Implementations of Algorithms Covered in MIT 6.006
by Dylan Cutler (DCtheTall)
Topics Covered
- 1D and 2D Peak Finding (lecture 1)
- Document Distance (lecture 2)
- Insertion Sort (lecture 2)
- Mergesort (lecture 3)
- Max Heaps (lecture 4)
- Heapsort (lecture 4)
- Binary Search Trees (lecture 5)
- AVL Trees (lecture 6)
- Counting Sort (lecture 7)
- Radix Sort (lecture 7)
- Hash Table with Chaining (lecture 8)
- Rolling Hashes (lecture 9)
- Karp-Rabin Text Search (lecture 9)
- Hash Table with Probing (lecture 10)
- Catalan Numbers (lecture 11)
- Karatsuba Multiplication (lecture 11)
- Breadth-First Search (lecture 13)
- Depth-First Search (lecture 14)
- Graph Cycle Detection (lecture 14)
- Topological Sort (lecture 14)
- Shortest Path Algorithm for a Directed Acyclic Graph (lecture 16)
- Dijkstra's Shortest Path Algorithm (lecture 16)
- Bellman-Ford Shortest Path Algorithm (lecture 17)
- Single Target Dijkstra's Algorithm (lecture 18)
- Bi-Directional Dijkstra's Algorithm (lecture 18)
- Goal Directed Dijkstra's Algorithm (lecture 18)
- Fibonacci Numbers (lecture 19)
- Memoization (lecture 19)
- Dynamic Programming (lecture 19, lecture 20, lecture 21)
Lecture 1
peakfinding.py
This program has implementations of algorithms for finding a peak in a 1-D or 2-D array of integers.
Lecture 2
docdist<i>.py
Each program in this file calculates the distance between two articles from Wikipedia. Each program incrementally improves the performance of the calculation.
Lecture 3
insertionsort.py
This program contains 2 implementations of insertion sort.
mergesort.py
This program contains 2 implementations of merge sort, the second being a recursive functional implementation.
Lecture 4
heapsort.py
This program contains an implementation applying the max heap invariant to Python lists. It also has an implementation of heapsort.
Lecture 5
bst.py
This program is an implementation of a binary search tree.
Lecture 6
avl.py
This program contains an implementation of an AVL tree, a self-balancing binary search tree.
Lecture 7
countingsort.py
This program contains an implementation of counting sort, a linear time sorting algorithm for integers.
radixsort.py
This program contains 2 implementations of radix sort, a linear time sorting algorithm for integers. One implementation is generalized for using any base integer for the buckets, the other is an optimized binary radix sort.
Lecture 8
hashtable.py
This program is an implementation of a hash table which uses chaining linked lists to handle collisions.
Lecture 9
karprabin.py
This program has an implementation of Karp-Rabin text search, which uses rolling hashes to efficiently find if a string is a substring of another.
Lecture 10
hashtable.py
This program is an implementation of a hash table which uses probing to handle collisions.
Lecture 11
catalan.py
This program contains a function which can find the terms in the Catalan number sequence.
karatsuba.py
This program contains an implementation of Karatsuba multiplication, a divide-and-conquer high precision multiplication algorithm.
Lecture 13
bfs.py
This program contains 2 implementations of breadth-first search.
Lecture 14
dfs.py
This program contains 2 implementations of depth-first search. One is a recursive implementation and another using a stack.
cycles.py
This program contains an implementation of an algorithm which uses depth-first search to detect if a graph contains any cycles.
topologicalsort.py
This program contains an implementation of topological sorts for directed, acyclic graphs (DAGs).
Lecture 16
topologicalsort.py
This program contains an implementation of an algorithm which uses topological sort to find the shortest path to each vertex from a given source vertex.
dijkstra.py
This program contains an implementation of Dijkstra's single source shortest path algorithm.
Lecture 17
bellmanford.py
This program contains an implementation of Bellman-Ford's shortest path algorithm. It will raise an exception if the graph has a negative weight cycle.
Lecture 18
singletarget.py
This program contains an implementation of a single-target Dijkstra's shortest path algorithm to find the shortest path between a source vertex and target vertex.
bidirectional.py
This program contains an implementation of a bi-directional single target Dijkstra's shortest path algorithm. It initiates two searches, one from the source vertex the other from the target vertex. It halts when each search finds a common vertex, and then finds the shortest bridge between the two vertices. The proof of correctness is covered in lecture.
goaldirected.py
This program contains an implementation of a goal-directed single-target Dijkstra's shortest path algorithm. It uses a heuristic to improve the speed of single-target Dijkstra's algorithm when it searches a large graph.
Lecture 19
fibonacci.py
This program contains 3 functions which compute the n^th Fibonacci number:
- A naive recursive algorithm.
- A dynamic programming algorithm which uses a memoization table.
- A bottom-up dynamic programming algorithm.
Lecture 20
blackjack.py
This program contains an algorithm for playing the best game of blackjack possible given that you know the order of the deck.
justify.py
This program contains an algorithm for justifying lines in a paragraph of text.
Lecture 21
distance.py
This program contains an implementation of computing the minimum edit distance between two strings.
knapsack.py
This program contains a solution to the knapsack problem: given a knapsack with a given capacity, what are the highest value items you can take given that the weight of the items cannot exceed the capacity.
matrices.py
This program contains an algorithm for finding the optimal matrix multiplication order for finding the product of multiple matrices.
Other algorithms
This repository also has implementations of the following algorithms not covered in lecture:
- A* search
- Iterated-Depth Depth-First Search (IDDFS)
- Red-Black tree