title:
Algorithmic Aspects of Well Quasi-Order Theory
Aspects algorithmiques de la théorie des beaux préordres
manager:
Jean Goubault-Larrecq
ects:
3
period:
1
hours:
24
weeks:
8
hours-per-week:
3
language:
English on request
lang:
track:
B
themes:
Automata/Games, Verification, Complexity
order:
2.09.1
successor:
wqo

Motivations & Objectives

Well-quasi-orderings, or wqos, play a fundamental role in important results in multiple areas of computer science: formal language theory, rewriting, program verification, algorithmic graph theory, automated deduction, etc., and they are still intensively used nowadays. At their very core, a wqo is a tool to prove finiteness statements; a major use is to show the termination of algorithms—where wqos provide a generalisation of well-founded linear orders. In particular, this has led to the definition of an abstract class of systems, called well-structured transition systems (WSTS), for which generic algorithms for various decision problems can be provided (in particular verification problems), and the termination of those algorithms relies on wqos.

The objective of this course is to present

  1. the basic notions of wqo theory, motivated and illustrated by algorithmic applications in various areas, with a particular focus on well-structured transition systems and their automated verification;
  2. a glimpse at the limitations of wqos, along with the possible solutions through better quasi orders (bqos) or Noetherian topological spaces;
  3. beyond proofs of termination, how to instrument wqos in order to extract complexity upper bounds, and how these match the lower bounds for some natural decision problems;
  4. as required by the previous point, an introduction to subrecursive hierarchies, i.e., ordinal-indexed hierarchies of recursive functions, and the associated complexity classes for very high complexity problems;

An application of these techniques is the proof of the ACKERMANN-completeness of the reachability problem for Petri nets—which is not covered in this course, as this would be a topic for an entire course on its own.

The course is usually split into two parts, corresponding roughly to points 1–2 and 3–4 above.

Course Plan

The section/chapter/exercise numbers refer to the lecture notes.

Part 1: Basics of wqos and algorithmic applications

(J. Goubault-Larrecq)

Part 2: Complexity of wqo-based algorithms

(S. Schmitz)

Evaluation

The evaluation is in two parts: a homework assignment serving as midterm exam, and a final written exam.

Here are a past homework assignment, the 2019 final exam, the 2023 final exam, and the 2024 final exam.

Main related courses:

Other related courses: