We present a method for automatically generating verification conditions for a class of imperative programs and safety properties. Our method is parametric with respect to the semantics of the imperative programming l...
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ISBN:
(纸本)9781450335164
We present a method for automatically generating verification conditions for a class of imperative programs and safety properties. Our method is parametric with respect to the semantics of the imperative programming language, as it specializes, by using unfold/fold transformation rules, a Horn clause interpreter that encodes that semantics. We define a multi-step operational semantics for a fragment of the C language and compare the verification conditions obtained by using this semantics with those obtained by using a more traditional small-step semantics. The flexibility of the approach is further demonstrated by showing that it is possible to easily take into account alternative operational semantics definitions for modeling new language features. Finally, we provide an experimental evaluation of the method by generating verification conditions using the multi-step and the small-step semantics for a few hundreds of programs taken from various publicly available benchmarks, and by checking the satisfiability of these verification conditions by using state-of-the-art Horn clause solvers. These experiments show that automated verification of programs from a formal definition of the operational semantics is indeed feasible in practice.
This paper presents a hybrid programming framework for solving multi-objective optimization problems in supply chain. The proposed approach consists of the integration and hybridization of two modeling and solving env...
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ISBN:
(纸本)9788360810668
This paper presents a hybrid programming framework for solving multi-objective optimization problems in supply chain. The proposed approach consists of the integration and hybridization of two modeling and solving environments, i.e., constraint logic programming and mathematical programming, to obtain a programming framework that offers significant advantages over the classical approach derived from operational research. The strongest points of both components are combined in the hybrid framework, which by introducing transformation allows a significant reduction in size of a problem and the optimal solution is found a lot faster. This is particularly important in the multi-objective optimization where problems have to be solved over and over again to find a set of Pareto-optimal solutions. An over two thousand-fold reduction in size was obtained for the illustrative examples together with a few hundred-fold reduction in the speed of finding the solution in relation to the mathematical programming method. In addition, the proposed framework allows the introduction of logical constraints that are difficult or impossible to model in operational research environments.
The paper presents the concept of a declarative approach to decision support for sustainable supply chain (SSC) problems. This approach proposed here combines the strengths of mathematical programming (MP) and constra...
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ISBN:
(纸本)9783319196381;9783319196374
The paper presents the concept of a declarative approach to decision support for sustainable supply chain (SSC) problems. This approach proposed here combines the strengths of mathematical programming (MP) and constraint logic programming (CLP), which leads to a significant reduction in the search time necessary to find the solution, and allows solving larger problems. It also presents the implementation of the proposed approach in the form of the declarative decision support platform (DDSP). The DDSP allows the implementation of complete decision-making models, constraints as well as a set of questions for these models. The illustrative examples presented in the paper illustrate efficiency and possibilities of this approach.
Generation of home plans based on several attributes like constraints and preferences is an interesting research area. Most related research works on floor plan generation do not always adhere to the necessary constra...
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ISBN:
(纸本)9781467382700
Generation of home plans based on several attributes like constraints and preferences is an interesting research area. Most related research works on floor plan generation do not always adhere to the necessary constraints such as reachability, connectivity and different shaping. This paper presents a novel and flexible technique for generating floor plans subject to minimum geometrical requirements, architectural and legal attributes by showing generated floor plans for different shaped designs with satisfying set of attributes. Since there are number of possible combinations to generate a floor plan, it is really a challenging task to figure out the optimum solution for a particular scenario. Rather than evaluating the floor plan after applying a set of attributes, system checks whether the floor plan satisfies the requirements, while generating the floor plan inside a single rule in knowledgebase. The proposed model would result in minimizing the number of attributes associated with the most important features in architectural home designing, significant reduction in designing costs and release of human labor. The main feature of the proposed system is its representation power since it is not limited to representing just rectangular shaped floor plans. In totality, this tends to increase customer satisfaction as a final goal of the system. Furthermore the method is efficient and easy to implement and integrate into the larger context of modeling of home plans.
Resource-constrained scheduling problems appear frequently at different levels of decisions in manufacturing, logistics, computer networks, software engineering etc. They are usually characterized by many types of con...
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ISBN:
(纸本)9783319248349;9783319248332
Resource-constrained scheduling problems appear frequently at different levels of decisions in manufacturing, logistics, computer networks, software engineering etc. They are usually characterized by many types of constraints, which often make them unstructured and difficult to solve (NP-complete). Traditional mathematical programming (MP) approaches are deficient because their representation of allocation constraints is artificial (using 0-1 variables). Unlike traditional approaches, declarative constraint logic programming (CLP) provides for a natural representation of heterogeneous constraints. In CLP we state the problem requirements by constraints;we do not need to specify how to meet these requirements. CLP approach is very effective for binary constraints (binding at most two variables). If there are more variables in the constraints and the problem requires further optimization, the efficiency decreases dramatically. This paper presents a hybrid programming framework for constrained scheduling problems where two environments (mathematical programming and constraint logic programming) were integrated. This integration, hybridization as well as a transformation of the problem helped reduce the combinatorial problem substantially. In order to compare the effectiveness of the proposed framework, also made implementation of illustrative example separately for the two environments MP and CLP.
This paper describes the hybrid approach to optimization of decision problems in supply chain management (SCM). The hybrid approach proposed here combines the strengths of mathematical programming (MP) and constraint ...
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ISBN:
(纸本)9783319184227;9783319184210
This paper describes the hybrid approach to optimization of decision problems in supply chain management (SCM). The hybrid approach proposed here combines the strengths of mathematical programming (MP) and constraint logic programming (CLP), which leads to a significant reduction in the search time necessary to find the optimal solution, and allows solving larger problems. The proposed hybrid approach is presented as a concept of an additional layer of decision-making in integrated systems, for example ERP, DRP, etc. This solution allows the implementation of complete decision-making models, additional constraints as well as a set of questions for these models. The illustrative model presented in the article illustrate the advantages of the approach.
Floor storage systems are used in the shoe industry to store fashion products of seasonal collections with low quantity and high variety. Since space is precious and order picking must be sped up, stacking of shoe box...
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ISBN:
(纸本)9781424447350
Floor storage systems are used in the shoe industry to store fashion products of seasonal collections with low quantity and high variety. Since space is precious and order picking must be sped up, stacking of shoe boxes should be optimized. The problem is modeled by assigning an integer code to each box basing on shoe characteristics (model, material, color, and size) and trying to force similar boxes into near locations to improve pickers' ability of fast order retrieval. The model is encoded in constraint logic programming and solved comparing different strategies, also using Large Neighborhood Search.
Uncertainty in logicprogramming has been widely investigated in the last decades, leading to multiple extensions of the classical logicprogramming paradigm. However, few of these are designed as extensions of the we...
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Uncertainty in logicprogramming has been widely investigated in the last decades, leading to multiple extensions of the classical logicprogramming paradigm. However, few of these are designed as extensions of the well-established and powerful constraint logic programming (CLP) scheme for CLP. In a previous work we have proposed the proximity-based qualified constraint logic programming (SQCLP) scheme as a quite expressive extension of CLP with support for qualification values and proximity relations as generalizations of uncertainty values and similarity relations, respectively. In this paper we provide a transformation technique for transforming SQCLP programs and goals into semantically equivalent CLP programs and goals, and a practical Prolog-based implementation of some particularly useful instances of the SQCLP scheme. We also illustrate, by showing some simple - and working - examples, how the prototype can be effectively used as a tool for solving problems where qualification values and proximity relations play a key role. Intended use of SQCLP includes flexible information retrieval applications.
Privacy policies are rules designed to ensure that individuals' health data are properly protected. Health Information Systems (HIS) are legally required to adhere to these policies. Since privacy policies are imp...
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Privacy policies are rules designed to ensure that individuals' health data are properly protected. Health Information Systems (HIS) are legally required to adhere to these policies. Since privacy policies are imposed on complex software systems, it is extremely hard to reason about their conformance and consistency. In order to address this problem, we have created a model-driven authoring environment to formally specify privacy policies originally defined in legal terms. In our observation, appropriate formalization of our policy language enabled formal analysis of its policies;these features were key to a successful model-driven engineering process. In this paper we present our modeling language and show its semantic anchoring to analyzable logic programs. We report on several projects where our approach is being applied and validated. (C) 2013 Elsevier B.V. All rights reserved.
We present a method for verifying properties of imperative programs by using techniques based on the specialization of constraintlogic programs (CLP). We consider a class of imperative programs with integer variables...
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We present a method for verifying properties of imperative programs by using techniques based on the specialization of constraintlogic programs (CLP). We consider a class of imperative programs with integer variables and we focus our attention on safety properties, stating that no error configuration can be reached from any initial configuration. We introduce a CLP program I that encodes the interpreter of the language and defines a predicate unsafe equivalent to the negation of the safety property to be verified. Then, we specialize the CLP program I with respect to the given imperative program and the given initial and error configurations, with the objective of deriving a new CLP program I-sp that either contains the fact unsafe (and in this case the imperative program is proved unsafe) or contains no clauses with head unsafe (and in this case the imperative program is proved safe). If Isp enjoys neither of these properties, we iterate the specialization process with the objective of deriving a CLP program where we can prove unsafety or safety. During the various specializations we may apply different strategies for propagating information (either propagating forward from an initial configuration to an error configuration, or propagating backward from an error configuration to an initial configuration) and different operators (such as the widening and the convex hull operators) for generalizing predicate definitions. Each specialization step is guaranteed to terminate, but due to the undecidability of program safety, the iterated specialization process may not terminate. By an experimental evaluation carried out on a significant set of examples taken from the literature, we show that our method improves the precision of program verification with respect to state-of-the-art software model checkers. (C) 2014 Elsevier B.V. All rights reserved.
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