I often like to circle back around to things I've previously explored. It's often beneficial to see things from a fresh perspective, especially when it comes to thinking algorithmically. The N queens problem is often used to introduce computer science
The knights tour is a classic chess puzzle, which involves finding a path on a chess board where starting from some place on the board, the knight occupies every space once without using the same space twice. Like the N queens problem, finding a knight
Few if any names hold as much weight in computer science as Donald Knuth. So when knuth proposes a solution to a problem, you'd be wise to listen. Amongst his (many) famous contributions is the awesomely named "Algorithm X". To quote wikipedia, Algorit
A fundamental concept for software engineers when it comes to writing maintainable software is the DRY principle: Don't repeat yourself. Many times when writing code we may find ourselves implementing algorithms that are very similar in structure to ea
The set ADT is an important and unique (see what I did there?) data structure with many uses, and many ways to implement them. Often implemented over a linked structure, sets are not quite a list and not quite a dictionary, but often have similar funct
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Swiz Heaps: A deterministic modification of Randomized Meldable Heaps
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Let's talk Eval/Apply
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BST Deletion: Removal By Merge
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Dictionary Based Compression: The LZW Algorithm
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Taking Action: Compiling Procedures to P-Code
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Making Decisions: Compiling If Statements to P-Code
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Repeating yourself: Compiling While Loops to P-Code
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Removing an entry from a B+ Tree without Rebalancing: A viable approach?
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Implementing An Iterator for In-Memory B-Trees
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Weight Balanced Binary Search Trees