The course spans the period
E4A (Fall 2018, see DTU’s academic calendar).
Lectures and tutorials take
place in building 324, room 070 every Tuesday, from 13:00 to 17:00.
The oral exam will be on
December 18, and possibly some day around it if needed.
Flemming
Nielson, Alberto Lluch Lafuente.
The basic idea behind model
checking is that we have a mathematical model of a software and/or hardware
system, and some property that we want to verify. The model is an abstract
description of what the system does (this could be manually or automatically
derived from either a specification or an implementation), and the property is
a description of what the system should do (possibly derived from some
requirements specification and expressed in specification languages called
temporal logics). A model checker is a software tool that will take any
model in a given formalism, and any property in a given logic, and will automatically
verify that property.
1. Every time we connect to a website, or use our
mobile phone, or fly on an airplane, we are relying on highly complex
distributed or embedded systems. As many aspects of our lives depend upon such
systems, we need them to be reliable – both in the sense of doing what we
expect them to do, and being fast enough to meet our expectations. Model
checking allow us to answer these questions, and in doing so build more robust
and reliable computer systems.
2. Model checking is used by key international IT
companies (Intel, Microsoft, Amazon, etc.) to provide highly reliable systems
and services. It is
indeed a unique design, analysis and development skill that that
internationally leading software and hardware companies need for engineering
safe and secure systems systems and services.
3. Model checking is a perfect complement to other
design, analysis and development techniques covered at courses offered at DTU
like program analysis and compiler
construction.
The course is split into two
main parts, in which we look at two different types of models and properties, and
a supplementary third part presenting a wider view of the field but in much
less detail.
Part I:
Discrete models and logics (56 blocks).
We use discrete models when
we are concerned with the possibility of something happening, as it lets
us model all the possible eventualities without considering how likely each one
is. This is typically used for systems that we have complete control over, and
so we want to ensure that they are free of bugs. For example, is it possible
for a mobile phone to crash? Or, is it possible for a word processor to
suddenly stop responding?
In this part of the course,
we will introduce something called a Kripke
structure as our modeling formalism. This is basically a finite state
machine whose states are labelled, and whose transitions
are nondeterministic (hence we take into account all possible eventualities).
We will introduce Computation Tree Logic (CTL) as a way of specifying
properties, and look at the CTL model checking
algorithm, although our focus will be on practical applications of model
checking. We will also think about what it means for two models to behave in an
equivalent way, by learning about a concept called bisimulation.
This is important for both comparing models and reducing the size of their
state space (making it easier to verify them). Finally we will take a brief
look at more expressive logics than CTL – in particular, a logic called CTL*.
Part II:
Stochastic models and logics in discrete time (56 blocks).
Sometimes we don't have
complete control of a system, because the environment it runs in is not
predictable. When we buy a ticket online, there is a chance that the network
could fail half way through the transaction – for example, a tree might fall
down and break a cable. Since there is always the possibility of something
going wrong, a more interesting question is to ask what the probability
of something happening is.
In this part of the course,
we will introduce a modelling formalism called a Discrete
Time Markov Chain (DTMC). This can be thought of as putting probabilities
on the transitions of the Kripke structures from Part
I. We will review some basic probability theory, and look at the behaviour of a DTMC as it evolves over time (transient
analysis), and after it has run for a long time (steady state analysis).
Building on this foundation, we will introduce a logic called Probabilistic
CTL (PCTL), and how to do model checking for it. This is an extension of
CTL in which we can ask questions like "can I be 99.99% certain that the
system won't crash before my ticket is booked?" We will extend the notion
of bisimulation from Part I to DTMCs, and briefly
look at what happens when we have both probabilistic and nondeterministic behaviour in a model.
Throughout this course, there
will be a strong emphasis on the practical application of model checking, and
we will make use of the PRISM model checker. This provides a higher level modelling language that maps onto all the mathematical
formalisms we have seen – transition systems and DTMCs – so that we do not need
to work with them directly. The aim is to develop a firm understanding of the
theory of model checking, but also to gain practical experience. There will be
two mandatory assignments, for which there will be a written report, and this
will be the basis of the oral exam.
o
You
can purchase the book here, from the university book store.
o
Please find errata for the book here.
·
The PRISM model
checker.
Meeting 
Date 
Lecturer 
Topic 
Reading Material 
Supplementary Material (on Campus Net) 
01 
4/9 
Flemming 
Introduction to the course. Overview of model checking and software
validation. Installing and using PRISM. 
Mandatory Assignment Part 0: Background and
Getting Started. Files FCFS.nm, FCFS.pctl, SRT.nm and SRT.pctl. Slides Lect1 and Exe1. 

02 
11/9 
Flemming 
Transition Systems. 
Sections 2, 2.1, 2.2.1 and 2.2.6 of [BK08]. 
Mandatory Assignment Part 1: Discrete Modelling and Verification. Slides Lect2 and Exe2. 
03 
18/9 
Flemming 
Computation Tree Logic (CTL). 
Sections 6, 6.1, 6.2 of [BK08]. 
Slides Lect3 and Exe3. 
04 
25/9 
Flemming 
CTL Model Checking. 
Sections 6.4, a bit of 6.8 of [BK08]. 
Slides Lect4 and Exe4. 
05 
2/10 
Flemming 
CTL Model Checking. 
Sections 6.4, a bit of 6.8 of [BK08]. 
Slides Lect5 and Exe5. 
06 
9/10 
Flemming 
Bisimulation. 
Sections 7, 7.1.1, 7.2 of [BK08]. 
Slides Lect6 and Exe6. 

22/10 

Hand in First Mandatory Assignment. 


07 
23/10 
Alberto 
Introduction to Markov chains. 
Sections 10, 10.1 of [BK08] 
Slides Lect7 and Exe 7. 
08 
30/10 
Alberto 
Probabilistic CTL, transient and steady state
distributions. Feedback session (mandatory assignment 1) 
Sections 10.1.1, 10.2 of [BK08] 
Slides Lect8 and Exe8 
09 
6/11 
Alberto 
The Qualitative Fragment of PCTL. 

Slides Lect9 and Exe9 
10 
13/11 
Alberto 
PCTL Model Checking. 
Sections 10.1.1, 10.2.1 of [BK08] 
Slides Lect10 and Exe10 
11 
20/11 
Alberto 
Probabilistic Bisimulation. 
Section 10.4.2 of [BK08] 
Slides Lect11 and Exe11 
12 
27/11 
Alberto 
Beyond CTL and PCTL. Work on the second mandatory assignment. 


29/11 
Hand in Second Mandatory Assignment. 

13 
4/12 
Flemming & Alberto 
Beyond CTL and PCTL. 


18/12 
Flemming & Alberto 
Oral exam. 
· 02246 page on CampusNet (participants, materials, etc.)
· 02246 page on DTU Kursusbasen (general description)