A high-performance, production-ready library of list-based algorithms, forged by FPIV. This is the foundational component of our digital arsenal, providing the essential, battle-tested tools for achieving algorithmic supremacy in Dart.
This library was built not just to provide functions, but to provide a competitive edge.
- ⚔️ Comprehensive Arsenal: An extensive collection of over 40 algorithms, covering everything from fundamental sorting and searching to highly specialized and advanced list manipulation techniques.
- 🚀 Performance-Driven: Every algorithm is implemented with a focus on efficiency. Our detailed benchmarks demonstrate superior performance, allowing you to build fast and responsive applications.
- 🛡️ Production-Ready & Robust: With over 140+ unit tests, thorough documentation, and robust error handling for edge cases,
fpiv_listis built for reliable use in production environments. - 🧬 Modern & Type-Safe: Written in modern Dart, leveraging generics (
<T extends Comparable<T>>) to provide a clean, type-safe, and predictable API.
This library is a complete toolkit for list manipulation, including (but not limited to):
- Advanced & Basic Sorting:
- Quick Sort, Merge Sort, Heap Sort, Comb Sort, Radix Sort, Bucket Sort, and over 20 more powerful sorting algorithms.
- Efficient Searching:
- Binary Search (for sorted lists), Linear Search.
- Subarray & Subsequence Problems:
- Kadane's Algorithm, Max Product Subarray, Longest Increasing Subsequence, Two Sum, and more.
- Core List Utilities:
- Find Max/Min, Reverse, Rotate, Find Duplicates, Remove Duplicates, Prefix Sum, and more.
For a complete list of all available functions, please refer to the API documentation.
Add fpiv_list to your pubspec.yaml dependencies:
dependencies:
fpiv_list: ^0.1.0 # Check pub.dev for the latest versionThen, import the library in your Dart code:
import 'package:fpiv_list/fpiv_list.dart';import 'package:fpiv_list/fpiv_list.dart';
void main() {
var numbers = [10, 7, 8, 9, 1, 5];
print('Original List: $numbers');
// Use a high-performance sort from the arsenal
quickSort(numbers, 0, numbers.length - 1);
print('Sorted with Quick Sort: $numbers');
// Find an element efficiently
final index = binarySearch(numbers, 8);
print('Found 8 at index: $index'); // Output: Found 8 at index: 2
}Performance is a core feature. Our benchmarks show a clear distinction between efficient and inefficient algorithms.
Sample Benchmark: 10,000 Elements
| Algorithm | List Size | Time (ms) |
|---|---|---|
| Bubble Sort | 1,000 | 11 ms |
| Insertion Sort | 1,000 | 5 ms |
| Selection Sort | 1,000 | 7 ms |
| Gnome Sort | 1,000 | 9 ms |
| Odd-Even Sort | 1,000 | 11 ms |
| Pancake Sort | 1,000 | 10 ms |
| Cycle Sort | 1,000 | 20 ms |
| Comb Sort | 1,000 | 2 ms |
| Stooge Sort (slow!) | 1,000 | 1241 ms |
| Quick Sort | 1,000 | 1 ms |
| Merge Sort | 1,000 | 5 ms |
| Heap Sort | 1,000 | 1 ms |
| Shell Sort | 1,000 | 2 ms |
| Counting Sort | 1,000 | 1 ms |
| Radix Sort | 1,000 | 4 ms |
| Pigeonhole Sort | 1,000 | 1 ms |
| Bitonic Sort | 1,000 | 2 ms |
| Linear Search | 1,000 | 0 ms |
| Binary Search | 1,000 | 0 ms |
| Find Max | 1,000 | 0 ms |
| Find Min | 1,000 | 0 ms |
| Reverse List | 1,000 | 0 ms |
| Find Duplicates | 1,000 | 2 ms |
| Remove Duplicates | 1,000 | 2 ms |
| Rotate Array Right | 1,000 | 0 ms |
| Quickselect (k=size/2) | 1,000 | 0 ms |
| Kadane's Algorithm | 1,000 | 0 ms |
| Max Product Subarray | 1,000 | 2 ms |
| Max Sum (k=10) | 1,000 | 0 ms |
| Min Sum (k=10) | 1,000 | 0 ms |
| Average (k=10) | 1,000 | 0 ms |
| LIS Binary Search | 1,000 | 0 ms |
| Two Sum Sorted | 1,000 | 0 ms |
| Prefix Sum Calculation | 1,000 | 0 ms |
| Algorithm | List Size | Time (ms) |
|---|---|---|
| Bubble Sort | 10,000 | 938 ms |
| Insertion Sort | 10,000 | 258 ms |
| Selection Sort | 10,000 | 412 ms |
| Gnome Sort | 10,000 | 559 ms |
| Odd-Even Sort | 10,000 | 631 ms |
| Pancake Sort | 10,000 | 645 ms |
| Cycle Sort | 10,000 | 1312 ms |
| Comb Sort | 10,000 | 5 ms |
For complete results and instructions on how to run the benchmarks on your own machine, see the BENCHMARK.md file.
Contributions are welcome. We aim to build the most powerful algorithmic arsenal in the Dart ecosystem. Please open an issue on GitHub to discuss any changes or new features.
This project is licensed under the MIT License - see the LICENSE file for details.