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algorithms : intro to sorting algorithms { insertion sort and selection sort }
- Algorithms are essential for organizing data, including sorting items in memory like arrays and trees.
- Sorting algorithms come with trade-offs and advantages, and this series explores various sorting algorithms.
- This article focuses on insertion sort and selection sort, explaining their time and space complexities, as well as providing implementations.
- Insertion sort involves putting elements in their correct positions by shifting them, with a time complexity of O(n^2).
- With space complexity of O(1), insertion sort is efficient for almost sorted arrays and uses in-place swapping.
- Selection sort involves choosing the smallest element from the unsorted part and swapping it, with a time complexity of O(n^2).
- Selection sort is not stable and may not preserve the order of equal elements, making it suitable for large datasets where swaps are expensive.
- Both algorithms have their strengths and weaknesses, making them suitable for different scenarios based on efficiency and stability requirements.
- Insertion sort is stable, whereas selection sort is not, and both have in-place sorting and minimal memory usage.
- Understanding these sorting algorithms can help in selecting the most appropriate one based on the specific requirements of the dataset being sorted.
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