ALGORITHMS AND DATA STRUCTURES
cod. 07563

Academic year 2024/25
1° year of course - Second semester
Professor
Andrea MUNARO
Academic discipline
Informatica (INF/01)
Field
Discipline informatiche
Type of training activity
Characterising
72 hours
of face-to-face activities
9 credits
hub:
course unit
in ITALIAN

Learning objectives

The main objective of the course is to introduce the most common data structures and related algorithms. The course also aims at providing students with the ability to study the computational complexity of algorithms. Finally, the course develops analytical and abstraction skills and aims at improving the ability to provide algorithmic solutions to practical problems.

With reference to Dublin indicators:

Knowledge and understanding
During the course, the main ideas related to algorithms and data structures are introduced. Students are encouraged to learn the study of computational complexity of algorithms and to learn proper use of different data structures.

Applying knowledge and understanding
Acquired theoretical knowledge is applied to solve specific problems. During the course, some exercise sessions are dedicated to the solutions of problems.

Making judgments
Exercises proposed during classes can be solved individually or in groups and they often can be solved in different ways. Students can compare their approach to the solutions proposed by other students and to the solutions shown during classes. Such comparisons enhance the development of specific skills which are useful to better understand the considered problems.

Communication skills
Discussions during classes allow students to improve their communications skills. Such discussions concern specific algorithmic techniques to solve the proposed problems and they focus on advantages and disadvantages of the proposed approaches. Students learn to work individually and in groups.

Learning skills
The study of algorithmic techniques and their application to heterogeneous problems help students to improve in-depth comprehension of the topics. Acquired knowledge can be adapted to solve problems which may be different from those specifically seen during classes. Students acquire computational techniques useful to work in groups and autonomously.

Prerequisites

Basic notions of mathematical analysis and programming.

Course unit content

The course introduces basic notions related to algorithms and data structures. In particular, the study of the computational complexity of algorithms is investigated and correct algorithms for different data structures are studied.

Full programme

Computational complexity and correctness of algorithms.

Algorithm design and Divide and Conquer.

Algorithms for arrays (e.g., search and sorting).

Algorithms for lists (e.g., search and modifications).

Algorithms for trees (e.g., search, traversal and priority queues).

Algorithms for hash tables (e.g., insertion and deletion).

Algorithms for order statistics and for disjoint sets.

Algorithms for graphs (e.g., graph traversal, strongly connected components, single-source shortest paths, minimum spanning trees).

Basics of further algorithm design techniques (dynamic programming, greedy).

Bibliography

T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein. Introduzione agli algoritmi e strutture dati, McGraw Hill, 2010.

C. Demetrescu, I. Finocchi, G. F. Italiano. Algoritmi e strutture dati, McGraw Hill, 2008.

J. Kleinberg, E. Tardos. Algorithm design, Pearson, 2006.

Teaching methods

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Assessment methods and criteria

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Other information

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2030 agenda goals for sustainable development

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