84 research outputs found
On Solving Word Equations Using SAT
We present Woorpje, a string solver for bounded word equations (i.e.,
equations where the length of each variable is upper bounded by a given
integer). Our algorithm works by reformulating the satisfiability of bounded
word equations as a reachability problem for nondeterministic finite automata,
and then carefully encoding this as a propositional satisfiability problem,
which we then solve using the well-known Glucose SAT-solver. This approach has
the advantage of allowing for the natural inclusion of additional linear length
constraints. Our solver obtains reliable and competitive results and,
remarkably, discovered several cases where state-of-the-art solvers exhibit a
faulty behaviour
Introducing willingness-to-pay for noise changes into transport appraisal: an application of benefit transfer.
Numerous research studies have elicited willingness-to-pay values for transport-related noise, however, in many industrialised countries including the UK, noise costs and benefits are still not incorporated into appraisals for most transport projects and policy changes (Odgaard et al, 2005; Grant-Muller et al, 2001). This paper describes the actions recently taken in the UK to address this issue, comprising: primary research based on the city of Birmingham; an international review of willingness-to-pay evidence; development of values using benefit transfers over time and locations; and integration with appraisal methods. Amongst the main findings are: that the willingness-to-pay estimates derived for the UK are broadly comparable with those used in appraisal elsewhere in Europe; that there is a case for a lower threshold at
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45dB(A)Leq,18hr1 rather than the more conventional 55dB(A); and that values per dB(A) increase with the noise level above this threshold. There are significant issues over the valuation of rail versus road noise, the neglect of non-residential noise and the valuation of high noise levels in different countries. Conclusions are drawn regarding the feasibility of noise valuation based on benefit transfers in the UK and elsewhere, and future research needs in this field are discussed
Multivariant Assertion-based Guidance in Abstract Interpretation
Approximations during program analysis are a necessary evil, as they ensure
essential properties, such as soundness and termination of the analysis, but
they also imply not always producing useful results. Automatic techniques have
been studied to prevent precision loss, typically at the expense of larger
resource consumption. In both cases (i.e., when analysis produces inaccurate
results and when resource consumption is too high), it is necessary to have
some means for users to provide information to guide analysis and thus improve
precision and/or performance. We present techniques for supporting within an
abstract interpretation framework a rich set of assertions that can deal with
multivariance/context-sensitivity, and can handle different run-time semantics
for those assertions that cannot be discharged at compile time. We show how the
proposed approach can be applied to both improving precision and accelerating
analysis. We also provide some formal results on the effects of such assertions
on the analysis results.Comment: Pre-proceedings paper presented at the 28th International Symposium
on Logic-Based Program Synthesis and Transformation (LOPSTR 2018), Frankfurt
am Main, Germany, 4-6 September 2018 (arXiv:1808.03326
A Survey of Satisfiability Modulo Theory
Satisfiability modulo theory (SMT) consists in testing the satisfiability of
first-order formulas over linear integer or real arithmetic, or other theories.
In this survey, we explain the combination of propositional satisfiability and
decision procedures for conjunctions known as DPLL(T), and the alternative
"natural domain" approaches. We also cover quantifiers, Craig interpolants,
polynomial arithmetic, and how SMT solvers are used in automated software
analysis.Comment: Computer Algebra in Scientific Computing, Sep 2016, Bucharest,
Romania. 201
Correct composition of dephased behavioural models
This research is supported by EPSRC grant EP/M014290/1.Scenarios of execution are commonly used to specify partial behaviour and interactions between different objects and components in a system. To avoid overall inconsistency in specifications, various automated methods have emerged in the literature to compose (behavioural) models. In recent work, we have shown how the theorem prover Isabelle can be combined with the constraint solver Z3 to efficiently detect inconsistencies in two or more behavioural models and, in their absence, generate the composition. Here, we extend our approach further and show how to generate the correct composition (as a set of valid traces) of dephased models. This work has been inspired by a problem from a medical domain where different care pathways (for chronic conditions) may be applied to the same patient with different starting points.Postprin
Global Guidance for Local Generalization in Model Checking
SMT-based model checkers, especially IC3-style ones, are currently the most
effective techniques for verification of infinite state systems. They infer
global inductive invariants via local reasoning about a single step of the
transition relation of a system, while employing SMT-based procedures, such as
interpolation, to mitigate the limitations of local reasoning and allow for
better generalization. Unfortunately, these mitigations intertwine model
checking with heuristics of the underlying SMT-solver, negatively affecting
stability of model checking. In this paper, we propose to tackle the
limitations of locality in a systematic manner. We introduce explicit global
guidance into the local reasoning performed by IC3-style algorithms. To this
end, we extend the SMT-IC3 paradigm with three novel rules, designed to
mitigate fundamental sources of failure that stem from locality. We instantiate
these rules for the theory of Linear Integer Arithmetic and implement them on
top of SPACER solver in Z3. Our empirical results show that GSPACER, SPACER
extended with global guidance, is significantly more effective than both SPACER
and sole global reasoning, and, furthermore, is insensitive to interpolation.Comment: Published in CAV 202
Global Guidance for Local Generalization in Model Checking
SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of Spacer solver in Z3. Our empirical results show that GSpacer, Spacer extended with global guidance, is significantly more effective than both Spacer and sole global reasoning, and, furthermore, is insensitive to interpolation
Lightweight String Reasoning for OCL
International audienceModels play a key role in assuring software quality in the modeldriven approach. Precise models usually require the definition of OCL expressions to specify model constraints that cannot be expressed graphically. Techniques that check the satisfiability of such models and find corresponding instances of them are important in various activities, such as model-based testing and validation. Several tools to check model satisfiability have been developed but to our knowledge, none of them yet supports the analysis of OCL expressions including operations on Strings in general terms. As, in contrast, many industrial models do contain such operations, there is evidently a gap. There has been much research on formal reasoning on strings in general, but so far the results could not be included into model finding approaches. For model finding, string reasoning only contributes a sub-problem, therefore, a string reasoning approach for model finding should not add up front too much computational complexity to the global model finding problem. We present such a lightweight approach based on constraint satisfaction problems and constraint rewriting. Our approach efficiently solves several common kinds of string constraints and it is integrated into the EMFtoCSP model finder
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