The problem of finding small unsatisfiable subsets of a set of constraints is important for various applications in computer science and artificial intelligence. We study the problem of identifying whether a given ins...
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The problem of finding small unsatisfiable subsets of a set of constraints is important for various applications in computer science and artificial intelligence. We study the problem of identifying whether a given instance to the constraint satisfaction problem (CSP) has an unsatisfiable subset of size at most k from a parameterized complexity point of view. We show that the problem of finding small unsatisfiable subsets of a CSP instance is harder than the corresponding problem for CNF formulas. Moreover, we show that the problem is not fixed-parameter tractable when restricting the problem to any maximal tractable Boolean constraint language (for which the problem is nontrivial). We show that the problem is hard even when the maximum number of occurrences of any variable is bounded by a constant, a restriction which leads to fixed-parameter tractability for the case of CNF formulas. Finally, we relate the problem of finding small unsatisfiable subsets to the problem of identifying variable assignments that are enforced already by a small number of constraints (backbones), or that are ruled out already by a small number of constraints (anti-backbones).
Technical debt is a term that has been used to describe the increased cost of changing or maintaining a system due to shortcuts taken during its development. As technical debt is a recent research area, its different ...
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Technical debt is a term that has been used to describe the increased cost of changing or maintaining a system due to shortcuts taken during its development. As technical debt is a recent research area, its different types and their indicators are not organized yet. Therefore, this paper proposes an ontology of terms on technical debt in order to organize a common vocabulary for the area. The organized concepts derived from the results of a systematic literature mapping. The proposed ontology was evaluated in two steps. In the first one, some ontology design quality criteria were used. For the second one, a specialist in the area performed an initial evaluation. This work contributes to evolve the Technical Debt Landscape through the organization of the different types of technical debt and their indicators. We consider this an important contribution for both researchers and practitioners because this information was spread out in the literature hindering their use in research and development activities.
Working with design patterns made significant progress towards the goal of improving the quality of software production. One of the major issues confronting used design pattern is the appropriate selection for them. H...
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ISBN:
(纸本)9780889869431
Working with design patterns made significant progress towards the goal of improving the quality of software production. One of the major issues confronting used design pattern is the appropriate selection for them. However, developers of experienced are able to choose the occasion design patterns for a given problem effectively;unluckily, are difficult task for inexperienced. Thus, there several tools for help choose of pattern. In this paper presents our attempt to use agent technology to enhance assistant the developers to selecting fits design pattern that need to solve their problem. This study focused on the improving the process of pattern selection through proposing an architecture Design Pattern Selection (DPS) based on Multi-Agent System (MAS) supports to obtain the appropriate recommendation.
In this paper, the event-triggered least squares state and fault estimation problem is investigated for a class of systems with stochastic nonlinearities. An event-triggered scheme is properly proposed whose main idea...
In this paper, the event-triggered least squares state and fault estimation problem is investigated for a class of systems with stochastic nonlinearities. An event-triggered scheme is properly proposed whose main idea is to transmit the measurement output to a remote estimator only when a specified event condition is violated and an event is triggered. A filter is designed so as to minimize an upper bound of the filtering error covariance with event-triggered measurement transmissions and additive stochastic nonlinearities. By solving two sets of discrete matrix equations, the desired filter parameters are calculated recursively and thus the method is applicable for online computation. Both the state and fault estimation problems are handled within the same framework using the least squares method. A numerical simulation is exploited to illustrate the effectiveness of the proposed algorithm.
This paper presents a min-max regret version programming model for the stochastic flexible job shop scheduling problem (S-FJSP) with the uncertainty of processing time. An effective Markov network based estimation of ...
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This paper presents a min-max regret version programming model for the stochastic flexible job shop scheduling problem (S-FJSP) with the uncertainty of processing time. An effective Markov network based estimation of distribution algorithm (EDA) is proposed to solve S-FJSP to minimize its maximum regret. The proposal employs Markov network modeling machine assignment where the effects between decision variables are represented as an undirected graph model. Furthermore, min-max regret metric based assessing algorithm is used to measure the robustness, where a critical path-based local search method is adopted to achieve better performance. We present an empirical validation for the proposal by applying it to solve various benchmark flexible job shop problems.
Patient monitoring is a very critical function carried out in health care facilities on a daily basis. This is normally done manually and or by Wireless Body Sensor Networks (WBSN) which are physically monitored by me...
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In this paper, the event-based finite-horizon filtering problem is investigated for discrete time-varying systems. For the purpose of reducing communication, a general event generator is employed to determine the even...
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In this paper, the event-based finite-horizon filtering problem is investigated for discrete time-varying systems. For the purpose of reducing communication, a general event generator is employed to determine the event time instant and then transmit the measurement output to the remote time-varying filter. By utilizing the stochastic analysis techniques, sufficient conditions are derived for a finite-horizon filter to satisfy the prescribed H ∞ performance requirement. These conditions are expressed in terms of the feasibility of a series of recursive linear matrix inequalities. The effectiveness of the proposed filter design scheme is illustrated by a numerical simulation.
Real-time sound rendering applications are memory-intensive and computation-intensive. To speed up computation and extend the simulated area, a real-time sound rendering system based on the hardware-oriented finite di...
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The concept of code smells is widespread in software Engineering. Despite the empirical studies addressing the topic, the set of context-dependent issues that impacts the human perception of what is a code smell has n...
The concept of code smells is widespread in software Engineering. Despite the empirical studies addressing the topic, the set of context-dependent issues that impacts the human perception of what is a code smell has not been studied in depth. We call this the code smell conceptualization problem. To discuss the problem, empirical studies are necessary. In this work, we focused on conceptualization of god class. God class is a code smell characterized by classes that tend to centralize the intelligence of the system. It is one of the most studied smells in software engineering literature. A controlled experiment that extends and builds upon a previous empirical study about how humans detect god classes, their decision drivers, and agreement rate. Our study delves into research questions of the previous study, adding visualization to the smell detection process, and analyzing strategies of detection. Our findings show that agreement among participants is low, which corroborates previous studies. We show that this is mainly related to agreeing on what a god class is and which thresholds should be adopted, and not related to comprehension of the programs. The use of visualization did not improve the agreement among the participants. However, it did affect the choice of detection drivers. This study contributes to expand empirical evidences on the impact of human perception on detecting code smells. It shows that studies about the human role in smell detection are relevant and they should consider the conceptualization problem of code smells.
This article presents two proposals in order to solve the problem of choosing the best access network available in the environment where the user is located. One based on a combination of fuzzy logic technique with tw...
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ISBN:
(纸本)9781479932177
This article presents two proposals in order to solve the problem of choosing the best access network available in the environment where the user is located. One based on a combination of fuzzy logic technique with two decision-making methods, AHP (Analytic Hierarchy Process) and GRA (Grey Relation Analysis), and the other based only on fuzzy logic technique. In order to demonstrate the effectiveness of these proposals, they were compared with a third one, of the authors in [71, which uses a combination of AHP method with a cost function. The obtained results show that the two proposals presented in this paper are more efficient in sorting and selecting the best access network when compared to the third.
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