Formal Methods and Functional Programming

Overview

Lecturers: Prof. Dr. Peter Müller and Prof. Dr. David Basin

Classes: Tuesdays 10-12 and Thursdays 10-12

Credits: 7 ECTS (4V + 2U)

Language: English (lectures), English and German (exercises)

Exercise classes: Tuesdays 14-16, Wednesdays 8-10 or Wednesdays 16-18

For questions/issues concerned with the first half (Functional Programming), please contact François Hublet; for the second half (Formal Methods), please contact Nicolas Klose.

Announcements

• [2024/05/02] The second midterm will take place on May 14 at 10:00 in the usual lecture halls.
• [2024/05/02] We will provide protected page this cheat sheet for the final. For the midterm we will provide a reduced version which only contains the materials covered so far.
  
• [2024/04/13] The FM team has magically time-travelled a year into the present!
  
• [2023/04/12] The FP team is handing the course over to the FM team. Have fun!
  
• [2023/04/12] The protected page master solution of the first midterm has been released.
  
• [2023/03/04] Our first midterm will take place on March 14 at 10:00 in the usual lecture halls!
  
• [2023/02/14] You can now enroll in an exercise group using CodeExpert. Note that enrollment in CodeExpert is obligatory to attend the exercises.
  
• [2023/01/25] The course webpage for this year's FMFP is up and running!
  

Description

In this course, participants will learn about new ways of specifying, reasoning about, and developing programs and computer systems. Our objective is to help students raise their level of abstraction in modelling and implementing systems.

The first part of the course will focus on designing and reasoning about functional programs. Functional programs are mathematical expressions that are evaluated and reasoned about much like ordinary mathematical functions. As a result, these expressions are simple to analyse and compose to implement large-scale programs. We will cover the mathematical foundations of functional programming, the lambda calculus, as well as higher-order programming, typing, and proofs of correctness.

The second part of the course will focus on deductive and algorithmic validation of programs modelled as transition systems. As an example of deductive verification, students will learn how to formalize the semantics of imperative programming languages and how to use a formal semantics to prove properties of languages and programs. As an example of algorithmic validation, the course will introduce model checking and apply it to programs and program designs.