Exams in Data Structures I
You should know all theory presented at the lecture: definitions of data structures and operations on them, all theorems and proofs thereof.
The exam is oral with written preparation. You will get one major and one minor question from the following list.
- Define the Splay tree. State and prove the theorem on amortized complexity of the Splay operation.
- Define the (a,b)-tree. Describe operations Find, Insert, and Delete. Analyze their complexity in the worst case.
- Formulate a cache-oblivious algorithm for transposition of a square matrix. Analyze its time complexity and I/O complexity.
- Describe and analyze hashing with linear probing.
- Define multi-dimensional range trees. Analyze time and space complexity of construction and range queries.
- Define suffix arrays and LCP arrays. Describe and analyze algorithms for their construction.
- Describe a flexible array with growing and shrinking. Analyze its amortized complexity.
- Define BB[α]-trees with lazy balancing. Analyze their amortized complexity.
- Design operations Find, Insert, and Delete on a Splay tree. Analyze their amortized complexity.
- State and prove the theorem on amortized complexity on Insert and Delete on (a,2a-1)-trees and (a,2a)-trees.
- Analyze k-way Mergesort in the cache-aware model. Which is the optimum value of k?
- State and prove the Sleator-Tarjan theorem on competivity of LRU.
- Define c-unversal and k-independent systems of hash functions. State and prove the theorem on the expected chain length in hashing with chains.
- Describe a system of hash functions based on scalar products. Prove that it is a 1-universal system from Zpk to Zp.
- Describe a system of linear hash functions. Prove that it is a 2-independent system from Zp to [m].
- Construct a k-independent system of hash functions from Zp to [m].
- Construct a 2-independent system of hash functions for hashing of strings of length at most L over an alphabet [a] to a set of buckets [m].
- Describe and analyze the Bloom filter.
- Show how to perform 1-dimensional range queries on binary search trees.
- Define k-d trees and show that they require Ω(sqrt(n)) time per 2-d range query.
- Show how to use suffix array and LCP array for finding the longest common substring of two strings.
- Show how to parallelize an (a,b)-tree.
- Describe and analyze a lock-free implementation of a stack.