CGAL is a Computational Geometry Algorithms Library written in C++, which is being developed by research groups in Europe and Israel. The goal is to make the large body of geometric algorithms developed in the field of computational geometry available for industrial application. We discuss the major design goals for CGAL, which are correctness, flexibility, ease-of-use, efficiency, and robustness, and present our approach to reach these goals. Generic programming using templates in C++ plays a central role in the architecture of CGAL. We give a short introduction to generic programming in C++, compare it to the object-oriented programming paradigm, and present examples where both paradigms are used effectively in CGAL. Moreover, we give an overview of the current structure of the CGAL-library and consider software engineering aspects in the CGAL-project. Copyright c ○ 1999 John Wiley & Sons, Ltd. KEY WORDS: computational geometry; software library; C++; generic programming;

Evaluating the design of a distributed application is difficult but provides useful information for program development and maintenance. In distributed debugging, for example, processes are often groupedtogether and treated as one entity to reduce the debugging complexity. We previously identified multiple approaches to automatic process clustering and prototypical tools implementing these approaches have been developed. The process clusters derived with these tools have been evaluatedbycomparing them to the author's understanding of the application design. This paper discusses a quantitative measureforprocess cluster evaluation. The measure uses information derivedbya static source analysis as well as information about interprocess communication during the application execution. Experiments show that the resulting quantitative evaluation conforms with a human evaluation of the same clusters.

Debugging distributed applications is very difficult, due to a number of problems. To manage the inherent complexity of distributed applications, the use of abstractions is proposed. One frequently performed abstraction is to group processes into clusters. We describe an approach to derive clustering rules from well--known programming paradigms for distributed programming. Programming paradigms determine how we think about problems and their implementation. They shape, among other things, the application structure. This paper identifies frequently used programming paradigms for distributed computing. Likely application structures resulting from the use of these paradigms are discussed and captured in process clustering rules. A quantitative measure for process cluster evaluation is presented and applied to clusters derived for Hermes applications. The results provide insight into the relative strength of the process clustering rules. 1 Introduction Distributed applications have a numb...