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This repository contains solutions for the Advent of Code (AOC) programming challenges from various years, mainly focusing on the 2022 edition. Advent of Code is an annual event where developers solve daily programming puzzles throughout December. The solutions in this repository are implemented in multiple programming languages such as Rust, JavaScript, Elixir, Python, Scala, Kotlin, and Zig.

The commit history shows the developer's progress as they work through the challenges, often mentioning struggles, improvements, and refactoring. The developer also occasionally goes back to previous years' challenges, such as AOC 2015 and AOC 2016, and solves them using different languages.

In summary, this repository is a collection of programming solutions for the Advent of Code challenges, showcasing the developer's skills and experience in various programming languages.

In the beginning, the developer focused on solving the Advent of Code (AOC) 2022 challenges, primarily using the Rust programming language. As they progressed through the daily puzzles, they made improvements to the codebase, such as better layout and reusability of input, adding comments for clarity, and optimizing the code by replacing certain functions with more efficient alternatives.

The developer occasionally experimented with other programming languages like Muzzle, Zig, and JavaScript for some of the challenges. However, they often faced difficulties or were not satisfied with the results, describing the solutions as "terrible" or "dreadful."

As the AOC 2022 event continued, the developer kept refining their solutions, addressing issues like off-by-one errors, simplifying match arms, and avoiding unwraps. They also tried to make the code more declarative and functional, using techniques like fold and filter_map. The developer occasionally switched between languages, implementing solutions in Elixir and JavaScript as well.

After completing the AOC 2022 challenges, the developer moved on to solving challenges from previous years, such as AOC 2015 and AOC 2016. They used a variety of programming languages like Python, Scala, Kotlin, and Zig to solve these challenges, showcasing their versatility and adaptability.

Throughout the process, the developer faced difficulties and struggled with some of the challenges, often resorting to brute force methods or writing "dirty" code to get the job done. However, they continuously made an effort to improve the codebase by refactoring, adding comments, and optimizing the solutions.