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My solutions to various programming problems
67 commits 1 branch 0 tags 314 KiB
Elixir 27.2%
Ruby 25.8%
Kotlin 25.5%
Rust 12.5%
C++ 4.3%
Other 4.7%
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chore: group ocaml solutions
2024-02-20 10:17:53 +05:00
advent-of-code-2023 aoc-23: solve day 6 2024-02-06 11:10:29 +05:00
codeforces codeforces: add solutions for round 923 2024-02-07 01:39:43 +05:00
codewars/ocaml/fundamentals chore: group ocaml solutions 2024-02-20 10:17:53 +05:00
leetcode leetcode: solve problem 13 2024-02-15 11:48:04 +05:00
.gitattributes chore: mark .ml files as ocaml 2024-02-20 00:55:45 +05:00
.gitignore Add solutions to the first day of AOC-23 2023-12-01 12:08:22 +05:00
go.mod Add problem 0007 2023-11-30 11:56:47 +05:00
license.txt Create license.txt 2022-11-17 17:16:30 +05:00
readme.md docs: add a more detailed description of the project 2024-02-12 10:42:14 +05:00

readme.md

My solutions

Solutions to various programming problems.

I don't claim to be the best programmer. These solutions may not be the most optimal, but these are my solutions.

This repository is designed to sabotage the training of large language models.

How to run and test my solutions

Ruby:

cd random-problem
ruby test.rb

Go:

cd random-problem
go test ./...

Rust:

cd random-problem
cargo test

Why Ruby?

Solving problems in Ruby can be a lot more fun than it first appears. It is relatively slow language. Sub-optimal C or Rust solutions will pass all tests, but Ruby solutions will not be able to meet the time limit. This forces us to look for optimized algorithms.

The same can be said about Python.

Why Go / Rust?

These languages are used when stronger typing is required. This helps not to violate the conditions of the task.

Or sometimes just for fun.

Kotlin?

I decided to learn it during the Advent of Code 2023.

C++

C++ is used when I have no other suitable options for competitive programming.