Computer Science

Educational objectives

GENERAL OBJECTIVES:
to obtain a general knowledge of the basic techniques of Differential Calculus and of the standard applications to problems of maxima-minima of functions of a real variable and to the study of their graph.

SPECIFIC OBJECTIVES:

Knowledge and understanding:
at the end of the course, students will master the basic notions of Differential Calculus, in particular the notions of function, limit and derivative.

Applying knowledge and understanding:
students will be able to solve typical problems from Differential Calculus, such as the explicit calculation of derivatives, of maxima and minima of a function, and to plot an approximate graph of functions of a real variable.

Critical and judgment skills:
students will be able to use a graph as a tool to analyse concrete phenomena which admit a mathematical description.

Communication skills:
students will be able to fully understand a scientific text of moderate complexity and relate on the essential ideas contained in it.

Learning skills:
the notions and techniques learned will give students access to more advanced notions, either in a further course or in the form of self-study, concerning further aspects of Differential and Integral Calculus.
dge of the basic techniques of Differential Calculus and of the standard applications to problems of maxima-minima of functions of a real variable and to the study of their graph.

Educational objectives

General objectives:
Introduction to programming through the Python language.

Specific objectives:
Introduction to programming through the Python language.
Data types, variables, assignments, control structures, functions, classes, modules and Input/Output.
Data structures: arrays, strings, lists, tuples and dictionaries.
Design and development of programs through procedural programming and object-oriented programming.
Recursive and iterative algorithms.
Python libraries for graphics, file handling, text/html processing and internet access.
Program debugging and testing.

Knowledge and understanding:
Understand and define a problem's requirements.
Choose how to represent the input and what data structures to use for intermediate computations and output.
Define the algorithm solving the problem.
Code the algorithm as a Python program.
Modularize the program as small separate functions/methods.
Test that the program satisfies the requirements.

Apply knowledge and understanding:
The student will work at home on a series of programming tasks, through the whole course, to practice and to show what has been learned.
At the end of the course, the exam will be based on a lab test where she should solve and program various programming exercises.

Critical and judgmental skills:
The student, at the end of the course, should be able to autonomously choose how to solve a programming task (analysis, implementation and test).

Communication skills:
It is very important that the student has good text comprehension abilities for the problem analysis and requirement definition phase.

Learning ability:
The ability to analyse a problem to define its requirements and design both the necessary data structures and the correct algorithm will be applicable to other programming languages and will be very useful for the following programming courses.

Educational objectives

General goals:
The course is aimed at acquiring the basic logical and set-up knowledge to tackle the study of other topics in mathematics and computer science.

Specific goals:

Knowledge and understanding:
At the end of the course student will have full understanding of the proposed logical-set-theoretical tools.

Apply knowledge and understanding:
Students will have acquired the ability to carry out a rigorous, even if elementary, mathematical reasoning, in particular with regard to the fundamental logical principles and the use of induction in all its forms.

Critical and judgmental skills:
Students will therefore be able to critically address the arguments proposed in other theoretical and applied teachings. In this regard, many examples are given from other lessons.

Communication skills:
Active participation in the classroom and the use of the oral exam serve to stimulate students in acquiring the proper language of mathematics and to transmit the knowledge and skills acquired appropriately .

Ability to continue the study:
Students will be able to deepen in the personal study the topics treated using what they have learned as a basis.

Educational objectives

General goals:
How to design combinational and sequential circuits.

Specific goals:
binary encoding of different data types, boolean algebra, analysis and synthesis of combinational circuits, flip-flop, analysis and synthesis of sequential circuits, registers, , interconnection between register and functional units.

Knowledge and understanding:
Knowing and understanding the handling and processing of information on a computer-

Applying knowledge and understanding:
Show the ability of designing simple combinational and sequential circuits that perform specific tasks.

Critiquing and judgmental skills:
Being able to choose the best approach, among those considered, for solving a specific task.

Communication skills:
Being able to evaluate and motivate the choices taken in the design of a circuit.

Learning skills:
Understanding the differences and advantages of the different design techniques

Educational objectives

Obiettivi generali:
L’obiettivo dell'insegnamento di Architettura degli elaboratori è di far comprendere i principi che sono usati per progettare i calcolatori moderni. In particolare, il corso tratta la struttura interna del microprocessore e le idee che hanno permesso la straordinaria evoluzione della potenza di calcolo negli ultimi 30 anni. come pipelining, caching, branch prediction, e multi-processing.

Obiettivi specifici:
Il corso tratta i principi di base di organizzazione del microprocessore e le nozioni di pipelining, caching, branch prediction, virtualizzazione e multi-processing. Inoltre, il corso tratta la programmazione assembly.

Conoscenza e comprensione:
Lo studente acquisirà conoscenza sull’organizzazione del microprocessore MIPS, come implementazione delle idee generali che fanno parte degli obbiettivi del corso. Inoltre, lo studente acquisirà conoscenza su come si strutturano i programmi in assembly, incluse le strutture dati, i paradigmi standard di programmazione e la ricorsione.

Applicazione di conoscenza e comprensione:
Le conoscenze sono applicate sulla architettura MIPS, comprese in modo tale da poter capire le implicazioni delle scelte di programmazione sulla performance dei programmi su hardware specifico. Questa risultato è ottenuto tramite esercizi di programmazione e di valutazione delle prestazioni.

Autonomia di giudizio:
Lo studente sarà in grado di comprendere le problematiche relative alle prestazioni del software su hardware specifico e di valutarne autonomamente le caratteristiche.

Abilità comunicative:
Il corso non si propone espliciti obiettivi sulle capacità comunicative, eccetto di formare all'esposizione rigorosa degli argomenti tecnici.

Capacità di apprendimento successivo:
Il corso pone le basi per la comprensione dei moduli dell'insegnamento di Sistemi operativi e di tutti i corsi di programmazione, inclusa la programmazione di sistemi paralleli.

Educational objectives

General goals:
The purpose of the course is to provide the student with basic mathematical analysis tools such as : the theory of series, integral calculusand differential equations.

Specific goals:
Students will be able to examine various techniques of integration and apply them to compute definite and indefinite integrals by using integration by substitution and the rule of integration by parts.Students will be able tocompute limits of sequences and discuss the convergence of number series, power seriesand Taylor series of elementary functions.

Knowledge and understanding:
At the end of this course the students will be able to calculate integrals and the solutions of some first order differential equationsand the solutions of second order linear differential equations with constant coefficientsLearning activities consists of lectures and exercise sessions. The lecture aim to introduce fundamental concepts, to explain them by showing examples.

Applying knowledge and understanding:
The exercise sessions aim to teach how to select and use calculation methods.

Educational objectives

This course will introduce students to very basic algorithm design and analysis. They will learn various established algorithms for solving fundamental problems, such as sorting or searching, together with the simplest tools to analyze them.

Knowledge and understanding
At the end of the course students will be familiar with the basic methodologies for the design and analysis of iterative and recursive algorithms, elementary data structures, major sorting algorithms and the most basic implementations of the dictionaries.

Apply knowledge and understanding:
At the end of the course students will have become familiar with the main basic data structures, in particular those implementing dictionaries. They will be able to explain the algorithms and analyse their time complexity, highlighting how their performances depend on the used data structure. They will be able to design new data structures and related algorithms on the basis of the existing ones; they will be able to explain the main sorting algorithms, illustrating the underlying design strategies and their time complexity analysis; they will be able to compare the asymptotic behaviour of the execution times of the studied algorithms, to design recursive solutions to problems and to analyse their asymptotic time complexity.

Critical and judgmental skills
Students will be able to analyze the quality of an algorithm and related data structures, both from the effective resolution of the problem and from the time complexity point of view.

Communication skills
Students will acquire the ability to expose their knowledge in a clear and organized way, which will be verified both through the written tests and during the oral examination.
Students will be able to express an algorithmic idea rigorously at high level, in pseudocode.

Learning ability
The acquired knowledge will allow students to face the study of other algorithmic design metodologies and of more advanced data structures within a master's degree course.

Educational objectives

General goals:
Learning object-oriented programming concepts through the Java programming language.

Obiettivi specifici:
Fundamentals of object oriented programming: classes and objects, encapsulation, inheritance, polymorphism, static and dynamic binding, design patterns. Functional programming. Tools and methodologies for software design through an object-oriented programming language. Java language.

Knowledge and understanding:
Knowledge of OOP constructs, with special reference to Java. Understanding a Java program. Ability to write a small- or medium-size Java programs.

Apply knowledge and understanding:
Ability to apply basic methodologies to face software system design of small and medium size. Ability to use the main development tools to implement such systems in Java.

Critical and judgmental abilities:
Ability to identify correct/effective and incorrect/ineffective instructions, constructs or patterns in Java.

Communication skills:
Ability to illustrate projects.

Learning ability:
Ability to learn and apply new programming techniques starting from those learned during the course.

Educational objectives

General goals:
The student will be able to understand the main cores of texts on technical topics, both theoretical and concrete, such as the study of computer parts and their use. In particular, the student will develop the skill of specialized translation of a technical text from English into Italian and/or vice-versa through the knowledge of the scientific lexicon and the practice of linguistic functions semantically consistent with the field of computer science. The lessons will also develop through dialogic practice and peer comparison in the form of work groups and discussions in order to allow the student to develop a personal linguistic fluency.

Specific goals:
Grammar focus developped through the practical use and relative understanding of specialized texts relating to the following topics:
A concise history of computer;
Computer components: hardware and software;
An introduction to operating Systems and computer programming language;
Where and how are computers used;
Computer networks and the internet.

Knowledge and understanding
The student will demonstrate a knowledge of the English language equal to level B2 of the Common European Framework of Reference. To this aim, he/she will be exposed to passages in authentic language, both written and oral through audio aids, to the practice of reading and translating.

Applying knowledge and understanding

The student will be able to understand the main cores of texts on technical topics relating to information technology and the world of computers. In particular, he/she will develop a double reading ability, in relation to the type of text, and the information requested: skimming, rapid scrolling for a global understanding; scanning, for the identification of specific information in the text. He/she will also develop the specific translation skills of a technical text, from English into Italian.
The student will develop this ability through the knowledge of the scientific lexicon and the practice of linguistic functions that are semantically consistent with the field of computer science.

Critical and judgmental skills:
The student will have to demonstrate that he has acquired autonomy in sectorial critical judgment, the ability to express opinions and to motivate choices. This ability will be acquired through dialogic practice and peer comparison in the form of work groups and discussions.

Communication skills:
The student will be able to communicate in a fluid way in English and to produce clear and correct texts, using a vocabulary appropriate to the IT sector. He/she will also demonstrate to have acquired a correct pronunciation. To this aim, specialized texts will be read in the classroom by the teacher and/or there will be listening via audio support.

Learning ability:
The students will have to show that they have developped oral and written learning skills in a constantly evolving sector, and therefore to update their skills also in reference to new application scenarios.

Educational objectives

At the end of the class, students will have a basic knowledge of:
- group theory,
- algebraic structure of some simple types of groups,
- resolution of systems of linear equations,
- diagonalisation of linear operators on finite dimensional vector spaces.

At the end of the class, students will be able to:
- make calculations inside a group,
- solve systems of linear equations,
- find eigenvalues and eigenvectors of linear operators.

Educational objectives

General goals:
To be able to design/evaluate the properties, storage structure and protocols of a database management system.

Specific goals:
Knowledge of the properties of a database schema and of a decomposition. Ability to retrieve information in a relational database using relational algebra. Ability to evaluate the cost of data access operations. Knowledge of protocols for concurrency control.

Knowledge and understanding:
Fundamentals of relational database design and querying (relational algebra). Main data structures for storage of data on secondary memory. Main techniques for concurrency control.

Applying knowledge and understanding:
To design relational schemes with “good properties”. To formulate queries in relational algebra. To evaluate costs of basic operations on a file with a given physical organization.

Critical and judgmental skills:
To be able to assess the properties of a relational schema and of a decomposition. To be able to choose an appropriate storage structure for the information in a schema.

Communication skills:
To be able to communicate/share che qualitative/quantitative characteristics of the relational structure of a database.

Learning skills:
To be able to use the learned concepts in the following module of the course and in a possible advanced course on Databases.

Educational objectives

General goals:
To be able to design/evaluate the properties, storage structure and protocols of a database management system.

Specific goals:
Knowledge of the properties of a database schema and of a decomposition. Ability to retrieve information in a relational database using relational algebra. Ability to evaluate the cost of data access operations. Knowledge of protocols for concurrency control.

Knowledge and understanding:
Fundamentals of relational database design and querying (relational algebra). Main data structures for storage of data on secondary memory. Main techniques for concurrency control.

Applying knowledge and understanding:
To design relational schemes with “good properties”. To formulate queries in relational algebra. To evaluate costs of basic operations on a file with a given physical organization.

Critical and judgmental skills:
To be able to assess the properties of a relational schema and of a decomposition. To be able to choose an appropriate storage structure for the information in a schema.

Communication skills:
To be able to communicate/share che qualitative/quantitative characteristics of the relational structure of a database.

Learning skills:
To be able to use the learned concepts in the following module of the course and in a possible advanced course on Databases.

Educational objectives

General objectives:
to acquire basic knowledge in probability theory.

Specific objectives:

Knowledge and understanding:
at the end of the course, students will be able to use basic notions in combinatorics to solve math problems, derive laws for discrete random variables.

Applying knowledge and understanding:
at the end of the course, students will be able to solve simple problems in discrete probability, problems concerning discrete random vectors and random numbers represented by continuous random variables. They will understand the role of indipendence and conditioning in discrete models and understand the meaning of some limit theorems, like the law of large numbers.

Critical and judgmental skills:
students will have the bases to analize and to build simple probabilistic models for physics, biology and technology, simulate discrete probability distribution, as well as the Gaussian distribution and understand the use of some elementry tools in statistics, like inference, sampling and simulation.

Communication skills:
ability to expose the contents of the course in the oral part of the test and in any theoretical questions present in the written test.

Learning skills:
the acquired knowledge will allow a study, individual or given in a course related to more specialized aspects of probability theory.

Educational objectives

General goals:
Our goal in this class is to unfold the concepts, structure, and mechanisms of modern operating systems. We will provide a thorough discussion of the fundamental characteristics that apply consistently throughout systems, and relate them to newer features raising from the recurrent development of technology and user necessities.

Specific goals:
The class will cover the characteristics and concepts of modern operating systems, with a particular reference to Unix and Linux. We will start off with a description of the evolution of the operating systems in time. Then, we will continue with fundamental concepts like processes, deadlock detection, mitigation, and prevention, concurrency and mutual exclusion, memory, processor, and I/O management, file systems, and security.

Knowledge and understanding
Deep understanding of how an operating system supports the execution of user programs and handles hardware peripherals of a computer. Techniques and fundamental methodologies to represent processes in main and secondary memory and to handle multiprogramming— multiple processes executed simultaneously in a systems with limited resources.

Applying knowledge and understanding
Being able to design user and system level programs in an efficient and secure way.

Critical and judgmental skills:
Being able to evaluate and foresee how programs will require and use system resources, uncover possible deadlock and livelock conditions in a multiprogramming system, guarantee the mutual exclusion among processes and protected access of sensitive memory and resources.

Communication skills:
Know how to communicate clearly and in a precise way the characteristics and support mechanisms provided by the operating systems.

Learning capability:
Being able to exploit the knowledge acquired in order to design system modules, user and system level programs in the second module of the course. Leveraging this knowledge to better understand more complex systems like distributed and cloud ones.

Educational objectives

General goals:
Our goal in this class is to unfold the concepts, structure, and mechanisms of modern operating systems. We will provide a thorough discussion of the fundamental characteristics that apply consistently throughout systems, and relate them to newer features raising from the recurrent development of technology and user necessities.

Specific goals:
The class will cover the characteristics and concepts of modern operating systems, with a particular reference to Unix and Linux. We will start off with a description of the evolution of the operating systems in time. Then, we will continue with fundamental concepts like processes, deadlock detection, mitigation, and prevention, concurrency and mutual exclusion, memory, processor, and I/O management, file systems, and security.

Knowledge and understanding
Deep understanding of how an operating system supports the execution of user programs and handles hardware peripherals of a computer. Techniques and fundamental methodologies to represent processes in main and secondary memory and to handle multiprogramming— multiple processes executed simultaneously in a systems with limited resources.

Applying knowledge and understanding
Being able to design user and system level programs in an efficient and secure way.

Critical and judgmental skills:
Being able to evaluate and foresee how programs will require and use system resources, uncover possible deadlock and livelock conditions in a multiprogramming system, guarantee the mutual exclusion among processes and protected access of sensitive memory and resources.

Communication skills:
Know how to communicate clearly and in a precise way the characteristics and support mechanisms provided by the operating systems.

Learning capability:
Being able to exploit the knowledge acquired in order to design system modules, user and system level programs in the second module of the course. Leveraging this knowledge to better understand more complex systems like distributed and cloud ones.

Educational objectives

General goals:
To be able to design/evaluate the properties, storage structure and protocols of a database management system.

Specific goals:
Knowledge of the properties of a database schema and of a decomposition. Ability to retrieve information in a relational database using relational algebra. Ability to evaluate the cost of data access operations. Knowledge of protocols for concurrency control.

Knowledge and understanding:
Fundamentals of relational database design and querying (relational algebra). Main data structures for storage of data on secondary memory. Main techniques for concurrency control.

Applying knowledge and understanding:
To design relational schemes with “good properties”. To formulate queries in relational algebra. To evaluate costs of basic operations on a file with a given physical organization.

Critical and judgmental skills:
To be able to assess the properties of a relational schema and of a decomposition. To be able to choose an appropriate storage structure for the information in a schema.

Communication skills:
To be able to communicate/share che qualitative/quantitative characteristics of the relational structure of a database.

Learning skills:
To be able to use the learned concepts in the following module of the course and in a possible advanced course on Databases.

Educational objectives

General goals:
To introduce students to scalable methodologies for the design and development of database software applications.

Specific goals:
To introduce students to formalised and scalable methodologies for the conceptual analysis and design of database applications, and to standard technologies for the development of databases.

Knowledge and understanding:
Students will acquire fundamental methodological skills in the design of medium-large database applications (in particular for what concerns: a) requirements elicitation; b) conceptual analysis; c) database design and main use-cases), and their development (using DBMSs and standard languages for defining, manipulating and querying data).

Applying knowledge and understanding:
Students will be able to proficiently apply the acquired skills in the actual design of medium-large database applications.

Critical and judgmental abilities:
Students will be able to take autonomous and rational decisions during the various phases of the design process of an actual database application.

Communication skills:
Students will be able to interact proficiently with final customers (for what concerns requirements elicitation) and with other designers (for what concerns the design process of medium-large software systems).

Learning capabilities:
Students will be able to extend their skills in the subjects of this course, by the autonomous reading of technical documentation concerning the design of database applications.

Educational objectives

General objectives:
Acquire basic knowledge on fundamental algorithm design techniques and techniques to analyze the correctness and the complexity of an algorithm.

Specific objectives:

Knowledge and understanding:
At the end of the course, the student knows:
- fundamental algorithm design techniques,
- techniques to analyze the correctness and the efficiency of an algorithm.

Apply knowledge and understanding:
At the end of the course, the student is able to:
- analyze the complexity of a problem using rigorous mathematical tools,
- analyze existing algorithms and data structures,
- design and analyze new algorithms and data structures for simple real-life-problems.

Critical and judgmental skills:
The student, at the end of the course, should be able to autonomously choose which algorithmic technique is best suited for a given problem and to evaluate among several algorithmic solutions for a certain problem which one should prefer.

Communication skills:
The student will acquire the ability to express an algoritmic idea throught the use of a pseudocode.

Learning ability:
The student will acquire the ability to analyse a problem, and to design the necessary data structures and the correct and efficient algorithms for the problem.

Educational objectives

General goals:
- Learn the fundamentals of modern computer networks and Internet

Specific goals:
Knowledge and understanding:
- Application, transport, network, and data-link protocols of the TCP/IP model

Applying knowledge and understanding:
- Understand any protocol involved with TCP/IP communications
- Grasp powerful network troubleshooting tools and techniques
- Ability to use network services like DNS and DHCP that help make computer networks run

Autonomy of judgment:
- Detect network problems
- Evaluate the design of new services

Communication skills:
- Ability to describe computer networks in terms of a five-layer model

Learning ability:
- The course provides the fundamentals to learn notions related to wireless systems and Internet of Things

Educational objectives

General goals:
Our goal in this class is to unfold the concepts, structure, and mechanisms of modern operating systems. We will provide a thorough discussion of the fundamental characteristics that apply consistently throughout systems, and relate them to newer features raising from the recurrent development of technology and user necessities.

Specific goals:
The class will cover the characteristics and concepts of modern operating systems, with a particular reference to Unix and Linux. We will start off with a description of the evolution of the operating systems in time. Then, we will continue with fundamental concepts like processes, deadlock detection, mitigation, and prevention, concurrency and mutual exclusion, memory, processor, and I/O management, file systems, and security.

Knowledge and understanding
Deep understanding of how an operating system supports the execution of user programs and handles hardware peripherals of a computer. Techniques and fundamental methodologies to represent processes in main and secondary memory and to handle multiprogramming— multiple processes executed simultaneously in a systems with limited resources.

Applying knowledge and understanding
Being able to design user and system level programs in an efficient and secure way.

Critical and judgmental skills:
Being able to evaluate and foresee how programs will require and use system resources, uncover possible deadlock and livelock conditions in a multiprogramming system, guarantee the mutual exclusion among processes and protected access of sensitive memory and resources.

Communication skills:
Know how to communicate clearly and in a precise way the characteristics and support mechanisms provided by the operating systems.

Learning capability:
Being able to exploit the knowledge acquired in order to design system modules, user and system level programs in the second module of the course. Leveraging this knowledge to better understand more complex systems like distributed and cloud ones.

Educational objectives

General goals:
Our goal in this class is to unfold the concepts, structure, and mechanisms of modern operating systems. We will provide a thorough discussion of the fundamental characteristics that apply consistently throughout systems, and relate them to newer features raising from the recurrent development of technology and user necessities.

Specific goals:
The class will cover the characteristics and concepts of modern operating systems, with a particular reference to Unix and Linux. We will start off with a description of the evolution of the operating systems in time. Then, we will continue with fundamental concepts like processes, deadlock detection, mitigation, and prevention, concurrency and mutual exclusion, memory, processor, and I/O management, file systems, and security.

Knowledge and understanding
Deep understanding of how an operating system supports the execution of user programs and handles hardware peripherals of a computer. Techniques and fundamental methodologies to represent processes in main and secondary memory and to handle multiprogramming— multiple processes executed simultaneously in a systems with limited resources.

Applying knowledge and understanding
Being able to design user and system level programs in an efficient and secure way.

Critical and judgmental skills:
Being able to evaluate and foresee how programs will require and use system resources, uncover possible deadlock and livelock conditions in a multiprogramming system, guarantee the mutual exclusion among processes and protected access of sensitive memory and resources.

Communication skills:
Know how to communicate clearly and in a precise way the characteristics and support mechanisms provided by the operating systems.

Learning capability:
Being able to exploit the knowledge acquired in order to design system modules, user and system level programs in the second module of the course. Leveraging this knowledge to better understand more complex systems like distributed and cloud ones.

Educational objectives

General goals:
The course introduces the students to some of the most important results in theoretical computer science: from the fundamental results in computability theory of the thirties, through the ones in automata theory of the fifties to the challenging open problem P versus NP, raised in the seventies.

Specific goals:
Students will understand that there are different models of computation and the reason for their different computational power.

The students will become familiar with abstract concepts such as language classes, universal machines, reducibility and they will know that some problems are impossible to solve by computers and that others are difficult to solve, even so difficult to solve that they could be considered unsolvable. They will see today's use of some of these results.

Knowledge and understanding:
By the end of the course the students will get familiar with the basic methods and results of the Theory of Computability and Complexity and they will be able to apply them to evaluate the complexity of problems from various fields. In particular, they will be able to:
prove the equivalence between different characterizations of regular languages
prove the equivalence between different characterizations of context-free languages
explain the concept of nondeterminism
explain the existence of problems without algorithmic solutions or those which are intractable

Applying knowledge and understanding:
By the end of the course the students will be able to:
build finite state automata by a formal or an informal specification of a language
build stack automata by a formal or an informal specification of a language
use reducibility between problems to prove either decidability or undecidability
use polynomial reductions to prove the NP-hardness of problems.

Criticaland judgmental skills:
Understand the right level of abstraction to solve problems, choose the more convenient computational model in an applicative context.

Communication skills:
describe problems that are undecidable, not provably intractable or intractable
explain the meaning and the relevance of the question “P=NP?"

Learning ability:
The student will be able to learn other computational models, both really new or variations of the ones seen during the course. She/he will be able to understand new NP-completeness proofs or more generally completeness proofs for any complexity class.

Educational objectives

General objectives:
The course explains the fundamentals of the methodologies and tools for the management of software processes. Particular attention is given to object-oriented analysis and design methodologies, and to their management and documentation through UML.

Specific objectives:
Introduction to software engineering approaches and software life cycle, in-depth analysis of the specific activities, analysis, design and testing of software systems, techniques for process management, with particular reference to the management of quality and risks and all 'cost analysis.

Knowledge and understanding:
At the end of the course students will have acquired knowledge about the main models of the software life cycle, the metrics for the sizing of the effort, the techniques for describing the different components of a software project. Knowledge about the use of UML language will have been acquired. Finally, they will also have become familiar with the scientific literature in the field.

Application of knowledge and understanding:
At the end of the course students will be able to work as a team in the activities of analysis, design, documentation and management of medium-sized software projects. Students will have learned to produce documentation based on UML, relative to the main types of diagrams: use cases, classes, interaction, status and activities, also through the use of professional software environments oriented to the systematic development of software projects. Finally, they will be able to produce an evaluation of the effort based on Function Points and Use Case Points.

Judgment skills:
Students will develop the analytical skills necessary to evaluate various alternatives during the software development process, with particular reference to the evaluation of architectural choices and project risks.

Communication skills:
Students will learn to document their choices, also through the use of documentation generation tools, in particular by exploiting diagrammatic notations. They will also have acquired the ability to prepare presentations related to scientific topics.

Learning ability:
The knowledge of the formal rigor aspects underlying the software engineering discipline will allow students to quickly gain confidence with techniques, in addition to those considered in the course, based on general principles.

Educational objectives

The final exam consists in the drafting, presentation and discussion of a written dissertation, prepared independently by the student, which documents in an organic and detailed the problem faced in the training internship and all the activities performed to reach the solution.

Educational objectives

The internship is carried out under the guidance of a manager and can be external (performed at companies or external bodies) or internal (carried out within the degree course). In both cases, the internship lasts about three months and requires that the student be offered a problem in the real world, to be solved through the elaboration of a project developed with a professional approach.