Intro

28/07/2022 was an important day for me because that day I completed the first step in my higher education career, I obtained a degree in Computer Science at Università degli Studi di Genova.

During these years I faced huge challenges (including a pandemic). It's been a mentally demanding period, with a lot of ups and downs, insomnia, anxiety and sadness, but eventually I met a bunch of cool people all unique in their own way, I am sorry we only had two semesters to see each other IRL, but I feel grateful for the opportunity of meeting them. Thanks Federico, we are very different in many ways and similar in many other. I am not entirely sure I would be here today without you, and thanks Marti, Fabio (F), Lorenzo (Lax), Lorenzo (Andrew), Davide (Scarro), Giorgio (Jojo), Milo, Samuele, Ali, Giacomo (Pede). I hope we may see again in the future,I wish you all the best for your life and more specifically I hope you may have the wisdom necessary to perform the right choices in your life. Sometimes I have been an asshole, sorry for that, I hope you learned something from me (not necessarily what I wanted to share).

Grades Transcript:

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Here you can find a course catalog. Have fun, and use this to finally understand the difference between Computer Engineering and Computer Science :)

Calculus 1

• Definition of derivative as a limit and the rules of differentiation to differentiate functions.
• The graph of a function using asymptotes, critical points, and the derivative test for increasing/decreasing and concavity properties.
• Max/min problems and the use of differentiation to solve them
• Integrals by using the Fundamental Theorem of Calculus.
• Techniques of integration, such as substitution, inverse substitution, partial fractions and integration by parts.

Architetture dei Calcolatori (Computer Architecture and Organization)

• Main elements of a computer, performances and computer languages, high level language, assembler and assembly language (MIPS architecture)
• A simple ALU model, boolean logic, CPU and control unit
• Memory hierarchies, mass storage memories and circuits
• Interrupts, traps and System Calls

Algoritmi e Strutture Dati (Algorithms and Data Structures)

• Methods for algorithm analysis: cost criteria, asymptotic notation, complexity analysis of recursive algorithms. Examples of development and analysis of algorithms.
• Sorting algorithms: insertion sort, selection sort, bubble sort, mergesort, quicksort
• Basic data structures: arrays and lists; stacks and queues; dictionaries implemented with lists.
• Dictionaries: implementation with binary search trees and hash tables.
• Trees: indexed and linked representations for binary trees and general trees; depth-first search and breadth-first search of trees.
• Search Trees: Binary search trees, search trees as a data structure for implementing dictionaries, balanced trees.
• Hash tables: collision lists and open addressing.
• Priority queues: implementation with lists and heaps.
• Graphs: definitions, data structures, primitives for querying and updating graphs; graph visits in depth and in width; examples of application of a graph visit algorithms.
• Laboratory: C++ laboratories related to course topics

Introduzione alla Programmazione (Introduction to Computer Programming)

• Introduction to the course, computational thinking, and programming.
• Programming environments and formal languages.
• Imperative programming: variables and instructions; assignment; input / output; if-then-else; loops; types; arrays; strings; functions; struct; dynamical y al ocating memory (heap); dynamic vectors; linked lists ; recursion and iteration.
• Simple algorithms on sequential data: ordering and search
• Introduction to problem analysis and solution design, with examples.

Algebra e Logica per Informatica (Algebra and Logics for Computer Science)

• Sets, functions, complex numbers, cardinality, combinatorics
• Algebraic structures, monoids, groups, rings, vectorial spaces,k-algebras, strings
• Heterogeneous algebras
• Introduction to logic
• Syntax of propositional logic
• Semantics of propositional logic: truth tables
• Syntax of first order logic
• Semantics of first order logic: models theory
• Formalization of problems

Linguaggi e Programmazione Orientata agli Oggetti (Programming Languages and Object Oriented Programming)

• Principles of programming languages: overview, programming paradigms; syntax, static and dynamic semantics, development of a semantics-driven interpreter.
• Object-oriented paradigm (the Java programming language): objects, classes, inheritance and dynamic binding, casting, overloading, exceptions. Advanced features: generic classes and methods, outline on nested classes and lambda-expressions. Practical uses of the standard API, iterator and visitor design pattern.
• Functional paradigm (the OCaml programming language): higher-order and polymorphic functions, polymorphic type inference, currying, functions on lists, user-defined types.

Sistemi di Elaborazione e Trasmissione dell' Elaborazione (Computer and Communication Systems)

• Introduction to modern operating systems
• Processes and threads; scheduling
• Memory management and virtualization
• File systems
• Computer Security
• Introduction to synchronization, deadlock
• Network technologies and 'internetworking
• Protocol Layers
• Internet stack (from application level to local network)
• Web and HTTP protocol
• File transfer
• Electronic Mail
• DNS protocol
• UDP and TCP protocols

Algebra Lineare e Analisi Numerica (Numerical Analysis and Linear Algebra)

• Error analysis
• Floating-point numbers and machine precision.
• Inherent error. Estimate for rational functions.
• Algorithmic error.
• Total error.
• Solution of nonsingular linear systems
• Numerical solution of linear systems (direct method of Gaussian elimination).
• Conditioning of matrices.
• Complexity and algorithmic error for the solution of linear systems.
• Other topics in linear algebra: geometric interpretation of vectors and matrices
• Scalar product and orthonormal bases.
• Matrices as geometric linear transformations.
• Null space, range and rank.
• Orthogonal matrices: rotations, reflections, QR factorization.
• Approximated solution of linear systems in the least-squares sense
• Geometric formulation of the problem.
• Normal equations.
• Solution through orthogonalization.
• Interpolation by spline functions
• Definition of interpolating spline.
• Computational procedure.
• Survey of mathematical and numerical properties.
• Other topics in linear algebra: eigenvalues
• Eigenvalues, eigenvectors, eigenspaces.
• Characteristic polynomial.
• Similarity relations and diagonalization.
• Applications.
• SVD and applications to least-squares
• Singular values decomposition (SVD) and relations with eigenvalues.
• Geometric properties of SVD and numerical rank.
• Generalized inverse and conditioning.
• Solution of the least-squares problem via SVD.
• Application to discrete data approximation (smoothing).
• Numerical treatment of eigenvalues
• Numerical properties: conditioning and localization.
• Iterative power method and variants.
• Other numerical methods: similarity reduction to a simplified form, QR method.

Basi di Dati (Database Management Systems)

• Introduction to DBMS concepts.
• Traditional data models; the relational model and languages.
• SQL language: querying and manipulation of relational datai.
• Entity-Relationship model.
• Logic database design.
• Quality control: normalization.
• Data management inside applications: stored procedures; SQL usage from a programming language, triggers.
• DBMS internals; indexes and query tuning, transactions and access control.
• Physical database design
• Lab: usage of a DBMS.

Teoria dell' Informazione e Inferenza (Information Theory and Inference)

• Elements of probability theory. Probability of an event, conditional probability, Bayes theorem, discrete random variables, probability distributions, expected values and variance, marginal probability, asymptotic laws..
• Elements of Information Theory. Information and entropy (Shannon). Kraft Mc Millian inequality. Information encoding without noise, Huffman Coding, Arithmetic Coding, Convolutional Encoding
• Elements of inference. Maximum likelihood estimation.
• Bayesian learning. Monte Carlo and Markov chains.

Analisi e Progettazione di Algoritmi (Algorithm analysis and design)

• Design and analysis techniques, asymptotic notations, correctness and complexity of recursive and iterative algorithms, divide-et-impera, dynamic programming, greedy algorithms.
• Sorting: simple sorts, mergesort, quicksort, heapsort, lower bound for comparison-based sorting algorithms, linear sorts.
• Advanced data structures: heaps, union-find structures.
• Graphs: definitions, representations, visits, topological sorting, strongly-connected components, single-source shortest paths (Dijkstra algorithm), minimum spanning tree (Prim and Kruskal algorithms).
• Theory of NP-completeness: complexity classes, NP-complete problems, approximation algorithms

Teoria degli Automi e Calcolabilita' (Automata Theory and Computability)

• Alphabets, strings, languages
• Deterministic (DFA) and non deterministic (NFA) finite state automata
• DFA minimization, regular expressions
• Closure properties of regular languages, pumping lemma
• Context-free grammars, derivation trees, ambiguity
• Deterministic and non deterministic push down automata (PDA)
• Closure properties of context-free languages, pumping lemma
• Turing machines, accepted languages
• Undecidability, recursive and recursively enumerable languages, universal language and machine, undecidability of the universal language
• Halting problem
• Undecidable problems on Turing machines, Rice theorem, Church thesis

Calculus 2

• Improper integrals.
• Sequences and series of functions.
• Functions of several variables, continuity, differentiability, derivative.
• Multiple integrals, change of variables
• Systems of differential equations
• Fourier series

Computazione Quantistica (Quantum Computing)

• Introduction
• Alternative systems and techniques of computation
• Universal logic gates
• Using 'snooker' as a computation system DNA computation
• Mathematical foundations: complex number, tensor product, unary operators
• Introduction to quantum phenomena
• 1900: experimental results: state superposition, measurements, entangled states
• Qubits as quantum states with two levels. Qubit superposition, qubit state representations on the 'Bloch sphere'
• Applications of unary operators to qubits. Classical logic gates, quantum logic gates, 2-qubits logic gates ("entangling gates"), usage of Pauli matrices to describe logic gates and unary operators
• Quantum information
• Quantum paral elism
• "No-cloning" Theorem
• "Dense coding"
• Quantum teleportation
• Simple quantum algorithms
• Deutch, Deutch-Josa and Simon algorithms
• Quantum cryptography: BB protocol, cryptographic protocols implementations
• Quantum algorithms: "Black Box" algorithm, Grover algorithm

Computer Security

• Introduction Computer Security
• The concepts of resource, vulnerability, threat, countermeasure, and risk
• Security goals: confidentiality, integrity, availability, ...
• Introduction to Cryptography
• Fundamental concepts (cryptography, cryptanalysis, general cryptographic schema)
• Monoalphabetic substitution ciphers (Caesar cipher)
• Polyalphabetic substitution ciphers (Vigen�re cipher)
• One-time pads (Vernam cipher)
• Transposition ciphers
• Composite ciphers
• Symmetric Cryptography
• Block and stream ciphers
• Feistel cipher structure
• DES and 3DES
• Modes of operation (Electronic Code Book, Cipher-Block Chaining, Stream Ciphers)
• Link vs end-to-end encryption
• The key distribution problem
• Public-Key Cryptography
• Introduction to public-key cryptography
• Introduction to Number Theory
• The RSA algorithm
• Diffie-Hellman key exchange
• Message Authentication and Digital Signatures
• Message integrity and authentication functions (message encryption, message authentication code,cryptographic hash functions)
• Digital signature
• Public Key Infrastructure (PKI)
• PKI components
• Digital Certificates Trust models
• Security Protocols
• Basic notions (protocol execution, assumptions and goals, attacker model)
• Examples of protocols (NSPK, Otway-Rees, Andrew Secure RPC, Denning & Sacco)
• Prudent engineering of security protocols
• Kerberos (architecture, protocol, inter-realm communication, limitations)
• Secure mail (PGP)
• Network Security
• Link Layer: WiFi Security
• Network Layer: IP-Sec
• Transport Layer: SSL/TLS
• Introduction to Firewalls
• Web Security
• Security on the client side (cookies and privacy, HTTP authentication mechanisms)
• Security on the server side (unvalidated input, broken authentication and session management, cross-site scripting, injection flaws, denial of service, ...)
• Secure Programming
• Buffer overflows
• Format string vulnerabilities
• Access Control
• Discretionary vs Mandatory Access Control
• Access control matrix model
• Role-Based Access Control (RBAC)
• Administrative Role-Based Access Control (ARBAC)
• Bell-LaPadula, Harrison-Ruzzo-Ullman, Chinese Wall models
• Cyber Exercise [12h hands on]

Fondamenti di Ingegneria del Software (Elements of Software Engineering)

• Introduction to the course and to software engineering
• Software development process models, agile methods (eg. Extreme programming)
• Requirements Engineering. Scenarios and use cases
• Design principles and design methods, coupling and cohesion, software architecture, design patterns, refactoring
• The UML: Class diagram, Sequence diagram, State Machine diagram, Activity diagram
• Software Testing: Testing functional / structural and coverage.
• Unit tests, integration, system, acceptance tests and regression tests
• Software evolution and Maintenance

Fondamenti di Elaborazione dei Segnali e Immagini (Elements of signal and image processing)

• Discrete Fourier Transformation
• Representation and processing of signals through DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform)
• Representation and processing of images through DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform)
• Sampling Noise treatment Filters and applications

Introduzione alla data science (Elements of data science)

• Introduction to Python
• Data collection and management, including pre-processing for typical real-world datasets
• Data analysis: statistical analysis, (foundations of) predictive analysis
• Visualization: GeoPandas, Plotly, NetworkX
• Distributed systems foundations: HPC and Big Data

Programmazione Concorrente e Algoritmi Distribuiti (Concurrent Programming and distributed algorithms)

• OS-level concurrency & multi-threading
• Concurrent development techniques
• Lock-free synchronization (focus on 'relaxed memory' architectures)
• Standard synchronization techniques: mutexes and barriers
• Memory models and Sequential consistencies
• Pthread, semaphores, monitors and synchronization barriers
• Concurrency in Java
• Threads as objects, fundamental synchronization primitives
• Libraries for High Level Concurrency
• Eclipse and debugging multithreaded code on Eclipse Threads, monitors, semaphores
• Producer-consumer pattern
• GUI, Events and Concurrency
• Swing, Javafx and Concurrency
• Async Tasks in Android (Java and Kotlin)
• Introduction to Distributed Algorithms
• Distributed Programming in Java
• Connection Pool (Connection Caching)
• Client-Server with Java Sockets

Sviluppo di Applicazioni Web (Web Application Development)

• Static Web pages creation with HTML5 and CSS.
• Server side programming: Dynamic Web page creation using PHP, syntax, data and control structures, objects. Cookies management, access control, session control. Interacting with databases via PHP scripts. Accessing databases with PDO.
• Introduction to XML and JSON.
• Client side programming: Javascript and the Document Object Model specification. Introduction to AJAX and JavaScript libraries.
• The REST (REpresentational State Transfer) architectural paradigm.
• Security, usability and accessibility in Web applications.
• Practical and final project covering al the subjects seen during the semester.