Insegnamento a.a. 2022-2023

Unit 1 (Computability - introduction)

·         Course overview

·         Introduction

·         Turing Machine (TM)

Unit 2 (Computability – more on TM)

·         More on the definition of TM

·         Decidable and Recognizable languages

·         Variants of TM

·         Simulation

Unit 3 (Computability – undecidability)

·         The Church-Turing Thesis

·         Examples of decidable languages

·         The Halting problem

Unit 4 (Computability – undecidability contd.)

·         More non-decidable problems

·         Reductions

Unit 5 (Computability – Rice’s theorem)

·         Rice’s Theorem

·         Post Correspondence Problem

·         Wrap up computability

Unit 6 (Complexity - Introduction)

·         Definition of time complexity

·         Complexity of single vs Multiple Tape TM’s

·         PTIME, PATH

Unit 7 (Complexity – The class NP)

·         Non-deterministic TM

·         Poly-time verifiability

·         The classes NP and coNP

Unit8 (Complexity – NP completeness)

·         Poly-time reducibility

·         NP completeness

·         Existence of NP-complete problems

Unit 9 (Complexity – Cook-Levin)

·         Cook-Levin Theorem

·         More NP-complete problems

·         Decision vs. Search

Unit 10 (Complexity – The class PSPACE)

·         Cook/Karp/Levin reductions

·         Coping with NP-hardness

·         Space complexity

Unit 11 (Cryptography - Encryption)

·         Perfect secrecy

·         Computational secrecy

Unit 12 (Cryptography - Authentication)

·         Message authentication

·         Digital signatures

The most important skill that the students are expected to pick up during this course is the ability to recognize and interpret computational intractability in case it is encountered. The course aims to develop a solid conceptual understanding of notions related to computation:

·         The concept of universal models of computation (such as Turing machines), that capture our intuitive notion of computation and allow us to reason about the capabilities of computers in a technology-independent manner.

·         The existence of intrinsic limits to computation. Computational problems that cannot be solved by any algorithm whatsoever (undecidability), and problems that are solvable but require unreasonable computational resources (computational complexity).

·         The notion of nondeterminism and in particular the conceptual difference between finding a solution and verifying that a given solution is correct.

·         The representation of computational problems, and the distinction/relationships between decision and search problems.

·         The notion of a reduction between computational problems and its implications on the relative complexity of the problems.

• Recognize problems that are NP-complete, and be able to devise simple NP-completeness proofs
• Recognize problems that are  undecidable, and be able to devise simple undecidability proofs
• Apply the idea of a reduction among computational problems
• Apply definitions of security in encryption and authentication 
• Be able to spot potential problems in proposed cryptographic protocols

• Face-to-face lectures
• Online lectures
• Guest speaker's talks (in class or in distance)

Biweekly homework assignments (4-5 questions each) will give you feedback on how you are doing and will help you internalize the material studied.

Assessment will be the same for attending and non-attending students.
Written exam (70% of the final grade) consists of open-ended questions,
some of which will test the student's understanding of the concepts
developed during the course (for example, the ability to reason about
graphs, to reason about the correctness of a given algorithm, or to analyze
the running time of a given
algorithm) and some of which will test the student's ability to apply such
concepts to new contexts, for example their ability to devise an algorithm
for a new problem, to prove the NP-completeness of a new problem, or to
prove the undecidability of a new problem.

Students can take the first partial written exam in the middle of the
semester and complete the second partial exam at the end of the course. In
this case the weight is: 35% for the first partial exam and 35% for the
second partial exam.
Alternatively, students can take a final written exam that accounts for 70%
of the final grade.

There is no required textbook. Recommended textbooks will be communicated to the students at the start of classes. Lecture slides and notes will be provided for selected topics.