Abstract We analyze the matching problem for bigraphs. In particular, we present a sound and complete inductive characterization of matching in bigraphs with binding. Our results yield a specification for a provably correct matching algorithm, as needed by our prototype tool implementing bigraphical reactive systems.

This showcase paper describes the Global Interaction Research Initiative - GIRI - recently inaugurated at the IT University of Copenhagen. It presents the motivation for this initiative, namely that the use of information technology is the core enabling factor for global collaboration and business. We argue that there is a fundamental need for understanding and providing next generation technologies for this ultra large-scale interaction paradigm. GIRI is organized around a set of research themes and projects, focusing on different application areas. Themes and projects are loosely coupled in the sense that each research project is defined in its own right with a specific set of challenges, vision, approach, partners, and funding scheme. At the time of writing, GIRI has 3 research themes and are hosting 6 projects, but these numbers are expected to increase as GIRI grows. GIRI is an open research initiative, and we invite other researchers to join.

Service discovery is one of the key tasks in SOA, locating a particular or a series of services by matching a user query with service advertisement in service repository. It's crucial to the automation and intelligence of service invocation, achieving better user-experience of QoS. However, key-word based syntactic matchmaker currently fails to provide a satisfied service discovery mechanism. Therefore, this paper proposes a RS-CASD (Rough Set-based Context-Aware Service Discovery) Framework that explores context information and ontology model to semantically enhance the user query and service advertisement for more fulfilled service discovery. Rough set theory is applied to deal with inexact or uncertain functional and contextual properties and extraction of context rules from historical records.

Recent research suggests that the goal of fully automatic and reliable program generation for a broad range of applications is coming nearer to feasibility. However, several interesting and challenging problems remain to be solved before it becomes a reality. Solving them is alsonecessary,if we hope ever to elevate software engineering from its current state (a highly developed handiwork) into a successful branch of engineering, capable of solving a wide range of new problems by systematic, well-automated and well-founded methods.A key problem in all program generation isterminationof the generation process. This article focuses on off-line partial evaluation and describes recent progress towards automatically solving the termination problem, first for individual programs, and then for specializers and “generating extensions,” the program generators that most offline partial evaluators produce.The technique is based onsize-change graphsthat approximate the changes in parameter sizes at function calls. We formulate a criterion,bounded anchoring,for detecting parameters known to be bounded during specialization: a bounded parameter can act as ananchorfor other parameters. Specialization points necessary for termination are computed by adding a parameter that tracks call depth, and then selecting a specialization point in every call loop where it is unanchored. By generalizing all unbounded parameters, we compute a binding-time division which together with the set of specialization pointsguaranteestermination.Contributions of this article include a proof, based on the operational semantics of partial evaluation with memoization, that the analysis guarantees termination; and an in-depth description of safety of the increasing size approximation operator required for termination analysis in partial evaluation.Initial experiments with a prototype shows that the analysis overall yields binding-time divisions that can achieve a high degree of specialization, while still guaranteeing termination.The article ends with a list of challenging problems whose solution would bring the community closer to the goal of broad-spectrum, fully automatic and reliable program generation.

Recent research suggests that the goal of fully automatic and reliable program generation for a broad range of applications is coming nearer to feasibility. However, several interesting and challenging problems remain to be solved before it becomes a reality.We first discuss the relations between problem specifications and their solutions in program form, and then narrow the discussion to an important special case: program transformation. Although the goal of fully automatic program generation is still far from fully achieved, there has been some success in a special case: partial evaluation, also known as program specialization.A key problem in all program generation is termination of the generation process. This paper (See the GPCE'02 proceedings for the full paper.} describes recent progress towards automatically solving the termination problem, first for individual programs, and then for specializers and "generating extensions," the program generators that most offline partial evaluators produce.

Recent research suggests that the goal of fully automatic and reliable program generation for a broad range of applications is coming nearer to feasibility. However, several interesting and challenging problems remain to be solved before it becomes a reality. .We first discuss the relations between problem specifications and their solutions in program form, and then narrow the discussion to an important special case: program transformation. Although the goal of fully automatic program generation is still far from fully achieved, there has been some success in a special case: partial evaluation, also known as program specialization.A key problem in all program generation is termination of the generation process. This paper describes recent progress towards automatically solving the termination problem, first for individual programs, and then for specializers and "generating extensions," the program generators that most offline partial evaluators produce.