Data structure assigenments with our solutions.
- The goals of this course are to learn a variety of useful data structures and to use them properly when designing efficient algorithms. During this process we will define (asymptotic) runtime and space efficiency of algorithms and their data structures. We will learn how to design algorithms and data structures to efficiently solve problems.
- Growth of Functions & Algorithm Analysis
- Recurrences
- Basic ADT’s: Arrays, Linked Lists, Stacks & Queues
- Binary Search Trees
- AVL-Trees
- B-Trees
- Probability basics
- Skip Lists
- Hash tables
- Heaps, Heap sort & Priority Queues
- Huffman codes/Lempel-Ziv
- Median (Deterministic and Randomized algorithms).
- Quicksort
- Sorting in Linear Time
- Elementary Graph Algorithms: BFS, DFS, Topological Sort, Pert, Dijkstra (no formal proofs)
- Amortized Analysis (include BB-α-tree)
- Data Structures for Disjoint Sets (Union Find)
- MST – Kruskal, Prim
- Bloom filter