Using Dafny, an Automatic Program Verifier
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A Study of Computing in Education and Ways to Enhance Students’ Perceptions and Understanding of Computing
SCHOOL OF DESIGN, ENGINEERING & COMPUTING MSc Enterprise Information Systems September 2013 Computing in Education: A study of computing in education and ways to enhance students’ perceptions and understanding of computing by Paul Albinson BSc (Hons), FdSc, MBCS Page 1 of 166 Abstract There is a huge demand for computing skills in industry due to computing becoming ubiquitous and essential for modern life. Yet despite this, industry struggles to find employees with suitable computing skills and similarly Further and Higher Education institutions have observed a lack of interest in their computing courses in recent years. This study looks at possible reasons for this lack of interest in computing, how computing is taught in education and ways to improve students’ perceptions and understanding of computing. It focuses around a case study of a university outreach event for secondary schools which investigated how interactive teaching methods can be used to enhance students’ perceptions and understanding of computing and to increase their computing knowledge. It includes the use of physical computing and was designed to make computing fun, motivational and relevant, and to provide examples of real-world applications. Surveys were used before and after the event to understand what students’ impressions and knowledge of computing is and to see if the event improved these. Observations were also used to see how well the students handled the event’s content and whether they appeared to enjoy and understand it. Results from the case study indicate that interactive teaching methods enhance computing education, and physical computing with electronics can enhance lessons and show the relevance of computing with examples of real-world applications, and can be fun and motivational. -
Verification of Concurrent Programs in Dafny
Bachelor’s Degree in Informatics Engineering Computation Bachelor’s End Project Verification of Concurrent Programs in Dafny Author Jon Mediero Iturrioz 2017 Abstract This report documents the Bachelor’s End Project of Jon Mediero Iturrioz for the Bachelor in Informatics Engineering of the UPV/EHU. The project was made under the supervision of Francisca Lucio Carrasco. The project belongs to the domain of formal methods. In the project a methodology to prove the correctness of concurrent programs called Local Rely-Guarantee reasoning is analyzed. Afterwards, the methodology is implemented over Dagny automatic program verification tool, which was introduced to me in the Formal Methods for Software Devel- opments optional course of the fourth year of the bachelor. In addition to Local Rely-Guarantee reasoning, in the report Hoare logic, Separation logic and Variables as Resource logic are explained, in order to have a good foundation to understand the new methodology. Finally, the Dafny implementation is explained, and some examples are presented. i Acknowledgments First of all, I would like to thank to my supervisor, Paqui Lucio Carrasco, for all the help and orientation she has offered me during the project. Lastly, but not least, I would also like to thank my parents, who had supported me through all the stressful months while I was working in the project. iii Contents Abstracti Contentsv 1 Introduction1 1.1 Objectives..................................3 1.2 Work plan..................................3 1.3 Content...................................4 2 Foundations5 2.1 Hoare Logic.................................5 2.1.1 Assertions..............................5 2.1.2 Programming language.......................7 2.1.3 Inference rules...........................9 2.1.4 Recursion............................. -
Microsoft Small Basic
Katolickie Gimnazjum i Liceum Ogólnokształcące im. Jana Pawła II w Łodzi Microsoft Small Basic Translated by Anna Wilk (klasa 2a 2009/2010) Wstęp Small Basic i programowanie Programowanie komputerowe jest zdefiniowane jako proces tworzenia oprogramowania komputerowego używającego języki programowania. Tylko jak mówimy i rozumiemy Anglików albo Hiszpana albo Francuzów, komputery mogą zrozumieć programy napisane w pewnych językach. To tzw. języki programowania. Na początku było niewiele takich języków, były proste i zrozumiałe. Z czasem oprogramowanie i komputery stały się bardziej skomplikowane i wyszukane, więc języki programowania również musiały ewaluować. W efekcie są to trudne do zrozumienia metody programowania, szczególnie dla początkujących. Small Basic przedstawia programowanie w przyjemny, niezwykle łatwy i ciekawy sposób, usuwa bariery, by każdy mógł wkroczyć w świat programowania. Small Basic - Środowisko Zacznijmy od przedstawienia interfejsu Small Basic’a i poruszania się w nim. Po pierwszym uruchomieniu zobaczycie właśnie takie okno: Obrazek 1 To jest Small Basic Środowisko, gdzie napiszemy nasze programy. Opiszemy każdy element zaznaczony numerem. 1. Edytor(1) to miejsce, w którym piszemy program. Otwierając przykładowy program lub poprzednio zapisany, pojawi się on w tym oknie. Możesz otworzyć i korzystać z kilku edytorów na raz. 2. Pasek narzędzi(2) nadaje komendy w edytorze. O różnych zadaniach nauczymy się później. 3. Powierchnia pod edytorem (3) to obszar na wszystkie okna edycji. Nasz pierwszy Program Już znasz podstawy, więc zacznijmy programować. Wpiszmy poniższą linijkę do edytora. TextWindow.WriteLine(„Hello World”) Jeżeli wszystko zostało wpisane poprawnie, to ujżymy coś takiego: Pierwszy Program Teraz, kiedy już napisaliśmy nasz pierwszy program, włączmy go. Możemy to zrobić klikajać na przycisk RUN w pasku narzędzi lub naciskając F5. -
Microsoft Small Basic
Microsoft Small Basic An introduction to Programming Chapter 1 An Introduction Small Basic and Programming Computer Programming is defined as the process of creating computer software using programming languages. Just like we speak and understand English or Spanish or French, computers can understand programs written in certain languages. These are called programming languages. In the beginning there were just a few programming languages and they were really easy to learn and comprehend. But as computers and software became more and more sophisticated, programming languages evolved fast, gathering more complex concepts along the way. As a result most modern programming languages and their concepts are pretty challenging to grasp by a beginner. This fact has started discouraging people from learning or attempting computer programming. Small Basic is a programming language that is designed to make programming extremely easy, approachable and fun for beginners. Small Basic’s intention is to bring down the barrier and serve as a stepping stone to the amazing world of computer programming. The Small Basic Environment Let us start with a quick introduction to the Small Basic Environment. When you first launch SmallBasic, you will see a window that looks like the following figure. Figure 1 - The Small Basic Environment This is the Small Basic Environment, where we’ll write and run our Small Basic programs. This environment has several distinct elements which are identified by numbers. The Editor, identified by [1] is where we will write our Small Basic programs. When you open a sample program or a previously saved program, it will show up on this editor. -
Transforming Event-B Models to Dafny Contracts
Electronic Communications of the EASST Volume XXX (2015) Proceedings of the 15th International Workshop on Automated Verification of Critical Systems (AVoCS 2015) Transforming Event-B Models to Dafny Contracts Mohammadsadegh Dalvandi, Michael Butler, Abdolbaghi Rezazadeh 15 pages Guest Editors: Gudmund Grov, Andrew Ireland Managing Editors: Tiziana Margaria, Julia Padberg, Gabriele Taentzer ECEASST Home Page: http://www.easst.org/eceasst/ ISSN 1863-2122 ECEASST Transforming Event-B Models to Dafny Contracts Mohammadsadegh Dalvandi1, Michael Butler2, Abdolbaghi Rezazadeh3 School of Electronic & Computer Science, University of Southampton 1 2 3 md5g11,mjb,[email protected] Abstract: Our work aims to build a bridge between constructive (top-down) and analytical (bottom-up) approaches to software verification. This paper presents a tool-supported method for linking two existing verification methods: Event-B (con- structive) and Dafny (analytical). This method combines Event-B abstraction and refinement with the code-level verification features of Dafny. The link transforms Event-B models to Dafny contracts by providing a framework in which Event-B models can be implemented correctly. The paper presents a method for transforma- tion of Event-B models of abstract data types to Dafny contracts. Also a prototype tool implementing the transformation method is outlined. The paper also defines and proves a formal link between property verification in Event-B and Dafny. Our approach is illustrated with a small case study. Keywords: Formal Methods, Hoare Logic, Program Verification, Event-B, Dafny 1 Introduction Various formal methods communities [CW96, HMLS09, LAB+06] have suggested that no single formal method can cover all aspects of a verification problem therefore engineering bridges be- tween complementary verification tools to enable their effective interoperability may increase the verification capabilities of verification tools. -
Verification and Specification of Concurrent Programs
Verification and Specification of Concurrent Programs Leslie Lamport 16 November 1993 To appear in the proceedings of a REX Workshop held in The Netherlands in June, 1993. Verification and Specification of Concurrent Programs Leslie Lamport Digital Equipment Corporation Systems Research Center Abstract. I explore the history of, and lessons learned from, eighteen years of assertional methods for specifying and verifying concurrent pro- grams. I then propose a Utopian future in which mathematics prevails. Keywords. Assertional methods, fairness, formal methods, mathemat- ics, Owicki-Gries method, temporal logic, TLA. Table of Contents 1 A Brief and Rather Biased History of State-Based Methods for Verifying Concurrent Systems .................. 2 1.1 From Floyd to Owicki and Gries, and Beyond ........... 2 1.2Temporal Logic ............................ 4 1.3 Unity ................................. 5 2 An Even Briefer and More Biased History of State-Based Specification Methods for Concurrent Systems ......... 6 2.1 Axiomatic Specifications ....................... 6 2.2 Operational Specifications ...................... 7 2.3 Finite-State Methods ........................ 8 3 What We Have Learned ........................ 8 3.1 Not Sequential vs. Concurrent, but Functional vs. Reactive ... 8 3.2Invariance Under Stuttering ..................... 8 3.3 The Definitions of Safety and Liveness ............... 9 3.4 Fairness is Machine Closure ..................... 10 3.5 Hiding is Existential Quantification ................ 10 3.6 Specification Methods that Don’t Work .............. 11 3.7 Specification Methods that Work for the Wrong Reason ..... 12 4 Other Methods ............................. 14 5 A Brief Advertisement for My Approach to State-Based Ver- ification and Specification of Concurrent Systems ....... 16 5.1 The Power of Formal Mathematics ................. 16 5.2Specifying Programs with Mathematical Formulas ........ 17 5.3 TLA ................................. -
Specifying Loops with Contracts Reasoning About Loops As Recursive Procedures
Chair for Software Systems Institute for Informatics LMU Munich Bachelor Thesis in Computer Science: Specifying Loops With Contracts Reasoning about loops as recursive procedures Gregor Cassian Alexandru August 8, 2019 I dedicate this work to the memory of Prof. Martin Hofmann, who was an amazing teacher and inspiration, and left us all too soon. Hiermit versichere ich, dass ich die vorliegende Bachelorarbeit selbstständig verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet habe. ............................................... (Unterschrift des Kandidaten) München, den 8. August 2019 5 Abstract Recursive procedures can be inductively verified to fulfill some contract, by assuming that contract for recursive calls. Since loops correspond essentially to linear recursion, they ought to be verifiable in an analogous manner. Rules that allow this have been proposed, but are incomplete in some aspect, or do not lend themselves to straight- forward implementation. We propose some implementation-oriented derivatives of the existing verification rules and further illustrate the advantages of contract-based loop specification by means of examples. Contents 1 Introduction 11 2 Motivating Example 12 2.1 Verification using an Invariant . 12 2.2 Using a local Recursive Procedure . 13 2.3 Comparison . 15 3 Preliminaries 16 4 Predicate transformer semantics 17 4.1 Prerequisites . 17 4.2 Loop specification rule for weakest precondition . 20 4.3 Soundness proof . 20 4.4 Context-aware rule . 22 4.5 Rules in strongest postcondition . 22 5 Rules in Hoare Logic 24 5.1 Preliminaries . 24 5.2 Loop specification rule in Hoare logic . 25 6 Implementation 26 7 Example Application to Textbook Algorithms 29 7.1 Euclid’s algorithm . -
Dafny: an Automatic Program Verifier for Functional Correctness K
Dafny: An Automatic Program Verifier for Functional Correctness K. Rustan M. Leino Microsoft Research [email protected] Abstract Traditionally, the full verification of a program’s functional correctness has been obtained with pen and paper or with interactive proof assistants, whereas only reduced verification tasks, such as ex- tended static checking, have enjoyed the automation offered by satisfiability-modulo-theories (SMT) solvers. More recently, powerful SMT solvers and well-designed program verifiers are starting to break that tradition, thus reducing the effort involved in doing full verification. This paper gives a tour of the language and verifier Dafny, which has been used to verify the functional correctness of a number of challenging pointer-based programs. The paper describes the features incorporated in Dafny, illustrating their use by small examples and giving a taste of how they are coded for an SMT solver. As a larger case study, the paper shows the full functional specification of the Schorr-Waite algorithm in Dafny. 0 Introduction Applications of program verification technology fall into a spectrum of assurance levels, at one extreme proving that the program lives up to its functional specification (e.g., [8, 23, 28]), at the other extreme just finding some likely bugs (e.g., [19, 24]). Traditionally, program verifiers at the high end of the spectrum have used interactive proof assistants, which require the user to have a high degree of prover expertise, invoking tactics or guiding the tool through its various symbolic manipulations. Because they limit which program properties they reason about, tools at the low end of the spectrum have been able to take advantage of satisfiability-modulo-theories (SMT) solvers, which offer some fixed set of automatic decision procedures [18, 5]. -
KAT and Hoare Logic
Introduction to Kleene Algebra Lecture 14 CS786 Spring 2004 March 15, 2004 KAT and Hoare Logic In this lecture and the next we show that KAT subsumes propositional Hoare logic (PHL). Thus the specialized syntax and deductive apparatus of Hoare logic are inessential and can be replaced by simple equational reasoning. Moreover, all relationally valid Hoare-style inference rules are derivable in KAT (this is false for PHL). The results of this lecture are from [8, 7]. In a future lecture we will show that deciding the relational validity of such rules is PSPACE-complete. Hoare logic, introduced by C. A. R. Hoare in 1969 [6], was the first formal system for the specification and verification of well-structured programs. This pioneering work initiated the field of program correctness and inspired dozens of technical articles [2, 1, 3]. For this achievement among others, Hoare received the Turing Award in 1980. A comprehensive introduction to Hoare logic can be found in [3]. Hoare logic uses a specialized syntax involving partial correctness assertions (PCAs) of the form {b} p {c} and a deductive apparatus consisting of a system of specialized rules of inference. Under certain conditions, these rules are relatively complete [2]; essentially, the propositional fragment of the logic can be used to reduce partial correctness assertions to static assertions about the underlying domain of computation. The propositional fragment of Hoare logic, called propositional Hoare logic (PHL), is subsumed by KAT. The reduction transforms PCAs to ordinary equations and the specialized rules of inference to equational implications (universal Horn formulas). The transformed rules are all derivable in KAT by pure equational reasoning. -
Symbolic Execution
Symbolic Execution CS252r Spring 2011 Contains content from slides by Jeff Foster Static analysis •Static analysis allows us to reason about all possible executions of a program •Gives assurance about any execution, prior to deployment •Lots of interesting static analysis ideas and tools •But difficult for developers to use •Commercial tools spend a lot of effort dealing with developer confusion, false positives, etc. • See A Few Billion Lines of Code Later: Using Static Analysis to Find Bugs in the Real World in CACM 53(2), 2010 ‣http://bit.ly/aedM3k © 2011 Stephen Chong, Harvard University 2 One issue is abstraction •Abstraction lets us scale and model all possible runs •But must be conservative •Try to balance precision and scalability • Flow-sensitive, context-sensitive, path-sensitivity, … •And static analysis abstractions do not cleanly match developer abstractions © 2011 Stephen Chong, Harvard University 3 Testing •Fits well with developer intuitions •In practice, most common form of bug-detection •But each test explores only one possible execution of the system •Hopefully, test cases generalize © 2011 Stephen Chong, Harvard University 4 Symbolic execution •King, CACM 1976. •Key idea: generalize testing by using unknown symbolic variables in evaluation •Symbolic executor executes program, tracking symbolic state. •If execution path depends on unknown, we fork symbolic executor •at least, conceptually © 2011 Stephen Chong, Harvard University 5 SymbolicSymbolicSymbolic Execution Execution execution ExampleExample example WhyWhy Is Is This This Possible? Possible? x=0, y=0, z=0 • There are very powerful SMT/SAT solvers today 1.1.intint a a= =α α, b, b= = β β, ,c c = = γ γ;; x=0, y=0, z=0 • There are very powerful SMT/SAT solvers today 2.2. -
Cartesian Hoare Logic for Verifying K-Safety Properties ∗
Cartesian Hoare Logic for Verifying k-Safety Properties ∗ Marcelo Sousa Isil Dillig University of Oxford, UK The University of Texas at Austin, USA [email protected] [email protected] Abstract produce outputs consistent with Ψ. Hence, a valid Hoare Unlike safety properties which require the absence of a “bad" triple states which input-output pairs are feasible in a single, program trace, k-safety properties stipulate the absence of but arbitrary, execution of S. a “bad" interaction between k traces. Examples of k-safety However, some important functional correctness proper- properties include transitivity, associativity, anti-symmetry, ties require reasoning about the relationship between multiple and monotonicity. This paper presents a sound and relatively program executions. As a simple example, consider deter- complete calculus, called Cartesian Hoare Logic (CHL), for minism, which requires 8x; y: x = y ) f(x) = f(y). This verifying k-safety properties. Our program logic is designed property is not a standard safety property because it cannot with automation and scalability in mind, allowing us to be violated by any individual execution trace. Instead, de- formulate a verification algorithm that automates reasoning terminism is a so-called 2-safety hyperproperty [10] since in CHL. We have implemented our verification algorithm in a we need two execution traces to establish its violation. In general, a k-safety (hyper-)property requires reasoning about fully automated tool called DESCARTES, which can be used to analyze any k-safety property of Java programs. We have relationships between k different execution traces. Even though there has been some work on verifying 2- used DESCARTES to analyze user-defined relational operators safety properties in the context of secure information flow [1, and demonstrate that DESCARTES is effective at verifying (or finding violations of) multiple k-safety properties. -
Hoare Logic: Proving Programs Correct
Hoare Logic: Proving Programs Correct 17-654/17-765 Analysis of Software Artifacts Jonathan Aldrich Reading: C.A.R. Hoare, An Axiomatic Basis for Computer Programming Some presentation ideas from a lecture by K. Rustan M. Leino Testing and Proofs • Testing • Proofs • Observable properties • Any program property • Verify program for one • Verify program for all execution executions • Manual development • Manual development with automated with automated proof regression checkers • Most practical approach • May be practical for now small programs in 10-20 years • So why learn about proofs if they aren’t practical? • Proofs tell us how to think about program correctness • Important for development, inspection • Foundation for static analysis tools • These are just simple, automated theorem provers • Many are practical today! Analysis of Software Artifacts - 3 Spring 2006 1 How would you argue that this program is correct? float sum(float *array, int length) { float sum = 0.0; int i = 0; while (i < length) { sum = sum + array[i]; i = i + 1; } return sum; } Analysis of Software Artifacts - 4 Spring 2006 Function Specifications • Predicate: a boolean function over program state • i.e. an expression that returns a boolean • We often use mathematical symbols as well as program text • Examples • x=3 • y > x • (x ≠ 0) ⇒ (y+z = w) Σ • s = (i ∈1..n) a[i] • ∀i∈1..n . a[i] > a[i-1] • true Analysis of Software Artifacts - 5 Spring 2006 2 Function Specifications • Contract between client and implementation • Precondition: • A predicate describing the condition the function relies on for correct operation • Postcondition: • A predicate describing the condition the function establishes after correctly running • Correctness with respect to the specification • If the client of a function fulfills the function’s precondition, the function will execute to completion and when it terminates, the postcondition will be true • What does the implementation have to fulfill if the client violates the precondition? • A: Nothing.