Constraint logic programming languages

Cohen, Jacques

doi:10.1145/79204.79209

Cited by 195 publications

(54 citation statements)

References 17 publications

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“…The key to Refresh's healing capabilities is its ability to use a constraint solver (Cohen, 1990) to derive a new feature selection for the application automatically. Prior work (Benavides et al, 2005(Benavides et al, , 2007White et al, 2007a) provides extensive details on the process for transforming a feature selection problem into a CSP (Cohen, 1990), which is the input format of a constraint solver and deriving a feature selection.…”

Section: Automated Feature Selection Using a Constraint Solvermentioning

confidence: 99%

“…Prior work (Benavides et al, 2005(Benavides et al, , 2007White et al, 2007a) provides extensive details on the process for transforming a feature selection problem into a CSP (Cohen, 1990), which is the input format of a constraint solver and deriving a feature selection. We briefly cover this mapping below.…”

Section: Automated Feature Selection Using a Constraint Solvermentioning

confidence: 99%

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Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing

White

Dougherty

Strowd

et al. 2009

Software Engineering for Self-Adaptive Systems

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Service-oriented architectures (SOAs) provide loose coupling and software reuse in enterprise applications. SOAs enable applications to heal themselves by failing over to alternate services when a critical application component or service reference fails. The numerous intricate details of identifying errors and planning a recovery strategy make it hard to develop applications that can heal by swapping services.Model-driven engineering (MDE) offers a potential solution to handling the complexity of building applications that can heal by swapping services. This paper presents an MDE technique called Refresh that is based on microrebooting and uses 1 feature models to derive a new and correct service composition when a failure occurs 2 an application's component container to shutdown the reference to the failed service 3 the application container to reboot the subsystem.We also present the results from a case study that shows Refresh significantly reduces both modelling and healing implementation effort.Keywords: feature modelling; service healing; reconfiguration; constraint satisfaction; service oriented architectures; SOAs; autonomic systems; enterprise Java Beans; model-driven development; microrebooting; self-healing; service composition. University, Nashville, TN. During the past two decades he has led pioneering research on patterns, optimisation techniques and empirical analyses of object-oriented and component-based frameworks and model-driven development tools that facilitate the development of middleware and applications for distributed real-time and embedded (DRE) systems. He is an expert on DRE computing patterns and middleware frameworks and has published over 400 technical papers and nine books that cover a range of topics including high-performance communication software systems, parallel processing for high-speed networking protocols, quality-of-service (QoS)-enabled distributed object computing, object-oriented patterns for concurrent and distributed systems model-driven development tools. He received his PhD in

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Section: Automated Feature Selection Using a Constraint Solvermentioning

confidence: 99%

Section: Automated Feature Selection Using a Constraint Solvermentioning

confidence: 99%

Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing

White

Dougherty

Strowd

et al. 2009

Software Engineering for Self-Adaptive Systems

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“…Constraint Logic Programming (CLP) [3] has proved to be an adequate Artificial Intelligence (AI) tool for supporting the declarative geometric programming found in GeoSpecif. We have used the following advantages of the CLP language Prolog III [4]:…”

Section: Declarative Geometric Programmingmentioning

confidence: 99%

Logic programming: a tool for development of educational systems

Allen

Trilling

1995

World Conference on Computers in Education VI

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Laurent Trilling IMAG-LGI Grenoble FranceAn intelligent system for exploring geometry is described. This system utilizes a declarative approach to geometric programming wherein geometric objects and properties are specified using logical specifications. The system automatically draws the specified figures from a set of designated base points and allows the user to explore geometric properties by dragging on these base points. Since the figure is constructed using a declarative approach, there are normally more points with which you can drag the figure than there would be if the figure had been constructed with a procedural system. The system has two parameters which the user must provide: the logical specification and the set of base points. The system, GeoSpecif is described. It is also shown how logic programming has been useful in defining and implementing a dynamic system for secondary school geometry and how a new programming construct, declarative geometric programming, grew out of efforts to design and build an educational system.

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“…mathematics. and formal languages" [Cohen 1990]. The combination of logic programming with constraint satisfaction is a natural extension of traditional logic programming languages since the fundamental unification process can be viewed as a special case of constraint satisfaction; i.e., unification of f(X,a) with f(bY) is equivalent to solving f(X.a)=f(b.Y).…”

Section: Constraint Logic Programmingmentioning

confidence: 99%

Constraints Logic Programming in Knowledge-Based Planning Domains

Day¹

1992

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Constraint logic programming languages

Cited by 195 publications

References 17 publications

Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing

Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing

Logic programming: a tool for development of educational systems

Constraints Logic Programming in Knowledge-Based Planning Domains

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