Logic and Proof: 20172018
Lecturer 

Degrees 
Schedule S1(CS&P) — Computer Science and Philosophy 
Term 
Hilary Term 2018 (16 lectures) 
Overview
Logic plays an important role in many disciplines, including Philosophy and Mathematics, but it is particularly central to Computer Science. This course emphasises the computational aspects of logic, including applications to databases, constraint solving, programming and automated verification, among many others. We also highlight algorithmic problems in logic, such as SATsolving, model checking and automated theorem proving.
The course relates to a number of thirdyear and fourthyear options.Propositional and predicate logic are central to Complexity Theory, Knowledge Representation and Reasoning, and Theory of Data and Knowledge Bases. They are also used extensively in ComputerAided Formal Verification, Probabilistic Model Checking and Software Verification.
Learning outcomes
At the end of the course students are expected to:
 Understand and be able to explain and illustrate the meaning of given logical formulas, to translate such formulas into English and viceversa.
 Be able to use the resolution proof system in proposiitonal logic and in predicate logic.
 Be able to express and formalize in a logical language properties of models such as graphs, strings and transition systems, and be able to determine the truth or falsity of such formulas in a given model.
Synopsis
Propositional logic (8 Lectures).
 Introduction. History of mathematical logic in computer science.
 Syntax and semantics of propositional logic. The SAT problem. Translating constraint problems to SAT.
 Logical equivalence and algebraic reasoning. CNF and DNF.
 Polynomialtime algorithms: Horn formulas, 2SAT, WalkSAT, and XORclauses.
 Binary decision diagrams.
 Resolution: soundness and refutation completeness.
 DPLL, clause learning, improvements, stochastic resolution.
 Compactness theorem.
Firstorder logic (8 Lectures).
 Signatures, structures and valuations.
 Examples: graphs, trees, strings, relational databases and number systems.
 Prenex normal form and Skolemisation.
 Herbrand models and ground resolution.
 Unification and resolution for predicate logic.
 Undecidability of satisfiability.
 Decidable theories: dense linear orders and linear arithmetic over the natural numbers.
Syllabus
 Syntax of propositional logic. Truth tables.
 HornSAT and 2SAT.
 Binary decision diagrams.
 Resolution. DPLL procedure.
 Compactness theorem.
 Syntax and semantics of firstorder logic.
 Prenex normal form and Skolemisation.
 Herbrand models and ground resolution.
 Unification and resolution for predicate logic.
 Undecidability of satisfiability for firstorder logic.
 Decidable theories, including linear arithmetic.
Reading list
Primary text:
 Logic for Computer Scientists. Uwe Schoning. Modern Birkäuser Classics, Reprint of the 1989 edition.
Secondary texts:
 Logic in computer science: modelling and reasoning about systems, 2nd edition, by M. Huth and M. Ryan. Cambridge University Press, 2004.
 Mathematical Logic for Computer Science, 3rd edition, by M. BenAri. Springer, 2012.
 Handbook of Practical Logic and Automated Reasoning, by J. Harrison. Cambridge University Press, 2009.
Further literature:
 Gödel, Escher, Bach: an Eternal Golden Braid, by D. Hofstadter. Basic Books, 1979.
 Logicomix: An Epic Search for Truth, by A. Doxiadis and C. Papadimitriou. Bloomsbury Publishing PLC, 2009.