17 research outputs found

    A Logical Product Approach to Zonotope Intersection

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    We define and study a new abstract domain which is a fine-grained combination of zonotopes with polyhedric domains such as the interval, octagon, linear templates or polyhedron domain. While abstract transfer functions are still rather inexpensive and accurate even for interpreting non-linear computations, we are able to also interpret tests (i.e. intersections) efficiently. This fixes a known drawback of zonotopic methods, as used for reachability analysis for hybrid sys- tems as well as for invariant generation in abstract interpretation: intersection of zonotopes are not always zonotopes, and there is not even a best zonotopic over-approximation of the intersection. We describe some examples and an im- plementation of our method in the APRON library, and discuss some further in- teresting combinations of zonotopes with non-linear or non-convex domains such as quadratic templates and maxplus polyhedra

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    This paper presents Aligators, a tool for the generation of universally quantified array invariants. Aligators leverages recurrence solving and algebraic techniques to carry out inductive reasoning over array content. The Aligators’ loop extraction module allows treatment of multi-path loops by exploiting their commutativity and serializability properties. Our experience in applying Aligators on a collection of loops from open source software projects indicates the applicability of recurrence and algebraic solving techniques for reasoning about arrays

    Automatic Synthesis of Logical Models for Order-Sorted First-Order Theories

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    [EN] In program analysis, the synthesis of models of logical theories representing the program semantics is often useful to prove program properties. We use order-sorted first- order logic as an appropriate framework to describe the semantics and properties of programs as given theories. Then we investigate the automatic synthesis of models for such theories. We use convex polytopic domains as a flexible approach to associate different domains to different sorts. We introduce a framework for the piecewise definition of functions and predicates. We develop its use with linear expressions (in a wide sense, including linear transformations represented as matrices) and inequalities to specify functions and predicates. In this way, algorithms and tools from linear algebra and arithmetic constraint solving (e.g., SMT) can be used as a backend for an efficient implementation.Partially supported by the EU (FEDER), projects TIN2015-69175-C4-1-R, and GV PROMETEOII/2015/ 013. R. Gutiérrez also supported by Juan de la Cierva Fellowship JCI-2012-13528.Lucas Alba, S.; Gutiérrez Gil, R. (2018). Automatic Synthesis of Logical Models for Order-Sorted First-Order Theories. Journal of Automated Reasoning. 60(4):465-501. https://doi.org/10.1007/s10817-017-9419-3S465501604Alarcón, B., Gutiérrez, R., Lucas, S., Navarro-Marset, R.: Proving termination properties with MU-TERM. In: Proceedings of AMAST’10. LNCS, vol. 6486, pp. 201–208 (2011)Alarcón, B., Lucas, S., Navarro-Marset, R.: Using matrix interpretations over the reals in proofs of termination. In: Proceedings of PROLE’09, pp. 255–264 (2009)Albert, E., Genaim, S., Gutiérrez, R.: A Transformational Approach to Resource Analysis with Typed-Norms. Revised Selected Papers from LOPSTR’13. LNCS, vol. 8901, pp 38–53 (2013)de Angelis, E., Fioravante, F., Pettorossi, A., Proietti, M.: Proving correctness of imperative programs by linearizing constrained Horn clauses. Theory Pract. Log. 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    Abstract Interpretation as Automated Deduction

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    International audienceAlgorithmic deduction and abstract interpretation are two widely used and successful approaches to implementing program veri-fiers. A major impediment to combining these approaches is that their mathematical foundations and implementation approaches are fundamentally different. This paper presents a new, logical perspective on abstract interpreters that perform reachability analysis using non-relational domains. We encode reachability of a location in a control-flow graph as satisfiability in a monadic, second-order logic parameterized by a first-order theory. We show that three components of an abstract interpreter, the lattice, transformers and iteration algorithm, represent a first-order, substructural theory, parametric deduction and abduction in that theory, and second-order constraint propagation

    Generic Combination of Heap and Value Analyses in Abstract Interpretation

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    Abstract. Abstract interpretation has been widely applied to approx-imate data structures and (usually numerical) value information. One needs to combine them to effectively apply static analysis to real software. Nevertheless, they have been studied mainly as orthogonal problems so far. In this context, we introduce a generic framework that, given a heap and a value analysis, combines them, and we formally prove its soundness. The heap analysis approximates concrete locations with heap identifiers, that can be materialized or merged. Meanwhile, the value analysis tracks information both on variable and heap identifiers, taking into account when heap identifiers are merged or materialized. We show how existing pointer and shape analyses, as well as numerical domains, can be plugged in our framework. As far as we know, this is the first sound generic automatic framework combining heap and value analyses that allows to freely manage heap identifiers.

    A Framework for Combining Algebraic and Logical Abstract Interpretations

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    We introduce a reduced product combining algebraic and logical abstractions to design program correctness verifiers and static analyzers by abstract interpretation. The key new idea is to show that the Nelson-Oppen procedure for combining theories in SMT-solvers computes a reduced product in an observational semantics, so that algebraic and logical abstract interpretations can naturally be combined in a classical way using a reduced product on this observational semantics. The main practical benefit is that reductions can be performed within the logical abstract domains, within the algebraic abstract domains, and also between the logical and the algebraic abstract domains, including the case of abstractions evolving during the analysis

    User-centered Program Analysis Tools

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    The research and industrial communities have made great strides in developing advanced software defect detection tools based on program analysis. Most of the work in this area has focused on developing novel program analysis algorithms to find bugs more efficiently or accurately, or to find more sophisticated kinds of bugs. However, the focus on algorithms often leads to tools that are complex and difficult to actually use to debug programs. We believe that we can design better, more useful program analysis tools by taking a user-centered approach. In this dissertation, we present three possible elements of such an approach. First, we improve the user interface by designing Path Projection, a toolkit for visualizing program paths, such as call stacks, that are commonly used to explain errors. We evaluated Path Projection in a user study and found that programmers were able to verify error reports more quickly with similar accuracy, and strongly preferred Path Projection to a standard code viewer. Second, we make it easier for programmers to combine different algorithms to customize the precision or efficiency of a tool for their target programs. We designed Mix, a framework that allows programmers to apply either type checking, which is fast but imprecise, or symbolic execution, which is precise but slow, to different parts of their programs. Mix keeps its design simple by making no modifications to the constituent analyses. Instead, programmers use Mix annotations to mark blocks of code that should be typed checked or symbolically executed, and Mix automatically combines the results. We evaluated the effectiveness of Mix by implementing a prototype called Mixy for C and using it to check for null pointer errors in vsftpd. Finally, we integrate program analysis more directly into the debugging process. We designed Expositor, an interactive dynamic program analysis and debugging environment built on top of scripting and time-travel debugging. In Expositor, programmers write program analyses as scripts that analyze entire program executions, using list-like operations such as map and filter to manipulate execution traces. For efficiency, Expositor uses lazy data structures throughout its implementation to compute results on-demand, enabling a more interactive user experience. We developed a prototype of Expositor using GDB and UndoDB, and used it to debug a stack overflow and to unravel a subtle data race in Firefox
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