chore: sync content to repo (#10351)

Co-authored-by: nilbuild <4921183+nilbuild@users.noreply.github.com>
2026-09-22 05:05:53 +08:00 · 2026-09-17 10:15:17 +02:00
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 # A* Algorithm

-A* is a pathfinding and graph traversal algorithm that finds the shortest path between two nodes. It combines the guarantees of Dijkstra's algorithm with a heuristic that estimates the remaining distance, guiding the search toward the goal and exploring far fewer nodes in practice.
+A\* is a pathfinding and graph traversal algorithm that finds the shortest path between two nodes. It combines the guarantees of Dijkstra's algorithm with a heuristic that estimates the remaining distance, guiding the search toward the goal and exploring far fewer nodes in practice.
@@ -1,3 +1,3 @@
 # Cyclic Sort

-Cyclic sort is a sorting technique for arrays whose values fall in a known, contiguous range, typically `1` to `n`. Each element is swapped to the position matching its value, placing everything correctly in O(n) time and O(1) space — ideal as a building block for problems such as finding missing or duplicate numbers.
+Cyclic sort is a sorting technique for arrays whose values fall in a known, contiguous range, typically `1` to `n`. Each element is swapped to the position matching its value, placing everything correctly in O(n) time and O(1) space — ideal as a building block for problems such as finding missing or duplicate numbers.
@@ -1,3 +1,3 @@
 # Fast and Slow Pointers

-The fast and slow pointers pattern uses two pointers that traverse a data structure at different speeds. It is commonly used to detect cycles in linked lists, find the middle of a list, or locate the kth element from the end, running in O(n) time with constant space.
+The fast and slow pointers pattern uses two pointers that traverse a data structure at different speeds. It is commonly used to detect cycles in linked lists, find the middle of a list, or locate the kth element from the end, running in O(n) time with constant space.
@@ -2,10 +2,10 @@

 Insertion sort is a simple sorting algorithm that works by iteratively inserting each element of an unsorted list into its correct position in a sorted portion of the list. It is like sorting playing cards in your hands. You split the cards into two groups: the sorted cards and the unsorted cards. Then, you pick a card from the unsorted group and put it in the right place in the sorted group.

- Start with the second element as the first element is assumed to be sorted.
- Compare the second element with the first if the second is smaller then swap them.
- Move to the third element, compare it with the first two, and put it in its correct position
- Repeat until the entire array is sorted.
+*   Start with the second element as the first element is assumed to be sorted.
+*   Compare the second element with the first if the second is smaller then swap them.
+*   Move to the third element, compare it with the first two, and put it in its correct position
+*   Repeat until the entire array is sorted.

 Visit the following resources to learn more:

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 # Island traversal

-Island traversal is a grid-based technique used to find connected regions of cells that share a common value, typically `1`s in a binary matrix. It combines grid traversal with depth-first or breadth-first search — often with visited tracking — to count islands, measure their size, or analyze their shape.
+Island traversal is a grid-based technique used to find connected regions of cells that share a common value, typically `1`s in a binary matrix. It combines grid traversal with depth-first or breadth-first search — often with visited tracking — to count islands, measure their size, or analyze their shape.
@@ -1,3 +1,3 @@
 # Kth Element

-Kth element problems ask you to find the kth smallest (or largest) element in a collection without fully sorting it. Common solutions include heaps, quickselect, or sorting, depending on the constraints — a pattern that also appears in questions about arrays, streams, and binary search trees.
+Kth element problems ask you to find the kth smallest (or largest) element in a collection without fully sorting it. Common solutions include heaps, quickselect, or sorting, depending on the constraints — a pattern that also appears in questions about arrays, streams, and binary search trees.
@@ -1,3 +1,3 @@
 # Merge Intervals

-The merge intervals pattern deals with overlapping ranges, typically merging a list of intervals that intersect. The standard approach sorts the intervals by start time and then folds them together in a single pass — a technique used in scheduling, availability, and range problems.
+The merge intervals pattern deals with overlapping ranges, typically merging a list of intervals that intersect. The standard approach sorts the intervals by start time and then folds them together in a single pass — a technique used in scheduling, availability, and range problems.
@@ -1,3 +1,3 @@
 # Multi-threaded

-Multi-threaded algorithms divide work across multiple threads to run faster on multi-core machines. Common patterns include parallel divide-and-conquer, thread-safe queues for producer-consumer flows, and careful synchronization to avoid race conditions — with quality often measured by speedup and scalability.
+Multi-threaded algorithms divide work across multiple threads to run faster on multi-core machines. Common patterns include parallel divide-and-conquer, thread-safe queues for producer-consumer flows, and careful synchronization to avoid race conditions — with quality often measured by speedup and scalability.