chore: sync content to repo (#10394)
Co-authored-by: nilbuild <4921183+nilbuild@users.noreply.github.com>
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# Adjacency List
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An adjacency list represents a graph by storing, for each vertex, a list of the vertices it connects to. This representation uses memory proportional to the number of edges, which makes it efficient for sparse graphs where most vertices are not directly connected to each other.
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Visit the following resources to learn more:
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# Bubble Sort
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Bubble sort repeatedly steps through a list, comparing adjacent elements and swapping them if they are in the wrong order, until no swaps are needed. Each pass moves the largest unsorted element into its correct position, like a bubble rising to the top. It runs in O(n²) time in the average and worst case, which makes it inefficient for large datasets but simple to understand and implement.
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Visit the following resources to learn more:
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@@ -4,7 +4,7 @@ C is a general-purpose computer programming language. It was created in the 1970
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Visit the following resources to learn more:
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- [@roadmap@Visit Dedicated C+ Roadmap](https://roadmap.sh/c)
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- [@roadmap@Visit Dedicated C Roadmap](https://roadmap.sh/c)
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- [@book@Beej's Guide to C Programming](https://beej.us/guide/bgc/)
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- [@article@Learn C - Tutorials Point](https://www.tutorialspoint.com/cprogramming/index.htm)
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- [@video@C Programming Tutorial for Beginners](https://www.youtube.com/watch?v=KJgsSFOSQv0)
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# Common Algorithms
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Common algorithms are well-established, reusable procedures for solving recurring problems like sorting a list, searching for a value, or finding a path through a graph. Studying them builds intuition for algorithm design and gives a shared vocabulary for discussing performance trade-offs, since most real-world problems can be broken down into variations of these known patterns.
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Visit the following resources to learn more:
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# Exponential
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Exponential time, written O(2^n), means the work doubles with each additional unit of input size. Algorithms with exponential time complexity become impractical quickly as input grows, and they often show up in brute-force solutions to problems without known efficient algorithms.
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Visit the following resources to learn more:
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- [@course@Heap Sort Algorithm](https://www.coursera.org/lecture/data-structures/heap-sort-hSzMO)
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- [@article@Heap Sort Algorithm](https://www.programiz.com/dsa/heap-sort)
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- [@video@Heap Sort in 4 Minutes](https://www.youtube.com/watch?v=2DmK_H7IdTo)
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- [@video@Heap Sort Algorithm - MIT](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291s)
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- [@video@Lecture 4 - Heaps and Heap Sort](https://www.youtube.com/watch?v=B7hVxCmfPtM&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=5)
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- [@video@Heap Sort Algorithm - MIT](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291s)
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@@ -4,5 +4,6 @@ Merge sort is a divide and conquer algorithm. It divides the input array into tw
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Visit the following resources to learn more:
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- [@article@Merge Sort in Python: Step-by-Step Guide + Code](https://roadmap.sh/python/merge-sort)
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- [@article@Merge Sort Algorithm](https://www.programiz.com/dsa/merge-sort)
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- [@video@Merge Sort in 3 Minutes](https://www.youtube.com/watch?v=4VqmGXwpLqc)
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# Non-Tail Recursion
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Non-tail recursion is a form of recursion where work remains to be done after the recursive call returns, such as combining the result with something else. Each call must keep its stack frame until the recursive call underneath it finishes, which means the call stack grows with each level of recursion and cannot be optimized away like tail recursion.
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Visit the following resources to learn more:
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# Red / Black Trees
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A red-black tree is a self-balancing binary search tree where each node is colored red or black, and a set of coloring rules ensures the tree never becomes more than roughly twice as tall as the shortest possible balanced tree. It requires fewer rotations on average than an AVL tree, which makes it a common choice for implementing ordered maps and sets in standard libraries.
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Visit the following resources to learn more:
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@@ -5,6 +5,6 @@ SQL databases store data in structured tables with fixed schemas and use SQL to
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Visit the following resources to learn more:
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- [@video@SQL vs. NoSQL: What's the difference?](https://www.youtube.com/watch?v=Q5aTUc7c4jg)
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- [@feed@Types of NoSQL Databases: How to Choose the Right One](https://roadmap.sh/backend/types-of-nosql-databases)
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- [@video@Database Design Tips | Choosing the Best Database in a System Design Interview](https://www.youtube.com/watch?v=cODCpXtPHbQ&t=22s)
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- [@video@NoSQL vs SQL – Which Type of Database Should You Use?](https://www.youtube.com/watch?v=FzlpwoeSrE0)
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- [@video@NoSQL vs SQL – Which Type of Database Should You Use?](https://www.youtube.com/watch?v=FzlpwoeSrE0)
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- [@feed@Types of NoSQL Databases: How to Choose the Right One](https://roadmap.sh/backend/types-of-nosql-databases)
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