Algorithms and Data Structures - Spring 2019


Feb 25: The lecture of Tuesday February 26 will be held in the Auditorium.

Feb 25: Homework problem n. 1 (non-graded): solve the vertical histogram Python programming exercise. This assignment will be discussed in class on Tuesday March 5.

All announcements are recorded here.

Instructor: Antonio Carzaniga
Assistants: Afrouz Jabalameli, Ioannis Mantas, Martin Suderland
Type of course: lecture
Lecture Hours: Tuesday 10:30–12:30 in SI-008, Thursday 10:30–12:30 in SI-008
Instructors' Office Hours: by appointment
Assistants' Office Hours: by appointment


Algorithms and data structures are fundamental to computer science, as they are the essence of computer programs. Also, the performance of any software system depends on the efficiency of its algorithms and data structures. Designing and analyzing algorithms is therefore crucial for the development of software systems. More generally, the study of algorithms provides insight into the nature of problems and their possible solutions, independent of programming language, programming paradigm, computer hardware, or any other implementation aspect. The objective of this course is to provide students with the knowledge and skills necessary to design and reason about algorithms, and to understand some of the most fundamental algorithms and data structures, their strengths and weaknesses, and their suitability in common contexts.


The course will cover basic notions of complexity, including asymptotic analysis of worst-case and average complexity, big-O, little-o, omega, and theta notation, polynomial reductions, poly-time verification vs. solution, NP and P complexity classes; general algorithm strategies such as brute force, greedy, divide-and-conquer, and dynamic programming; common algorithms, including elementary numeric computations, searching and sorting, elementary graph algorithms, and string matching; basic data structures, including stacks, queues, linked lists, and rooted trees; more advanced data structures, including B-trees, heaps, hash tables, and structures representing disjoint sets and dictionaries.



Additional information is available through the following links and pages.

this page is maintained by Antonio Carzaniga and was updated on February 09, 2018