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Laurea in Matematica Applicata

Computer programming with laboratory (2010/2011)

Course code 4S02751  
Credits 12  
Coordinator Ugo Solitro
Disciplinary sector INF/01 - Computing
Teaching language Italian
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Teaching is organised as follows:

Activity Credits Period Academic staff
Teoria 8 II semestre Ugo Solitro
Laboratorio 4 II semestre Ugo Solitro

Lecture timetable

II semestre
Activity day Time Type Place Note
Teoria Tuesday 1:30 PM - 4:30 PM lesson Lecture theatre E  
Teoria Wednesday 3:30 PM - 5:30 PM lesson Lecture theatre E  
Teoria Friday 1:30 PM - 3:30 PM laboratorio Didactic workshop Delta  
Laboratorio Monday 10:30 AM - 1:30 PM laboratorio Didactic workshop Delta  

Educational objectives

Introduction to informatics.
Study the programming principles and their application to the solution of problems, mathematical ones in particular, by means of a particular programming language.
The fundamentals of programming.
The techniques for the analysis and solution of the problems; more we introduce the methods for the evaluation of correctness and efficiency of the algorithms.
In the laboratory we learn how to develop project of small or medium size in a specific programming language.

Syllabus

- Introduction

Basics of Computer Science.

Part I - problems, algorithms and programs.

- Fundamentals: problem, specifics, algorithm; abstract machine, compiler and interpreter; programming languages.
- Introduction to the programming language.
- Elementary programming: basic instructions and development of simple programs.
- Data types. The general concept of data type: characterization and data representation. Variables, expressions and assignment. Abstract Data Types.
- Primitive data types: characterization, usage and related problems.
- Program structure. Fundamental instructions.
- Sub-programs: structure, parameters and visibility.
- Structured data types. Arrays, pointers, strings and other data structures.
- Basics of objects.
- Dynamic data structures.
- Introduction to graphs and other subjects.

Part II - Analysis of Algorithms

- Correctness: termination, logic properties; methods for the correctness verification.
- Introduction to the complexity. Performance of algorithms. Evaluation of efficiency. Computational costs.
- Asymptotic estimation of the complexity in time and space. The worst and medium case.
- Amortized analysis.
- Static sequences: implementation and algorithms.
- Matrices: implementation, operations and algorithms.
- Dynamic sequences: abstract definition and implementation; basic operations.
- Trees. Abstract definition and implementation. Basic operation. Binary research trees.
- Introduction to graphs.

Basics of Object Oriented Programming

--------------------
Laboratory.

In the laboratory we familiarize with the programming language developing projects based on the ideas presented in the lessons.
We study the fundamental elements of the language and we deal with the problems that arise in the development of the solution; in particular we acquire skill in editing, compiling, debugging and basic project management.

Exam methods

The final exam is unique and consists in two parts:
- a written exam concerning the topics of the course and the laboratory projects.
- an oral part (the admission to this part is allowed only after passing the first one): discussion on the examination paper, the lab activity and in general on the topics of the course.
The final written exam can be replaced by verification the tests that take place during the course.

Reference books
Activity Author Title Publisher Year ISBN Note
Teoria Bertossi, Alan e Montresor, Alberto Algoritmi e strutture di dati Città Studi Edizioni, De Agostini Scuola 2010 9788825173567
Laboratorio Bertacca M. e Guidi A. Programmare in Java McGraw-Hill 2007 978-88-386-6400-7

Statistics on students' past performance (Art. 2 del D.M. 31/10/2007, n. 544)

Statistics
Outcomes Exams Outcomes Percentages Average Standard Deviation
Passed 61.90% 24 2
Failed 9.52%
Absent 17.46%
Withdrawn 11.11%
Canceled --


Distribuzione degli esiti positivi
18 19 20 21 22 23 24 25 26 27 28 29 30 30 e Lode
2.5% 0.0% 2.5% 12.8% 10.2% 12.8% 10.2% 20.5% 10.2% 5.1% 5.1% 2.5% 2.5% 2.5%

Data from AA 2010/2011 based on 63 students. I valori in percentuale sono arrotondati al numero intero più vicino.