/else` conditional statements to determine the output value based on the input integer. **Pros:** * Easy to implement and understand: The code is straightforward and easy to comprehend. * Works well with small datasets: If-else statements perform reasonably well for small datasets or simple logic. **Cons:** * Slow performance: Nested if/else statements can lead to slow performance, especially for large inputs or complex logic. * Limited scalability: As the number of cases increases, the code becomes harder to maintain and debug. **Approach 3: switch Statement with custom Case Handling** The third approach uses a custom `switch` statement with case handling to map input integers to corresponding output values. This implementation is similar to the original but with a switch statement instead of if/else. **Pros:** * Efficient execution: Switch statements can be faster than if/else for larger datasets, as they allow direct branching. * Easy maintenance: The code remains easy to comprehend and modify compared to nested if/else structures. **Cons:** * Limited flexibility: Switch statements require the exact case value to match an output, limiting flexibility in certain scenarios. * May lead to spaghetti code: If not implemented carefully, switch cases can become complex and hard to maintain. **Library Usage** The `Map` data structure is a native JavaScript built-in, which means it's part of the language itself. There's no additional library required for its usage. **Special JS Features/Syntax** This benchmark doesn't utilize any special JavaScript features or syntax beyond standard ES6+ constructs (e.g., arrow functions, template literals). If you wanted to explore specific advanced topics like async/await or Promises, this benchmark wouldn't be the best fit. **Alternatives** For similar microbenchmarking purposes, you might consider exploring other approaches, such as: 1. Using a library like Lodash's `findKey` function for map-like behavior. 2. Implementing custom binary search algorithms for efficient lookup. 3. Comparing array-based approaches (e.g., using an index table). 4. Utilizing modern JavaScript features like async/await for more complex, concurrent test cases. When choosing alternative methods, consider the specific requirements of your project and how much overhead you're willing to introduce in terms of complexity or performance impact.
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