A Type-Safe Model of Adaptive Object Groups

Services are autonomous, self-describing, technology-neutral software units that can be described, published, discovered, and composed into software applications at runtime. Designing software services and composing services in order to form applications or composite services requires abstractions beyond those found in typical object-oriented programming languages. This paper explores service-oriented abstractions such as service adaptation, discovery, and querying in an object-oriented setting. We develop a formal model of adaptive object-oriented groups which offer services to their environment. These groups fit directly into the object-oriented paradigm in the sense that they can be dynamically created, they have an identity, and they can receive method calls. In contrast to objects, groups are not used for structuring code. A group exports its services through interfaces and relies on objects to implement these services. Objects may join or leave different groups. Groups may dynamically export new interfaces, they support service discovery, and they can be queried at runtime for the interfaces they support. We define an operational semantics and a static type system for this model of adaptive object groups, and show that well-typed programs do not cause method-not-understood errors at runtime.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

Mesmerizer: A Effective Tool for a Complete Peer-to-Peer Software Development Life-cycle

In this paper we present what are, in our experience, the best practices in Peer-To-Peer(P2P) application development and how we combined them in a middleware platform called Mesmerizer. We explain how simulation is an integral part of the development process and not just an assessment tool. We then present our component-based event-driven framework for P2P application development, which can be used to execute multiple instances of the same application in a strictly controlled manner over an emulated network layer for simulation/testing, or a single application in a concurrent environment for deployment purpose. We highlight modeling aspects that are of critical importance for designing and testing P2P applications, e.g. the emulation of Network Address Translation and bandwidth dynamics. We show how our simulator scales when emulating low-level bandwidth characteristics of thousands of concurrent peers while preserving a good degree of accuracy compared to a packet-level simulator

A Modular Toolkit for Distributed Interactions

We discuss the design, architecture, and implementation of a toolkit which supports some theories for distributed interactions. The main design principles of our architecture are flexibility and modularity. Our main goal is to provide an easily extensible workbench to encompass current algorithms and incorporate future developments of the theories. With the help of some examples, we illustrate the main features of our toolkit.Comment: In Proceedings PLACES 2010, arXiv:1110.385

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Kickstarting Choreographic Programming

We present an overview of some recent efforts aimed at the development of Choreographic Programming, a programming paradigm for the production of concurrent software that is guaranteed to be correct by construction from global descriptions of communication behaviour

CompendiumLD – a tool for effective, efficient and creative learning design

Developers and teachers go through a complex decision making process when designing new learning activities – working towards an effective pedagogical mix, combining resources, tools, student and tutor support. This paper describes CompendiumLD, a prototype tool we have built to support practitioners through the process of designing learning activities. We describe how the tool fits into our vision of a dynamic, interactive set of resources and system tools to support effective, efficient and creative learning design. It describes CompendiumLD's features and explains the rationale behind their development. It shows how the tool is intended to aid designers make choices, and plan developments, facilitating creativity and efficiency in the design process. In our conclusions we consider how such a system can support the design of effective learning activities