# COMP21111 Logic and Modelling syllabus 2021-2022

COMP21111 materials

COMP21111 Logic and Modelling

Level 2
Credits: 10
Enrolled students: 108

Requisites

• Pre-Requisite (Compulsory): MATH10111
• Pre-Requisite (Compulsory): MATH10131
• Pre-Requisite (Compulsory): MATH10212
• Pre-Requisite (Compulsory): MATH10232
• Pre-Requisite (Compulsory): COMP11120

• Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Pre-requisites

To enrol students are required to have taken COMP11120 or one of the following: MATH10111, MATH10131 , MATH10212, MATH10232.

Assessment methods

• 50% Written exam
• 50% Coursework
Timetable
SemesterEventLocationDayTimeGroup
Sem 1 w1-5,7-12 Lecture Engineering Building B 2B.020 Blended Theatre 2 Tue 14:00 - 15:00 -
Sem 1 w3-5,7-12 ONLINE Examples Fri 09:00 - 10:00 -
Sem 1 w3-5,7-12 ONLINE Examples Fri 10:00 - 11:00 -
Themes to which this unit belongs
• Rigorous Development

## Overview

This is a unique course developed at the University of Manchester. It explains how implementations of logic can be used to solve a number a number of problems, such as solving hardest Sudoku puzzles in no time, analysing two-player games, or finding serious errors in computer systems

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.

## Aims

This course intends to build an understanding of fundamentals of (mathematical) logic as well as some of the applications of logic in modern computer science, including hardware verification, finite domain constraint satisfaction and verification of concurrent systems.

## Syllabus

• Propositional logic
• Conjunctive normal form (CNF)
• DPLL satisfiability algorithm
• Randomized satisfiability algorithms
• Compact representations of Boolean functions using BDTs/BDDs/OBDDs
• Quantified Boolean Logic (QBF) Splitting and DPLL algorithms for QBF
• Propositional logic of finite domains
• State-changing systems
• Linear temporal logic (LTL)
• Model checking

## Teaching methods

Lectures

22 in total, 2 per week, including some feedback sessions on exercises

## Feedback methods

My Website of this course will contain a lot of material, including solutions to exercises

## Study hours

• Assessment written exam (2 hours)
• Lectures (24 hours)
• Practical classes & workshops (9 hours)

## Employability skills

• Analytical skills
• Innovation/creativity
• Problem solving
• Research

## Learning outcomes

On successful completion of this unit, a student will be able to:

• Have a knowledge about basic reasoning (or satisfiability-checking) algorithms for propositional logic.
• Have a knowledge of quantified boolean formulas and basic understanding of bound variables and quantifiers.
• To understand BDDS (binary decision diagrams) as a data structure for compact representation of propositional formulas.
• Have a knowledge about applications of propositional logic (such as finite domain constraint satisfaction and planning) and be able to apply it for solving hard combinatorial problems.
• Have a knowledge of simple temporal logics.
• Be able to formally specify finite-state concurrent systems as transition systems.
• Be able to specify properties of simple transition systems in temporal logics.