Algorithms and Data Structures 2

• classify advanced data structures and algorithms design patterns.
• describe the properties of advanced data structures and algorithms.
• analyse algorithms with respect to the use of resources.
• prove the correctness of algorithms.
• recover the underlying abstract structure of a real problem.
• adapt generic algorithms to new problem settings.
• design efficient data structures and algorithms.
• implement advanced algorithms.
• describe an algorithm in a comprehensible way.

Basic graph algorithms (shortest paths, flows). Data structures for indexing, predecessor and subset sum (e.g. search trees, Fenwick trees). Algorithms for string matching. Techniques for the design and analysis of algorithms (dynamic programming, divide-and-conquer, amortised analysis). Randomized algorithms. NP.

02105/02326, The course builds on 02105 Algorithms and Data Structures I.

Lectures and exercises.