Computing and Information Systems - Research Publications

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    Four-Valued Reasoning and Cyclic Circuits
    Gange, G ; Horsfall, B ; Naish, L ; Sondergaard, H (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2014-07-01)
    Allowing cycles in a logic circuit can be advantageous, for example, by reducing the number of gates required to implement a given Boolean function, or a set of functions. However, a cyclic circuit may easily be ill behaved. For instance, it may have some output wire oscillation instead of reaching a steady state. Propositional three-valued logic has long been used in tests for good behavior of cyclic circuits; a symbolic evaluation method known as ternary analysis provides one criterion for good behavior under certain assumptions about wire and gate delay. We revisit ternary analysis and argue for the use of four truth values. The fourth truth value allows for the distinction of undefined and underspecified behavior. Ability to under specify behavior is useful, because, in a quest for smaller circuits, an implementor can capitalize on degrees of freedom offered in the specification. Moreover, a fourth truth value is attractive because, rather than complicating (ternary) circuit analysis, it introduces a pleasant symmetry, in the form of contra-duality, as well as providing a convenient framework for manipulating specifications. We use this symmetry to provide fixed point results that clarify how two-, three-, and four-valued analyses are related, and to explain some observations about ternary analysis.
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    Synthesizing Optimal Switching Lattices
    Gange, G ; Søndergaard, H ; Stuckey, PJ (Association for Computing Machinery, 2014-11)
    The use of nanoscale technologies to create electronic devices has revived interest in the use of regular structures for defining complex logic functions. One such structure is the switching lattice, a two-dimensional lattice of four-terminal switches. We show how to directly construct switching lattices of polynomial size from arbitrary logic functions; we also show how to synthesize minimal-sized lattices by translating the problem to the satisfiability problem for a restricted class of quantified Boolean formulas. The synthesis method is an anytime algorithm that uses modern SAT solving technology and dichotomic search. It improves considerably on an earlier proposal for creating switching lattices for arbitrary logic functions.
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    A complete refinement procedure for regular separability of context-free languages
    Gange, G ; Navas, JA ; Schachte, P ; Sondergaard, H ; Stuckey, PJ (ELSEVIER SCIENCE BV, 2016-04-25)
    Often, when analyzing the behaviour of systems modelled as context-free languages, we wish to know if two languages overlap. To this end, we present a class of semi-decision procedures for regular separability of context-free languages, based on counter-example guided abstraction refinement. We propose two effective instances of this approach, one that is complete but relatively expensive, and one that is inexpensive and sound, but for which we do not have a completeness proof. The complete method will prove disjointness whenever the input languages are regularly separable. Both methods will terminate whenever the input languages overlap. We provide an experimental evaluation of these procedures, and demonstrate their practicality on a range of verification and language-theoretic instances.
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    Reference Abstract Domains and Applications to String Analysis
    Amadini, R ; Gange, G ; Gauthier, F ; Jordan, A ; Schachte, P ; Sondergaard, H ; Stuckey, PJ ; Zhang, C (IOS Press, 2018-02-09)
    Abstract interpretation is a well established theory that supports reasoning about the run-time behaviour of programs. It achieves tractable reasoning by considering abstractions of run-time states, rather than the states themselves. The chosen set of abstractions is referred to as the abstract domain. We develop a novel framework for combining (a possibly large number of) abstract domains. It achieves the effect of the so-called reduced product without requiring a quadratic number of functions to translate information among abstract domains. A central notion is a reference domain, a medium for information exchange. Our approach suggests a novel and simpler way to manage the integration of large numbers of abstract domains. We instantiate our framework in the context of string analysis. Browser-embedded dynamic programming languages such as JavaScript and PHP encourage the use of strings as a universal data type for both code and data values. The ensuing vulnerabilities have made string analysis a focus of much recent research. String analysis tends to combine many elementary string abstract domains, each designed to capture a specific aspect of strings. For this instance the set of regular languages, while too expensive to use directly for analysis, provides an attractive reference domain, enabling the efficient simulation of reduced products of multiple string abstract domains.
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    Wombit: A Portfolio Bit-Vector Solver Using Word-Level Propagation
    Wang, W ; Søndergaard, H ; Stuckey, PJ (Springer Netherlands, 2019-10-15)
    We develop an idea originally proposed by Michel and Van Hentenryck of how to perform bit-vector constraint propagation on the word level. Most operations are propagated in constant time, assuming the bit-vector fits in a machine word. In contrast, bit-vector SMT solvers usually solve bit-vector problems by (ultimately) bit-blasting, that is, mapping the resulting operations to conjunctive normal form clauses, and using SAT technology to solve them. Bit-blasting generates intermediate variables which can be an advantage, as these can be searched on and learnt about. As each approach has advantages, it makes sense to try to combine them. In this paper, we describe an approach to bit-vector solving using word-level propagation with learning. We have designed alternative word-level propagators to Michel and Van Hentenryck’s, and evaluated different variants of the approach. We have also experimented with different approaches to learning and back-jumping in the solver. Based on the insights gained, we have built a portfolio solver, Wombit, which essentially extends the STP bit-vector solver. Using machine learning techniques, the solver makes a judicious up-front decision about whether to use word-level propagation or fall back on bit-blasting.
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    Horn Clauses As an Intermediate Representation for Program Analysis and Transformation
    Gange, G ; Navas Laserna, J ; Schachte, P ; SONDERGAARD, H ; Stuckey, PJ (Cambridge University Press, 2015)
    Abstract Many recent analyses for conventional imperative programs begin by transforming programs into logic programs, capitalising on existing LP analyses and simple LP semantics. We propose using logic programs as an intermediate program representation throughout the compilation process. With restrictions ensuring determinism and single-modedness, a logic program can easily be transformed to machine language or other low-level language, while maintaining the simple semantics that makes it suitable as a language for program analysis and transformation. We present a simple LP language that enforces determinism and single-modedness, and show that it makes a convenient program representation for analysis and transformation.
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    Interval Analysis and Machine Arithmetic: Why Signedness Ignorance Is Bliss
    Gange, G ; Navas, JA ; Schachte, P ; Sondergaard, H ; Stuckey, PJ (Association for Computing Machinery, 2015)
    The most commonly used integer types have fixed bit-width, making it possible for computations to “wrap around,” and many programs depend on this behaviour. Yet much work to date on program analysis and verification of integer computations treats integers as having infinite precision, and most analyses that do respect fixed width lose precision when overflow is possible. We present a novel integer interval abstract domain that correctly handles wrap-around. The analysis is signedness agnostic. By treating integers as strings of bits, only considering signedness for operations that treat them differently, we produce precise, correct results at a modest cost in execution time.
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    An Algorithm for Affine Approximation of Binary Decision Diagrams
    Henshall, K ; Schachte, P ; Sondergaard, H ; Whiting, L (Theory of Computing Exchange, 2010)
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    Un-kleene boolean equation solving
    Herlihy, B ; Schachte, P ; Sondergaard, H (WORLD SCIENTIFIC PUBL CO PTE LTD, 2007-04)
    We present a new method for finding closed forms of recursive Boolean function definitions. Traditionally, these closed forms are found by Kleene iteration: iterative approximation until a fixed point is reached. Conceptually, our new method replaces each k-ary function by 2k Boolean constants defined by mutual recursion. The introduction of an exponential number of constants is mitigated by the simplicity of their definitions and by the use of a novel variant of ROBDDs to avoid repeated computation. Experiments suggest that this approach is significantly faster than Kleene iteration for examples that require many Kleene iteration steps.
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    Information loss in knowledge compilation: A comparison of Boolean envelopes
    Schachte, P ; Sondergaard, H ; Whiting, L ; Henshall, K (ELSEVIER SCIENCE BV, 2010-06)