Problem Solving Environments (PSEs) can be defined as integrated computing environments for developing, executing,
and analysing applications in a specific domain. They provide a set of user-friendly mechanisms and tools that allow
to "compose" an application, by gluing together, using some kind of problem-oriented language, different building blocks.
Such building blocks range from libraries and application codes, to tools for I/O, data visualization and analysis, and
interactive steering. PSEs may also incorporate some form of knowledge, in order to assist the users in formulating,
solving and analysing their problems. The main motivation for developing PSEs is that they enable to build applications
without dealing with most of the details related to hardware and software architectures, to solution algorithms and their
implementations, and to analysis and monitoring tools, thus allowing end-users to concentrate on the application problems
to be solved. PSEs can be used for different purposes, such as modelling and simulation, design optimisation, rapid
prototyping, and decision support.
PSEs have undergone a significant evolution in the last decade, to take into account the rapid changes in hardware and software and the requirements of applications. In particular, the concept of Multi-disciplinary PSE (MPSE) has emerged, which reflects the multi-physics and multi-disciplinary nature of today's advanced applications and the need of combining hardware, software, data and human skills, that are usually distributed over a network and across different organizations. A MPSE has been defined as a framework and software kernel for combining PSEs for tailored, flexible, multi-disciplinary applications, and is naturally thought as network or Grid-enabled.
Developing the above fully integrated PSEs is a difficult and costly task, requiring different expertise and a large man effort. An answer to this problem can be given by PSE toolkits, conceived as general frameworks that provide tools for building and deploying specific PSEs and MPSEs. An increasing activity in this area has been observed, which is devoted to defining and implementing architectures for PSE toolkits.
Research and development in the field of PSEs is so active that several environments are available which can be "classified" as PSEs. Nevertheless, more research is needed to realise fully integrated PSEs, enabling more complex simulations, higher levels of abstraction and more effective cooperation among multiple users in distributed collaborative environments. The exploitation of technologies such as parallel and distributed computing, component-based software engineering, advanced interactive visualization, knowledge discovery, and Grid computing plays a fundamental role in pursuing this goal.
This topic addresses multiple aspects of research on PSEs, including design and implementation issues, exploitation of enabling technologies, applications, and education issues.
Prof. Peter Sloot
Section Computational Science
Faculty of Science
University of Amsterdam
Amsterdam, The Netherlands
Prof. Elias Houstis
Department of Computer and Communications Engineering
University of Thessaly
and Department of Computer Sciences
West Lafayette, IN, USA
Prof. Daniela di Serafino
Department of Mathematics
Second University of Naples