CSE 599 F Formal Verification of Computer Systems

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CSE 599 F: Formal Verification of Computer Systems CSE 599 F: Formal Verification of Computer Systems

Course information • Instructor: Shaz Qadeer • Office: 454 Allen Center • Lectures: CSE Course information • Instructor: Shaz Qadeer • Office: 454 Allen Center • Lectures: CSE 303, Wed-Fri, 12 pm 1: 20 pm • Office hours: Wed-Fri, by appointment • Web page: http: //www. cs. washington. edu/education/courses/599 f/

What is this course about? • Techniques for improving reliability of computer systems – What is this course about? • Techniques for improving reliability of computer systems – Applicable to both software and hardware – Focus on software • Automated techniques for verification of partial specifications

This course is not about… • • Programming languages and type systems Software engineering This course is not about… • • Programming languages and type systems Software engineering methodology Dynamic analysis Software testing

Prerequisites • • Algorithms Formal language theory Elementary mathematical logic But, none of that Prerequisites • • Algorithms Formal language theory Elementary mathematical logic But, none of that matters if you really want to understand the material

Goals • Learn about the fundamental ideas • Understand the current research problems • Goals • Learn about the fundamental ideas • Understand the current research problems • Do novel research The best advances come from a combination of techniques from different research areas!

Grades • Homeworks – Work out examples and theoretical problems – Use prototype verification Grades • Homeworks – Work out examples and theoretical problems – Use prototype verification tools to verify simple examples • Discussion and review of research articles • Project (in groups of 1 -2) – Independent research – Survey of a research area – Use a verification tool to verify a realistic system

Why should we care? • NIST (National Institute of Standards and Technology) report – Why should we care? • NIST (National Institute of Standards and Technology) report – software bugs cost $60 billion annually • High profile incidents of systems failure – – Therac-25 radiation overdoses, 1985 -87 Pentium FDIV bug, 1994 Northeast blackout, 2003 Air traffic control, LA airport, 2004

Intellectual challenge • Civil engineering – Bridges don’t fail Intellectual challenge • Civil engineering – Bridges don’t fail

Reliable Engineering Reliable Engineering

Intellectual challenge • Civil engineering – Bridges don’t fail • Mechanical engineering – Cars Intellectual challenge • Civil engineering – Bridges don’t fail • Mechanical engineering – Cars are reliable

Intellectual challenge • Civil engineering – Bridges don’t fail • Mechanical engineering – Cars Intellectual challenge • Civil engineering – Bridges don’t fail • Mechanical engineering – Cars are reliable • Software engineering

Why is software hard? • The human element – Getting a consistent and complete Why is software hard? • The human element – Getting a consistent and complete set of requirements is difficult – Requirements often change – Human beings use software in ways never imagined by the designers

Why is software hard? • The mathematical element – Huge set of behaviors – Why is software hard? • The mathematical element – Huge set of behaviors – Nondeterminism • External due to inputs • Internal due to concurrency – Even if the requirements are unchanging, complete and formally specified, it is infeasible to check all the behaviors

Bubble Sort Bubble. Sort(int[] a, int n) { for (i=0; i<n-1; i++) { for Bubble Sort Bubble. Sort(int[] a, int n) { for (i=0; i

Simple programming language x Variable P Program = assert x | x++ | x-- Simple programming language x Variable P Program = assert x | x++ | x-- | P 1 ; P 2 | if x then P 1 else P 2 | while x P Assertion checking for this language is undecidable!

Holy grail of algorithmic verification • Soundness – If the algorithm reports no failure, Holy grail of algorithmic verification • Soundness – If the algorithm reports no failure, then the program does not fail • Completeness – If the algorithm reports a failure, then the program does fail • Termination – The algorithm terminates It is impossible to achieve the holy grail in general!

Methods • Model checking • Axiomatic verification Methods • Model checking • Axiomatic verification

Model checking • Create a model of the program in a framework that is Model checking • Create a model of the program in a framework that is decidable – Finite state system – Pushdown system • Manual model creation • Automated model verification

Axiomatic verification • Program verification similar to validity checking in a mathematical logic – Axiomatic verification • Program verification similar to validity checking in a mathematical logic – Axioms – Rules of inference • Programmer attempts to find a proof using the axioms and the rules of inference • Manual proof discovery • Automated proof checking

Recently… • Combination of model checking and axiomatic verification – Iterated abstration and refinement Recently… • Combination of model checking and axiomatic verification – Iterated abstration and refinement




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