02246: Model Checking

Dates

The course spans the period E4A (Fall 2017, see DTU’s academic calendar).

Lectures and tutorials take place in building 303A, room 044 every Tuesday, from 13:00 to 17:00.

The oral exam will be on December 19, and possibly some day around it if needed.

Lecturers

Flemming Nielson, Alberto Lluch Lafuente.

What is Model Checking?

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.

Why is it important?

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.

Course Structure

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 (5-6 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 non-deterministic (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 (5-6 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 non-deterministic 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.

Textbooks and Course Materials

o   You can purchase the book here, from the university book store.

o   Please find errata for the book here.

Tools

·      The PRISM model checker.

Course Schedule (subject to changes)

Meeting

Date

Lecturer

Topic

Reading Material

Supplementary Material (on Campus Net)

01

 

5/9

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

12/9

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

19/9

Flemming

Computation Tree Logic (CTL).

Sections 6, 6.1, 6.2 of [BK08].

Slides Lect3 and Exe3.

04

26/9

Flemming

CTL Model Checking.

Sections 6.4, a bit of 6.8 of [BK08].

Slides Lect4 and Exe4.

05

3/10

Flemming

CTL Model Checking.

Sections 6.4, a bit of 6.8 of [BK08].

Slides Lect5 and Exe5.

06

10/10

Flemming

Bisimulation.

Sections 7, 7.1.1, 7.2 of [BK08].

Slides Lect6 and Exe6.

 

23/10

 

Hand in First Mandatory Assignment.

 

 

07

24/10

Alberto

Introduction to Markov chains.

Sections 10, 10.1 of [BK08]

Slides Lect7 and Exe 7.

08

31/10

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

7/11

Alberto

The Qualitative Fragment of PCTL.


Section 10.2.2 of [BK08]

Slides Lect9 and Exe9

10

14/11

Alberto

PCTL Model Checking.

Sections 10.1.1, 10.2.1 of [BK08]

Slides Lect10 and Exe10

11

21/11

Alberto

Probabilistic Bisimulation.

Section 10.4.2 of [BK08]

Slides Lect11 and Exe11

12

28/11

Alberto

Beyond CTL and PCTL.

Work on the second mandatory assignment.

 

30/11

Hand in Second Mandatory Assignment.

13

5/12

Flemming

& Alberto

Beyond CTL and PCTL.
Feedback session (mandatory assignment 2)

 

19/12

Flemming

& Alberto

Oral exam.

Other pages

·      02246 page on CampusNet (participants, materials, etc.)

·      02246 page on DTU Kursusbasen (general description)