Course Outline

Contents

• Course Details
• Course Summary
• Assumed Knowledge
• Student Learning Outcomes
• Teaching Strategies
• Student Conduct
• Assessment
• Resources for Students
• Course Evaluation and Development

Course Details

Course Code	COMP3153
Course Title	Algorithmic Verification
Convenor	Paul Hunter
Admin	Paul Hunter
Classes	Lectures : Monday 10:00-12:00 (wks 1-5, 7-10) [Ainsworth 202]; Wednesday 10:00-12:00 (wks 1-5, 7-10) [OShane G05] Tutorials : Timetable for all classes
Consultations	Thursdays, 8:30pm
Units of Credit	6
Course Website	http://cse.unsw.edu.au/~cs3153/
Handbook Entry	http://www.handbook.unsw.edu.au/undergraduate/courses/current/COMP3153.html

Course Description

It is virtually impossible to guarantee correctness of a system, and in turn the absence of bugs by standard software engineering practice such as code review, systematic testing and good software design alone. The complexity of systems is typically too high to be manageable by informal reasoning or reasoning that is not tool supported. The formal methods community has developed various rigorous, mathematically sound techniques and tools that allow the automatic analysis of systems and software. The application of these fully automatic techniques is typically called algorithmic verification. The course will describe several automatic verification techniques, the algorithms they are based on, and the tools that support them. We will discuss examples to which the techniques have been applied, and provide experience with the use of several state-of-the-art analysis tools.

The topics covered by the lectures will educate students on the foundations of automata theory and temporal logics, LTL and CTL model checking techniques and model checking tools, the application of static analysis techniques to program verification, and modern advanced verification techniques for timed and probabilistic systems.

Assumed Knowledge

Students need to have successfully completed the core programming, algorithm, and discrete mathematics courses.

The course makes use of a number of discrete mathematics concepts. Students may find the course very difficult without MATH1081 or equivalent discrete mathematics background.

Completion, or undertaking of automata and/or logic courses such as COMP4141, COMP2111, COMP6721 or COMP4161 are desirable for getting the most out of the course, but not essential.

Course Learning Outcomes

After completing this course, students should:

• Understand foundations of automata theory and temporal logics
• Compare and contrast different LTL and CTL model checking techniques and model checking tools
• Apply modern LTL and CTL model checking tools to verification tasks
• Compare and contrast different static analysis techniques for program verification
• Understand modern advanced verification techniques for timed systems
• Develop formal models of software systems, amenable to automatic verification

Teaching Strategies

The learning focus in this course is primarily on lectures, tutorials and homework assignments. While marks are assigned to the homework, their primary purpose is to give you concrete tasks with deadlines to help you structure your learning.

Lectures

Each week, two 2-hour lectures will introduce you to new material, which is being reinforced and practised in tutorials and assignments. The course draws on several textbooks for material, listed later in this document. More reading material covering specific topics will be identified throughout the course. Students are required to study reading material as advised during the lecture and/or on the course web page.

Tutorials

Tutorials supplement the learning of the material covered in lectures through class-based discussion of ideas and concepts stimulated by staff, students and problem sets. In order to get the most out of these discussions, it is expected that you will have attempted the problem sets prior to tutorials and have identified areas of improvement.

Attendance at all tutorials is expected for this course.

Homework assignments

Formative weekly assessment tasks reinforce the learning of topics covered in lectures and tutorials. The tasks are a combination of theory-based problem sets and practical tasks aimed at familiarising you with the model-checking tools introduced in this course. Students are expected to complete these, with ongoing feedback from their tutors, in a timely manner.

Course Schedule

Following is a tentative schedule of topics covered in the course.

Week	Topics
Week 1	Background, logic, automata
Week 2	Model checking, Safety & Liveness
Week 3	Tool: Spin
Week 4	Simulation & Bisimulation
Week 5	Verification games
Week 6	Flex week
Week 7	Static Analysis
Week 8	Symbolic Model Checking
Week 9	Binary Decision Diagrams
Week 10	Timed automata and languages

Student Conduct

The Student Code of Conduct ( Information , Policy ) sets out what the University expects from students as members of the UNSW community. As well as the learning, teaching and research environment, the University aims to provide an environment that enables students to achieve their full potential and to provide an experience consistent with the University's values and guiding principles. A condition of enrolment is that students inform themselves of the University's rules and policies affecting them, and conduct themselves accordingly.

In particular, students have the responsibility to observe standards of equity and respect in dealing with every member of the University community. This applies to all activities on UNSW premises and all external activities related to study and research. This includes behaviour in person as well as behaviour on social media, for example Facebook groups set up for the purpose of discussing UNSW courses or course work. Behaviour that is considered in breach of the Student Code Policy as discriminatory, sexually inappropriate, bullying, harassing, invading another's privacy or causing any person to fear for their personal safety is serious misconduct and can lead to severe penalties, including suspension or exclusion from UNSW.

If you have any concerns, you may raise them with your lecturer, or approach the School Ethics Officer , Grievance Officer , or one of the student representatives.

Plagiarism is defined as using the words or ideas of others and presenting them as your own. UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:

• Plagiarism and Academic Integrity
• UNSW Plagiarism Procedure

Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism. In particular, you are also responsible that your assignment files are not accessible by anyone but you by setting the correct permissions in your CSE directory and code repository, if using. Note also that plagiarism includes paying or asking another person to do a piece of work for you and then submitting it as your own work.

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW staff and students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

If you haven't done so yet, please take the time to read the full text of

• UNSW's policy regarding academic honesty and plagiarism

The pages below describe the policies and procedures in more detail:

• Student Code Policy
• Student Misconduct Procedure
• Plagiarism Policy Statement
• Plagiarism Procedure

You should also read the following page which describes your rights and responsibilities in the CSE context:

• Essential Advice for CSE Students

Assessment

The final grade for this course will be determined from the assessible components of this course:

• 50%: Weekly assessment tasks [formative]
• 50%: FInal exam [summative]

Weekly assessment tasks

The weekly assessment tasks will be made available via the formatif system. With formative assessments, the students are encouraged to complete the tasks to a satisfactory level with ongoing feedback and guidance from their tutors and lecturer. At the end of term students construct a portfolio that reflects on their achievements. The final grade for this component will be determined by the quality and quantity of successfully completed tasks as demonstrated by this portfolio.

Tasks will consist of a combination of theoretical problem sets and practical exercises and will predominantly cover the material of the previous week's lectures.

Final exam

The final exam for this course will be a take-home exam which students must complete independently. Students must achieve a minimum of 40% on this assessment piece in order to pass the course.

Resources for Students

Recommended Textbooks

• Christel Baier and Joost-Pieter Katoen. Principles of model checking . MIT Press, 2008. ISBN 978-0-262-02649-9
• Edmund Clarke, Orna Grumberg and Doron Peled. Model Checking . MIT Press, 2000.
• Michael Huth and Mark Ryan. Logic in Computer Science (2nd edition) . Cambridge University Press, 2004.
• Beatrice Berard et al. Systems and Software Verification: Model-Checking Techniques and Tools . Springer, 2001

Further Reading

• Rajeev Alur. Techniques for Automatic Verification of Real-Time Systems . PhD thesis, Stanford University, 1991
• Thomas Ball, Vladimir Levin, Sriram K. Rajamani. A decade of software model checking with SLAM . Communication of the ACM 54(7):68-76, 2011.
• Armin Biere, Marijn Heule, Hans van Maaren, Toby Walsh. Handbook of Satisfiability . Frontiers in Artificial Intelligence and Applications 185, IOS Press, 2009.
• Edmund Clarke, Daniel Kroening, Natasha Sharygina. Predicate Abstraction of ANSI-C Programs Using SAT Formal Methods in System Design , 25, 105—127, Kluwer Academic Publishers, 2004.
• Edmund Clarke, Orna Grumberg, Somesh Jha, Yuan Lu, and Helmut Veith. Counterexample-guided abstraction refinement . In Computer Aided Verification, pages 154Ð169, 2000.
• Dexter Kozen. Automata and Computability . Springer, 1997. ISBN 978-0-387-94907-9
• Flemming Nielson, Hanne Riis Nielson and Chris Hankin. Principles of Program Analysis . Springer, 1999.
• Michael Sipser. Introduction to the Theory of Computation (3rd edition) . Cengage Learning, 2013. ISBN-13: 978-1-133-18781-3

Verification tools

• The nuXmv model checker
• The SPIN model checker
• The CBMC model checker
• The UPPAAL real-time model checker

Course Evaluation and Development

This course is being continuously improved and we will conduct a survey at the end of session to obtain feedback on the quality of the various course components. Your participation in the survey will be greatly appreciated.

Feedback from last year's myExperience report indicates that students would prefer more feedback throughout the term. We will address this by changing the assessment structure to a formative process.