Duplicated code, also known as code clones, are one of the malicious 'code smells' that often need to be removed through refactoring for enhancing maintainability. Among all the potential refactoring opportuni...
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ISBN:
(纸本)9780769543987
Duplicated code, also known as code clones, are one of the malicious 'code smells' that often need to be removed through refactoring for enhancing maintainability. Among all the potential refactoring opportunities, the choice and order of a set of refactoring activities may have distinguishable effect on the design/code quality. Moreover, there may be dependencies and conflicts among those refactorings. The organization may also impose priorities on certain refactoring activities. Addressing all these conflicts, priorities, and dependencies, manual formulation of an optimal refactoring schedule is very expensive, if not impossible. Therefore, an automated refactoring scheduler is necessary, which will maximize benefit and minimize refactoring effort. In this paper, we present a refactoring effort model, and propose a constraint programming approach for conflict-aware optimal scheduling of code clone refactoring.
A typical technique in integer programming for filtering variables is known as variable fixing. The optimal dual solution of the linear relaxation can be used to detect some of the 0/1 variables that must be fixed to ...
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ISBN:
(纸本)9783319661582;9783319661575
A typical technique in integer programming for filtering variables is known as variable fixing. The optimal dual solution of the linear relaxation can be used to detect some of the 0/1 variables that must be fixed to either 0 or 1 in any solution improving the best known, but this filtering is incomplete. A complete technique is proposed in this paper for satisfaction problems with an ideal integer programming formulation. We show, in this case, that the 0/1 variables taking the same value in all solutions can be identified by solving a single linear program with twice the number of the original variables. In other words, a complete variable fixing of the 0/1 variables can be performed for a small overhead. As a result, this technique can be used to design generic arc consistency algorithms. We believe it is particularly useful to quickly prototype arc consistency algorithms for numerous polynomial constraints and demonstrate it for the family of Sequence global constraints.
We create a program synthesis for searching optimal configurations in collaborative decision-making models. At the specification level, existing approaches do not consider both individual and business constraints to c...
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ISBN:
(纸本)9783319559612;9783319559605
We create a program synthesis for searching optimal configurations in collaborative decision-making models. At the specification level, existing approaches do not consider both individual and business constraints to configure products in a cooperative manner. Usually, the combination of independent specifications is manually implemented into low level platforms, which limits the management of constraint-intensive decision processes. Our proposed model-driven collaboration system analyses multiple domain and preference models to help selecting goal-driven technological solutions. First, we extend an existing domain-specific language to specify multi-objective and constraint-based business rules. Next, we created model transformations to generate a program that can be executed into two different constraint-based platforms, which combine heterogeneous and highly expressive models. We apply our approach to find a goal-driven enterprise information system solution. The program synthesis analyzed in average 697 constraints across multiple specifications to avoid inconsistencies in manual configurations.
In this paper, we propose innovative system in order to assist the user in a 3D objects layout context. Through a combination between virtual reality (VR) and constraint programming (CP) technique, user's 3D inter...
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ISBN:
(纸本)9788086943817
In this paper, we propose innovative system in order to assist the user in a 3D objects layout context. Through a combination between virtual reality (VR) and constraint programming (CP) technique, user's 3D interaction and manipulation will be translated to incoming queries of a constraints solver which propagate constraints and generate a new possible solution. The computed solution is transmitted, as new positions of 3D objects, to virtual environment (VE) which reconfigures itself. We focus in this paper on the architecture of our system and we describe the implementation of several constraints and some first results.
The analysis of infeasible subproblems plays an important role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid gl...
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ISBN:
(纸本)9783319597768;9783319597751
The analysis of infeasible subproblems plays an important role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications, obtained by domain propagation, that led to infeasibility. The result of the analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept has its origin in solving satisfiability problems and is similarly used in constraint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. The dual LP solution provides a set of multipliers that can be used to generate a single new globally valid linear constraint. The main contribution of this short paper is an empirical evaluation of two ways to combine both approaches. Experiments are carried out on general MIP instances from standard public test sets such as Miplib2010;the presented algorithms have been implemented within the non-commercial MIP solver SCIP. Moreover, we present a pool-based approach to manage conflicts which addresses the way a MIP solver traverses the search tree better than aging strategies known from SAT solving.
Starting from a hypothetical open shop production quantity estimation problem with weakly formulated objective function, this paper comparatively discusses a manual heuristic solution and an IBM-ILOG based numerical s...
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ISBN:
(纸本)9781538638422
Starting from a hypothetical open shop production quantity estimation problem with weakly formulated objective function, this paper comparatively discusses a manual heuristic solution and an IBM-ILOG based numerical solution. Problem complexity is managed by specific partitioning strategies in the construction of heuristic solution instances. The study may serve as starting point in the systematic building of a more general heuristic solution method with potential applications in business plan forecasting.
The Dynamic Facility Layout Problem (DFLP) is designing a facility over a multi-period planning horizon where the interdepartmental material flows change from one period to the next one due to changes in product deman...
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The Dynamic Facility Layout Problem (DFLP) is designing a facility over a multi-period planning horizon where the interdepartmental material flows change from one period to the next one due to changes in product demands The DFLP is used while designing manufacturing and logistics facilities over multiple planning periods;however, it is a very challenging nonlinear optimization problem. In this paper, a zone based block layout is used to design manufacturing and logistics facilities over multiple planning periods. A zone-based block layout inherently includes possible aisle structures, which can easily be adapted to different material handling systems. The unequal area DFLP is modeled and solved using a zone-based structure where the dimensions of the departments are decision variables, and the departments are assigned to flexible zones with a pre-structured positioning. A matheuristic approach, which combines concepts from Tabu Search (TS) and mathematical programming, is proposed to solve the zone-based DFLP on the continuous plane with unequal area departments. The TS determines the relative locations of departments and their assignments to zones while their exact locations and shapes are calculated by the mathematical programming. Numerical results for a set of test problems from the literature showed that our proposed matheuristic approach is promising. (C) 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the International Conference on Computational Science
With the generalization of cloud infrastructures usage, energy consumption has become a major issue. Scheduling heuristics have been proposed to optimize the resource usage of data center so as to take down the energy...
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ISBN:
(纸本)9781538621295
With the generalization of cloud infrastructures usage, energy consumption has become a major issue. Scheduling heuristics have been proposed to optimize the resource usage of data center so as to take down the energy consumption. This paper tackles the problem with a different approach by taking into consideration the availability of renewable energy. First we formalize the green energy aware scheduling problem (GEASP) and propose a global model based on constraint programming as well as a search heuristic to solve it efficiently. The proposed model integrates the various aspects inherent to the dynamic planning in a data center: heterogeneous PMs, various application types (i.e., active applications and batch applications), actions and energetic costs of turning ON/OFF physical machines, interrupting/resuming batch applications, CPU and RAM resource consumption, tasks migration, migration costs, and integration of green energy availability. The model can therefore reduce both the costs related to energy consumption and the carbon footprint of a data center. We evaluate the model with an indirect comparison against the state-of-the-art framework PIKA on real-world workload and solar power traces.
AES is a mainstream block cipher used in many protocols and whose resilience against attack is essential for cybersecurity. In [14], Oren and Wool discuss a Tolerant Algebraic Side-Channel Analysis (TASCA) and show ho...
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ISBN:
(纸本)9783319661582;9783319661575
AES is a mainstream block cipher used in many protocols and whose resilience against attack is essential for cybersecurity. In [14], Oren and Wool discuss a Tolerant Algebraic Side-Channel Analysis (TASCA) and show how to use optimization technology to exploit side-channel information and mount a computational attack against AES. This paper revisits the results and posits that constraint programming is a strong contender and a potent optimization solution. It extends bit-vector solving as introduced in [8], develops a CP and an IP model and compares them with the original Pseudo-Boolean formulation. The empirical results establish that CP can deliver solutions with orders of magnitude improvement in both run time and memory usage, traits that are essential to potential adoption by cryptographers.
Multivalued Decision Diagrams (MDDs) are efficient data structures widely used in several fields like verification, optimization and dynamic programming. In this thesis, we first focus on improving the main algorithms...
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Multivalued Decision Diagrams (MDDs) are efficient data structures widely used in several fields like verification, optimization and dynamic programming. In this thesis, we first focus on improving the main algorithms such as the re- duction, allowing MDDs to potentially exponentially compress set of tuples, or the combination of MDDs such as the intersection of the union. We go further by designing parallel algorithms, and algorithms handling non-deterministic MDDs. We then investigate relaxed MDDs, that are more and more used in optimization, and define the notions of relaxed reduction or operation and de- sign efficient algorithms for them. The sampling of solutions stored in a MDD is solved with respect to probability mass functions or Markov chains. In order to combine MDDs with constraint programming, we design the propagators of all the types of MMDD constraints in solvers, and introduce a new one, the channeling constraint. These new propagators outperform the existing ones and allow the reformulation of several other constraints such as the dispersion constraint, and even to define new ones easily. We finally apply our algorithm to several real world industrial problems such as text and music generation and geomodeling of a petroleum reservoir.
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