FUNDAMENTALS OF PROGRAMMING A
cod. 1000747

Academic year 2020/21
1° year of course - First semester
Professor
Federico BERGENTI
Academic discipline
Informatica (INF/01)
Field
Formazione informatica
Type of training activity
Basic
56 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ITALIAN

Learning objectives

The main aim of the course is to provide students with the fundamental techniques of imperative programming. The course also aims at providing students with the ability to apply analytical techniques to solve simple practical problems and to translate these solutions into executable programs. Finally, the course develops analytical and abstraction skills and it aims at improving the ability related to the decomposition of problems into sub-problems.

Taking Dublin Indicators into account:

Knowledge and understanding
During the course, the main ideas related to imperative programming are introduced. Particular emphasis is dedicated to the comprehension of algorithmic techniques on which imperative languages rely. Most of the suggested literature is in italian, even though proper english words are used during classes, in order to help students in reading also international scientific papers and books. During the course, students are encouraged to learn fundamentals of programming. Students also acquire adequate knowledge of computers architecture and information representation. Moreover, students are able to comprehend applications of mathematics to computer science.

Applying knowledge and understanding
Acquired theoretical knowledge is applied to solve specific problems, which are typically related to mathematics. During the course, some exercise sessions are dedicated to the solutions of problems. Many solving methods are applied to mathematical and numerical problems and they are presented from an algorithmic point of view. Students are able to use computational instruments as a support to mathematical processes and as a way to acquire new information.

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 and exercise sessions 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 on functions, set theory, and logics.

Course unit content

Computer architecture and information representation are introduced in the first part of the course. Then, the fundamental of imperative programming are presented. In particular, the concepts of variable, data type, algorithm, and expression are examined and functions and recursive functions are introduced.

Full programme

1) Information Representation
- Definition of alphabet, string, language and examples
- Definition of information
- Binary encoding and properties
- Representation of texts
- Representation of sounds
- Representation of images
- Representation of videos
- Redundant encoding
- Huffman encoding and applications
- Representation of integer and rational numbers and base conversion
- Representation of numbers in computers

2) Computers Architecture
- Problems and solutions
- Definition of process, program, algorithm
- Machine hierarchy (hints)
- Computer architecture (CPU, memories)

3) Programming
- Variables and data types
- Assignment and expressions
- Functions and recursive functions
- Selection statements
- Iterative statements
- Flux diagram and pseudocode
- Arrays
- Structs
- File manipulation
- Computational cost of algorithms (hints)
- Pointers (hints)

Bibliography

- D. Mandrioli, S. Ceri, L. Sbattella, P. Cremonesi, G. Cugola. Informatica arte e mestiere, McGraw-Hill, 2014.

Additional material:

- Exercises on elly.smfi.unipr.it
- L.J. Aguilar. Fondamenti di programmazione in C++ , McGraw-Hill, 2008.
- R. Miller, D. Clark, B. White, e W. Knottenbel: An Introduction to the
Imperative Part of C++, 1999, disponibile su WEB all'indirizzo http:
//www.doc.ic.ac.uk/~wjk/C++Intro/CourseStructure.html#S
- Notes at http://people.math.
unipr.it/gianfranco.rossi/Teaching/FondProgr/index.html

Teaching methods

The majority of the course consists in frontal lessons.

Assessment methods and criteria

The final exam consists in a written test and a programming test. The final grade depends on both tests.

Other information

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2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.scienze@unipr.it
T. +39 0521 905116

Quality assurance office

Education manager
dott.ssa Giulia Bonamartini

T. +39 0521 906968
E. servizio smfi.didattica@unipr.it
E. del manager giulia.bonamartini@unipr.it

President of the degree course

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Faculty advisor

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Career guidance delegate

Prof. Francesco Morandin
E. francesco.morandin@unipr.it

Tutor Professors

Prof. Emilio Acerbi
E. emilio.acerbi@unipr.it

Prof. Marino Belloni
E. marino.belloni@unipr.it

Prof.ssa Maria Groppi
E. maria.groppi@unipr.it

Prof.ssa Chiara Guardasoni
E. chiara.guardasoni@unipr.it

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Prof. Costantino Medori
E. costantino.medori@unipr.it

Prof. Adriano Tomassini
E. adriano.tomassini@unipr.it

Erasmus delegates

Prof.ssa Fiorenza Morini
E. fiorenza.morini@unipr.it

Quality assurance manager

Prof.ssa Maria Groppi
E. maria.groppi@unipr.it

Tutor students

Dott. Matteo Mezzadri
E. matteo.mezzadri@studenti.unipr.it