A learning repository with implementations and datasets for multiplication, merge sort, quicksort, Karatsuba multiplication, and Karger's randomised minimum-cut algorithm.
Project status: coursework archive; programs are independent exercises with mixed languages and limited automated tests.
- C++ Karatsuba multiplication example.
- Python merge-sort and quicksort exercises.
- Python implementation of Karger's minimum-cut algorithm.
- Text datasets used by the exercises.
- Editor task configuration and a tracked Windows executable.
python mergeshort.py
python quickshort.py
python kargerMinCut.py
g++ -std=c++17 -Wall -Wextra -pedantic karatsuba.cpp -o karatsuba- Karger's algorithm is randomised; record the seed and number of trials for reproducible comparisons.
- State input format, index conventions, and expected outputs next to each dataset.
- Do not trust the tracked karatsuba.exe; rebuild executables from source.
- A maintainable revision should add unit tests, type hints, deterministic fixtures, and asymptotic-complexity notes.
| Path | Purpose |
|---|---|
| karatsuba.cpp | Divide-and-conquer multiplication. |
| mergeshort.py | Merge-sort exercise. |
| quickshort.py | Quicksort and comparison counting. |
| kargerMinCut.py | Randomised graph minimum cut. |
| *.txt | Exercise inputs. |
The repository is for learning and benchmarking. Treat downloaded datasets and prebuilt executables as untrusted until inspected; prefer rebuilding from source.
Open an issue before a large change. Keep changes focused, document assumptions, and include a reproducible verification step.
A repository-wide open-source license has not been declared. Obtain permission before redistributing material.