Automating Abstract Interpretation⋆
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Integrated Program Debugging, Verification, and Optimization Using Abstract Interpretation (And the Ciao System Preprocessor)
Integrated Program Debugging, Verification, and Optimization Using Abstract Interpretation (and The Ciao System Preprocessor) Manuel V. Hermenegildo a,b Germ´anPuebla a Francisco Bueno a Pedro L´opez-Garc´ıa a aDepartment of Computer Science, Technical University of Madrid (UPM) {herme,german,bueno,pedro.lopez}@fi.upm.es http://www.clip.dia.fi.upm.es/ bDepts. of Comp. Science and Electrical and Computer Eng., U. of New Mexico [email protected] – http://www.unm.edu/~herme Abstract The technique of Abstract Interpretation has allowed the development of very so- phisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development frame- work which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the pro- gram. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of valida- tion and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost). -
Abstract Interpretation and Abstract Domains with Special Attention to the Congruence Domain
Malardalen¨ University Master Thesis Abstract Interpretation and Abstract Domains with special attention to the congruence domain Stefan Bygde May 2006 Department of Computer Science and Electronics Malardalen¨ University Vaster¨ as,˚ Sweden Abstract This thesis is a survey on a framework for program analysis known as Abstract interpre- tation. Abstract interpretation uses abstract semantics to obtain important properties of programs. Different abstract semantics can be used in abstract interpretation, to obtain different properties. For instance there are semantics that spots upper and lower limits for the values of the variables of the program. These different semantics are called abstract domains and this thesis is meant to summarize different numerical abstract domains as well as give mathematical properties to them. The thesis also offers a small survey of free software libraries that implements abstract domains. Special attention will be given to the congruence domain. The congruence domain was implemented in a program analysis tool developed at M¨alardalen University. In the congruence domain the property ”variable x is always congruent to n modulo m” is obtained. Abstract operators for this domain are presented and new bit-operators are introduced. Contents 1 Introduction 4 1.1 Static analysis and WCET . ..................... 4 1.2 SWEET . ................................ 5 1.3 Motivation and results ......................... 7 1.4 Related work . ......................... 7 1.5 Outline . ................................ 7 2 Collecting semantics 8 2.1 Definitions ................................ 8 2.2 The transition system . ......................... 9 3 Abstract Interpretation 9 3.1 The idea of abstraction ......................... 10 3.2 Galois connections . ......................... 10 3.2.1 An example . ......................... 11 3.3 Relational and non-relational domains ................ -
Structure and Perspective: Philosophical Perplexity and Paradox Published: Pp
Structure and Perspective: Philosophical Perplexity and Paradox published: pp. 511-530 in M. L. Dalla Chiara et al. (eds.) Logic and Scientific Methods. Vol 1. Dordrecht: Kluwer, 1997. Bas C. van Fraassen, Princeton University 1. Science as representation ..................................................................................... 1 1.1 The philosophical consensus ca. 1900 .............................................................. 2 1.2 The problem of multiple geometries ................................................................. 3 1.3 Relativity of representation ............................................................................... 5 2. Structuralism, its initial (mis)fortunes ................................................................. 6 2.1 Russell's structuralist turn ................................................................................. 6 2.2 The collapse of structuralism? .......................................................................... 8 2.3 Putnam's model-theoretic argument -- a paradox? .......................................... 11 3. Structuralism: the semantic approach ............................................................... 15 3.1 Structural description of nature ....................................................................... 15 3.2 Adequacy to the phenomena ........................................................................... 16 3.3 Structuralism lost after all? ............................................................................. 18 3.4 Truth -
Static Program Analysis Via 3-Valued Logic
Static Program Analysis via 3-Valued Logic ¡ ¢ £ Thomas Reps , Mooly Sagiv , and Reinhard Wilhelm ¤ Comp. Sci. Dept., University of Wisconsin; [email protected] ¥ School of Comp. Sci., Tel Aviv University; [email protected] ¦ Informatik, Univ. des Saarlandes;[email protected] Abstract. This paper reviews the principles behind the paradigm of “abstract interpretation via § -valued logic,” discusses recent work to extend the approach, and summarizes on- going research aimed at overcoming remaining limitations on the ability to create program- analysis algorithms fully automatically. 1 Introduction Static analysis concerns techniques for obtaining information about the possible states that a program passes through during execution, without actually running the program on specific inputs. Instead, static-analysis techniques explore a program’s behavior for all possible inputs and all possible states that the program can reach. To make this feasible, the program is “run in the aggregate”—i.e., on abstract descriptors that repre- sent collections of many states. In the last few years, researchers have made important advances in applying static analysis in new kinds of program-analysis tools for identi- fying bugs and security vulnerabilities [1–7]. In these tools, static analysis provides a way in which properties of a program’s behavior can be verified (or, alternatively, ways in which bugs and security vulnerabilities can be detected). Static analysis is used to provide a safe answer to the question “Can the program reach a bad state?” Despite these successes, substantial challenges still remain. In particular, pointers and dynamically-allocated storage are features of all modern imperative programming languages, but their use is error-prone: ¨ Dereferencing NULL-valued pointers and accessing previously deallocated stor- age are two common programming mistakes. -
Design of Semantics by Abstract Interpretation
…/… Design of Semantics by Abstract Interpretation -- Abstraction of the relational into a nondeterministic Plotkin/- Smyth/Hoare denotational/functional semantics; -- Abstraction of the natural/demoniac relational into a determin istic denotational/functional semantics;Scott’ssemantics; Patrick COUSOT -- Abstraction of nondeterministic denotational semantics to weakest École Normale Supérieure precondition/strongest postcondition predicate transformer se DMI, 45, rue d’Ulm mantics; 75230 Paris cedex 05 Abstraction of predicate transformer semantics to à la Hoare France -- ax ;Programproofmethods; [email protected] iomatic semantics http://www.dmi.ens.fr/ cousot Extension to the λ-calculus. ˜ • MPI-Kolloquium, Max-Planck-Institut für Informatik, Saarbrücken, am Montag, dem 2. Juni 1997 um 14.15 Uhr 1 1 Extended version of the invited address at MFPS XIII, CMU, Pittsburgh, March 24, 1997 © P. Cousot 1 MPI-Kolloquium, Max-Planck-Institut für Informatik, Saarbrücken, 2. Juni 1997 © P. Cousot 3 MPI-Kolloquium, Max-Planck-Institut für Informatik, Saarbrücken, 2. Juni 1997 Content Application of abstract interpretation ideas to the design of formal semantics: Examples of Abstract Interpretations Examples of abstract interpretations; • Abstraction of fixpoint semantics; • -- Maximal trace semantics of nondeterministic transition systems; -- Abstraction of the trace into a natural/demoniac/angelic relational semantics; …/… © P. Cousot 2 MPI-Kolloquium, Max-Planck-Institut für Informatik, Saarbrücken, 2. Juni 1997 © P. Cousot 4 MPI-Kolloquium, -
Abstract Interpretation Based Program Testing
1 Abstract Interpretation Based Program Testing Patrick Cousot and Radhia Cousot Département d’informatique Laboratoire d’informatique École normale supérieure École polytechnique 45 rue d’Ulm 91128 Palaiseau cedex, France 75230 Paris cedex 05, France [email protected] [email protected] http://lix.polytechnique.fr/˜rcousot http://www.di.ens.fr/˜cousot Abstract— Every one can daily experiment that programs II. An informal introduction to abstract are bugged. Software bugs can have severe if not catas testing trophic consequences in computer-based safety critical ap plications. This impels the development of formal methods, Abstract testing is the verification that the abstract se whether manual, computer-assisted or automatic, for verify mantics of a program satisfies an abstract specification. ing that a program satisfies a specification. Among the auto matic formal methods, program static analysis can be used The origin is the abstract interpretation based static check to check for the absence of run-time errors. In this case the ing of safety properties [1], [2] such as array bound checking specification is provided by the semantics of the program and the absence of run-time errors which was extended to ming language in which the program is written. Abstract in terpretation provides a formal theory for approximating this liveness properties such as termination [3], [4]. semantics, which leads to completely automated tools where Consider for example, the factorial program (the random run-time bugs can be statically and safely classified as un assignment ? is equivalent to the reading of an input value reachable, certain, impossible or potential. We discuss the or the passing of an unknown but initialized parameter extension of these techniques to abstract testing where speci fications are provided by the programmers. -
Effectiveness of Mathematics in Empirical Science
The (reasonable) effectiveness of mathematics in empirical science Jairo José da Silva Universidade Estadual Paulista Júlio de Mesquita Filho, UNESP, Brazil e–mail: [email protected] ABSTRACT WORK TYPE I discuss here the pragmatic problem in the philosophy of mathematics, that is, Article the applicability of mathematics, particularly in empirical science, in its many variants. My point of depart is that all sciences are formal, descriptions of formal– ARTICLE HISTORY structural properties instantiated in their domain of interest regardless of their Received: material specificity. It is, then, possible and methodologically justified as far as 27–April–2018 science is concerned to substitute scientific domains proper by whatever domains Accepted: —mathematical domains in particular— whose formal structures bear relevant 30–November–2018 formal similarities with them. I also discuss the consequences to the ontology of mathematics and empirical science of this structuralist approach. ARTICLE LANGUAGE English KEYWORDS Philosophy of Mathematics Domains Formal Structures Ontology © Studia Humanitatis – Universidad de Salamanca 2018 NOTES ON CONTRIBUTOR Jairo José da Silva is a Professor of Mathematics (retired) at the State University of São Paulo and a Researcher at the National Council of Scientific and Technological Development (CNPq) of the Brazilian Ministry of Science and Technology. PhD in Mathematics at the University of California – Berkeley, USA, and a PhD in Philosophy at the Universidade Estadual de Campinas, Brazil. His main interests are the philosophy of formal and empirical sciences, phenomenology and the foundations of mathematics. He is co–author, together with Claire Ortiz Hill, of the book The Road Not Taken – On Husserl’s Philosophy of Logic and Mathematics (London: College Publications, 2013); and author of Mathematics and Its Applications. -
Abstract Interpretation of Programs for Model-Based Debugging
Abstract Interpretation of Programs for Model-Based Debugging Wolfgang Mayer Markus Stumptner Advanced Computing Research Centre University of South Australia [mayer,mst]@cs.unisa.edu.au Language Abstract Semantics Test-Cases Developing model-based automatic debugging strategies has been an active research area for sev- Program eral years. We present a model-based debug- Conformance Test Components ging approach that is based on Abstract Interpre- Fault Conflict sets tation, a technique borrowed from program analy- Assumptions sis. The Abstract Interpretation mechanism is inte- grated with a classical model-based reasoning en- MBSD Engine gine. We test the approach on sample programs and provide the first experimental comparison with earlier models used for debugging. The results Diagnoses show that the Abstract Interpretation based model provides more precise explanations than previous Figure 1: MBSD cycle models or standard non-model based approaches. 2 Model-based debugging 1 Introduction Model-based software debugging (MBSD) is an application of Model-based Diagnosis (MBD) [19] techniques to locat- Developing tools to support the software engineer in locating ing errors in computer programs. MBSD was first intro- bugs in programs has been an active research area during the duced by Console et. al. [6], with the goal of identifying last decades, as increasingly complex programs require more incorrect clauses in logic programs; the approach has since and more effort to understand and maintain them. Several dif- been extended to different programming languages, includ- ferent approaches have been developed, using syntactic and ing VHDL [10] a n d JAVA [21]. semantic properties of programs and languages. The basic principle of MBD is to compare a model,ade- This paper extends past research on model-based diagnosis scription of the correct behaviour of a system, to the observed of mainstream object oriented languages, with Java as con- behaviour of the system. -
Abstract Interpretation: a Unified Lattice Model for Static Analysis of Programs by Construction Or Approximation of Fixpoints
ABSTRACT INTERPRETATION : ‘A UNIFIED LATTICE MODEL FOR STATIC ANALYSIS OF PROGRAMS BY CONSTRUCTION OR APPROXIMATION OF FIXPOINTS Patrick Cousot*and Radhia Cousot** Laboratoire d’Informatique, U.S.M.G., BP. 53 38041 Grenoble cedex, France 1. Introduction Abstract program properties are modeled by a com– plete semilattice, Birkhoff[611. Elementary Pro- A program denotes computations in some universe of gram constructs are locally interpreted by order objects. Abstract interpretation of programs con– preserving functions which are used to associate sists in using that denotation to describe compu– a system of recursive equations with a program. The tations in another universe of abstract objects, program global properties are then defined as one so that the results of abstract execution give of the extreme fixpoints of that system, Tarski [55]. some information on the actual computations. An The abstraction process is defined in section 6. It intuitive example (which we borrow from Sintzoff is shown that the program properties obtained by 172]) is the rule of signs. The text ‘1515* 17 an abstract interpretation of a program are consis– may be understood to denote computations on the tent with those obtained by a more refined inter– abstract universe {(+), (-), (~)} where the se- pretation of that program. In particular, an ab– mantics of arithmetic operators is defined by the stract interpretation may be shown to be consistent rule of signs. The abstract execution -1515* 17 with the formal semantics of the language. Levels => -(+) * (+) e> (–) * (+) => (–), proves that of abstraction are formalized by showing that con- –1515 * 17 is a negative number. Abstract interpre– sistent abstract interpretations form a lattice tation is concerned by a particular underlying (section 7). -
Arxiv:1007.3250V1 [Cs.PL] 19 Jul 2010 Ple Opromhg-Adlwlvlotmztosand Optimizations Low-Level and High- Perform to Applied Ae Rpoesro the of Etc
Verification of Java Bytecode using Analysis and Transformation of Logic Programs E. Albert1, M. G´omez-Zamalloa1, L. Hubert2, and G. Puebla2 1 DSIC, Complutense University of Madrid, E-28040 Madrid, Spain 2 CLIP, Technical University of Madrid, E-28660 Boadilla del Monte, Madrid, Spain {elvira,mzamalloa,laurent,german}@clip.dia.fi.upm.es Abstract. State of the art analyzers in the Logic Programming (LP) paradigm are nowadays mature and sophisticated. They allow inferring a wide variety of global properties including termination, bounds on re- source consumption, etc. The aim of this work is to automatically transfer the power of such analysis tools for LP to the analysis and verification of Java bytecode (jvml). In order to achieve our goal, we rely on well-known techniques for meta-programming and program specialization. More pre- cisely, we propose to partially evaluate a jvml interpreter implemented in LP together with (an LP representation of) a jvml program and then analyze the residual program. Interestingly, at least for the examples we have studied, our approach produces very simple LP representations of the original jvml programs. This can be seen as a decompilation from jvml to high-level LP source. By reasoning about such residual programs, we can automatically prove in the CiaoPP system some non-trivial prop- erties of jvml programs such as termination, run-time error freeness and infer bounds on its resource consumption. We are not aware of any other system which is able to verify such advanced properties of Java bytecode. 1 Introduction Verifying programs in the (Constraint) Logic Programming paradigm —(C)LP— offers a good number of advantages, an important one being the maturity and sophistication of the analysis tools available for it. -
Verification by Abstract Interpretation
Verification by Abstract Interpretation Patrick Cousot École normale supérieure, Département d’informatique 45 rue d’Ulm, 75230 Paris cedex 05, France [email protected], www.di.ens.fr/~cousot Dedicated to Zohar Manna, for his 26th birthday. Abstract. Abstract interpretation theory formalizes the idea of abstrac- tion of mathematical structures, in particular those involved in the spec- ification of properties and proof methods of computer systems. Verifica- tion by abstract interpretation is illustrated on the particular cases of predicate abstraction, which is revisited to handle infinitary abstractions, and on the new parametric predicate abstraction. 1 Introduction Abstract interpretation theory [7,8,9,11,13] formalizes the idea of abstraction of mathematical structures, in particular those involved in the specification of properties and proof methods of computer systems. Verification by abstract interpretation is illustrated on the particular cases of predicate abstraction [4,15,19] (where the finitary program-specific ground atomic propositional components of inductive invariants have to be provided) which is revisited (in that it is derived by systematic approximation of the con- crete semantics of a programming language using an infinitary abstraction) and on the new parametric predicate abstraction, a program-independent generaliza- tion (where parameterized infinitary predicates are automatically combined by reduction and instantiated to particular programs by approximation). 2 Elements of Abstract Interpretation Let us first recall a few elements of abstract interpretation from [7,9,11]. 2.1 Properties and Their Abstraction. Given a set Σ of objects (such as program states, execution traces, etc.), we represent properties P of objects s ∈ Σ as sets of objects P ∈ ℘(Σ) (which have the considered property). -
Foundations for Mathematical Structuralism This Philosophical View Comes in a Variety of Forms
Uri Nodelman and Edward N. Zalta 2 1 Introduction Mathematical structuralism is the view that pure mathematics is about 1 ∗ abstract structure or structures (see, e.g., Hellman 1989, Shapiro 1997). Foundations for Mathematical Structuralism This philosophical view comes in a variety of forms. In this paper, we investigate, and restrict our use of the term `structuralism' to the form that acknowledges that abstract structures exist, that the pure objects of Uri Nodelman mathematics are in some sense elements of, or places in, those structures, and and that there is nothing more to the pure objects of mathematics than Edward N. Zalta can be described by the basic relations of their corresponding structure (e.g., Dedekind 1888 [1963], Resnik 1981, 1997, Parsons 1990, and Shapiro Center for the Study of Language and Information 1997).2 We shall not suppose that structures are sets nor assume any Stanford University set theory; our goal is to give an analysis of mathematics that doesn't presuppose any mathematics. Our work is motivated by two insights. First, as we discuss in Section 2.1, abstract objects are connected to the properties that define them in a different way than ordinary objects are connected to the properties they bear. Second, as we discuss in Section 3.1, theorems and truths about abstract relations are more important in Abstract defining mathematical structures than mathematical entities. Recently, the literature on structuralism has centered on a variety of questions and problems. These issues arise, in part, because the philo- sophical view has not been given proper, mathematics-free theoretical We investigate the form of mathematical structuralism that ac- foundations.3 We shall show how to view mathematical structures as knowledges the existence of structures and their distinctive struc- tural elements.