Logic For Computer Science

Learning time distribution

Learning outcomes

Knowledge

• C1.Fundamental computer science and math knowledge. / Cunoștințe fundamentale de informatică și matematică.

Skills

• A1. The ability to identify appropriate formal/computational models, to use scientific modeling/computational instruments, to analyze the efficiency of an instrument or to use data structures/
• Abilitatea de a identifica modele formale/computaționale adecvate, de a utiliza instrumente de
• modelare și de calcul științific, de a analiza eficiența unui algoritm sau a utilizării unei structuri de
• date.
• A3. The ability to identify appropriate algorithms/data structures for solving concrete problems, to apply the development principles to applications and to implement algorithms in a programming language. /Abilitatea de a identifica algoritmi și structuri de date adecvate unei probleme concrete, de a
• aplica principiile de dezvoltare a unei aplicații informatice și de a implementa algoritmi într-un
• limbaj de programare.

Responsibility

• R1. The capacity to solve automatically specific tasks, in an autonomous manner/ Capacitatea de a rezolva în manieră autonomă sarcini specifice.
• R2. The capacity to identify/select appropriate solutions and to generate novel ideas. / Capacitatea de a identifica/selecta soluții/căi de rezolvare adecvate și de a genera idei
• inovative.
• R3. The capacity to identify and plan correctly the specific tasks for a particular project. / Capacitatea de a identifica și planifica corect/eficient sarcinile specifice unui anumit proiect.
• R6. The capacity to adapt to new requirements and ways to carry out activities. / Capacitatea de a se adapta la noi cerințe și modalități de desfășurare a activității.

Online platform

Course content

Course bibliography

Adrian Crăciun – Logic for Computer Science. Lecture Notes. 2024 (Posted on Google Classroom) Mordechai Ben-Ari, Mathematical Logic for Computer Science. Second Revised Edition. Springer, 2001. Bruno Buchberger, Logic for Computer Science. Manuscript, Copyright Bruno Buchberger 1991. Folosit cu permisiunea autorului. Jean H. Gallier, Logic for Computer Science, Foundations of Automatic Theorem Proving, Copyright 2003, Jean H. Gallier. John Harrison, Handbook of Practical Logic and Automated Reasoning, Cambridge University. Daniel J. Velleman, How to Prove It: A Structured Approach, Second Edition, Cambridge University Press, 2006.

Seminar content

Seminar bibliography

Reasoning-based problem solving knowledge and skills are essential in any activity based on computer science, and this is particularly true for the IT industry.

Corroboration

(none)

AI tools guidance

Evaluation and delivery

Performance standards

Basic knowledge of the concepts presented in the lecture: explain and apply. Minimal knowledge is measured by reaching the grade for passing the exam (5).

Additional info

(none)