Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
B
ING-INF/05
12
B
INF/01
12
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05

2° Year   activated in the A.Y. 2011/2012

ModulesCreditsTAFSSD
6
B
ING-INF/05
Tre insegnamenti a scelta tra i seguenti
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
SECS-P/10
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
FIS/01
6
B
INF/01
Altre attivita' formative
4
F
-
24
E
-
ModulesCreditsTAFSSD
12
B
ING-INF/05
12
B
INF/01
12
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
activated in the A.Y. 2011/2012
ModulesCreditsTAFSSD
6
B
ING-INF/05
Tre insegnamenti a scelta tra i seguenti
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
SECS-P/10
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
FIS/01
6
B
INF/01
Altre attivita' formative
4
F
-
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
8
D
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Algorithms - ALGORITMI  (2010/2011)

Teaching code

4S02709

Teacher

Margherita Zorzi

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

II semestre dal Mar 1, 2011 al Jun 15, 2011.

Seminars 0

To show the organization of the course that includes this module, follow this link:  Course organization

Learning outcomes

The goal of this course is to introduce some advanced paradigms for algorithms development and analysis in order to determine good approximate solutions for hard optimization problems.

Program

Main concepts recall about computational problems: definition, instances, encoding, precise and approximate models. Optimization computational problem.
Main concepts recall about algorithms: computational resources, input encoding, input size/cost, computational time. Worst and average analysis. Computational time and growth order.
Computational time vs. hardware improvements: main relations. Efficient algorithms and tractable problems.

Divide et impera paradigm
-------------------------
Definition and application to some problems.

Greedy paradigm
---------------
Definition and application to some problems. Matroids and greedy algorithms.
Huffman Codes

Backtracking technique
----------------------
Definition and application to some problems (main examples: Graham Scan and Knuth-Morris-Pratt algorithm).

Branch & Bound technique
------------------------
Definition and application to some problems.

Dynamic programming paradigm
----------------------------
Definition and application to some problems.
Memoization and Dynamic programming.


Probabilistic algorithms
------------------------
Definition and few application examples.
Numerical probabilistic algorithms, Monte Carlo algorithms and Las Vegas algorithms. Examples: Buffon's needle, Pattern Matching and Universal hashing.


Local search tecnique
---------------------
Definition and application to some problems.

Approximations algorithms
-------------------------
Definition and some examples.
Simulated annealing.
Tabù search.

Examination Methods

Written test/ open questions

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Teaching materials e documents