Analysing Logic Programs by Reasoning Backwards

Howe, Jacob M.; King, Andy; Lu, Lunjin

doi:10.1007/978-3-540-25951-0_6

Cited by 12 publications

(10 citation statements)

References 64 publications

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“…The specialized CLP clauses may enable more efficient bounded verification, and they can also be used as input to other tools for analysis and verification (such as constraint-based analyzers [3,11] and SMT solvers [8,14]), which have already been shown to be effective in other contexts [2,4,5]. Moreover, the specialized clauses can be used to apply backward analysis techniques for CLP programs based on abstract interpretation (see, for instance, [9,12]). Backward analysis aims at deriving from a property that is expected to hold at the end of the execution of a program, conditions on the query which guarantee that the desired property indeed holds.…”

Section: Discussionmentioning

confidence: 99%

Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Angelis

Fioravanti

Palacios

et al. 2018

Electron. Proc. Theor. Comput. Sci.

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Dynamically typed languages, like Erlang, allow developers to quickly write programs without explicitly providing any type information on expressions or function definitions. However, this feature makes those languages less reliable than statically typed languages, where many runtime errors can be detected at compile time. In this paper, we present a preliminary work on a tool that, by using the well-known techniques of metaprogramming and symbolic execution, can be used to perform bounded verification of Erlang programs. In particular, by using Constraint Logic Programming, we develop an interpreter that, given an Erlang program and a symbolic input for that program, returns answer constraints that represent sets of concrete data for which the Erlang program generates a runtime error. the Spanish Ayudas para contratos predoctorales para la formación de doctores and Ayudas a la movilidad predoctoral para la realización de estancias breves en centros de I+D, MINECO (SEIDI), under FPI grants BES-2014-069749 and EEBB-I-17-12101.

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Section: Discussionmentioning

confidence: 99%

Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Angelis

Fioravanti

Palacios

et al. 2018

Electron. Proc. Theor. Comput. Sci.

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“…Projection analysis [Wadler and Hughes 1987;Hughes 1988;Davis and Wadler 1990] in functional programs and mode analyses [King and Lu 2002;Howe et al 2004] in logic programs both underapproximate the weakest preconditions sharing the same goal as our abstract-value slicer, but their techniques are not directly applicable to the problem of this article. The projection analysis estimates a function that transforms the demand for the output to the one for the input.…”

Section: Related Workmentioning

confidence: 99%

Goal-directed weakening of abstract interpretation results

Seo

Yang

et al. 2007

ACM Trans. Program. Lang. Syst.

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One proposal for automatic construction of proofs about programs is to combine Hoare logic and abstract interpretation. Constructing proofs is in Hoare logic. Discovering programs' invariants is done by abstract interpreters.One problem of this approach is that abstract interpreters often compute invariants that are not needed for the proof goal. The reason is that the abstract interpreter does not know what the proof goal is, so it simply tries to find as strong invariants as possible. These unnecessary invariants increase the size of the constructed proofs. Unless the proof-construction phase is notified which invariants are not needed, it blindly proves all the computed invariants.In this article, we present a framework for designing algorithms, called abstract-value slicers, that slice out unnecessary invariants from the results of forward abstract interpretation. The framework provides a generic abstract-value slicer that can be instantiated into a slicer for a particular abstract interpretation. Such an instantiated abstract-value slicer works as a postprocessor to an abstract interpretation in the whole proof-construction process, and notifies to the Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 ( next proof-construction phase which invariants it does not have to prove. Using the framework, we designed an abstract-value slicer for an existing relational analysis and applied it on programs. In this experiment, the slicer identified 62%-81% of the computed invariants as unnecessary, and resulted in 52%-84% reduction in the size of constructed proofs.

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“…Thus, for non-leftmost unfolding to be able to "jump over" internal predicates, it is required that such pure assertions are available not only for external predicates, but also for predicates internal to the module. Such assertions can be manually added by the user or, much more interestingly, as our system does, by backwards analysis [5,3,6]. Indeed, we believe that manual introduction of assertions about purity of goals is too much of a burden for the user.…”

Section: Automatic Inference Of Purity Assertionsmentioning

confidence: 99%

“…For logic programs without impure predicates, non-leftmost unfolding is sound thanks to the independence of the computation rule (see for example [13]). 5 Unfortunately, non-leftmost unfolding poses several problems in the context of full Prolog programs with impure predicates, where such independence does not hold anymore. For instance, ground/1 is an impure predicate since, under LD resolution, the goal ground(X),X=a fails whereas X=a,ground(X) succeeds with computed answer X/a.…”

Section: Introductionmentioning

confidence: 99%

Non-leftmost Unfolding in Partial Evaluation of Logic Programs with Impure Predicates

Albert

Puebla²,

Gallagher

2006

Logic Based Program Synthesis and Transformation

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Partial evaluation of logic programs which contain impure predicates poses non-trivial challenges. Impure predicates include those which produce side-effects, raise errors (or exceptions), and those whose truth value varies according to the degree of instantiation of arguments 4. In particular, non-leftmost unfolding steps can produce incorrect results since the independence of the computation rule no longer holds in the presence of impure predicates. Existing proposals allow non-leftmost unfolding steps, but at the cost of accuracy: bindings and failure are not propagated backwards to predicates which are potentially impure. In this work we propose a partial evaluation scheme which substantially reduces the situations in which such backpropagation has to be avoided. With this aim, our partial evaluator takes into account the information about purity of predicates expressed in terms of assertions. This allows achieving some optimizations which are not feasible using existing partial evaluation techniques. We argue that our proposal goes beyond existing ones in that it is a) accurate, since the classification of pure vs impure is done at the level of atoms instead of predicates, b) extensible, as the information about purity can be added to programs using assertions without having to modify the partial evaluator itself, and c) automatic, since (backwards) analysis can be used to automatically infer the required assertions. Our approach has been implemented in the context of CiaoPP, the abstract interpretation-based preprocessor of the Ciao logic programming system.

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Analysing Logic Programs by Reasoning Backwards

Cited by 12 publications

References 64 publications

Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Goal-directed weakening of abstract interpretation results

Non-leftmost Unfolding in Partial Evaluation of Logic Programs with Impure Predicates

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