Software is more and more developed in international cooperative efforts where project team members have different educational and cultural backgrounds and the team may even be distributed among sites in several countries. Software engineering education should also involve distributed and cross-cultural project work to prepare the future software developers for this kind of work environment. In a pilot project of two universities in Finland and in Russia a cross-cultural student team gathered experience by developing a common software product in a distributed project. While in general the project was successful, the team encountered some problems mainly due to the need to work in a foreign language and the practical limitations of remote connections

ALCHEMIST is a general purpose transformation generating environment, which supports specification, generation and execution of data transformations. ALCHEMIST allows an abstract specification of the transformation through a window-based interface and supports the generation and compilation of transformation program code from these specifications. Unlike compiler-compilers, ALCHEMIST is intended to automate building transformations between two complex representation formats and is thus especially suitable for constructing transformations between database tools, CASE tools, graphical editors or text formatters. In this paper we describe the design principles and the structure of ALCHEMIST, and demonstrate its use. We also discuss our experiences with several example transformations and present a real-life case study of using ALCHEMIST for interfacing two software development environments.

Association rules, introduced by Agrawal, Imielinski, and Swami, are rules of the form "for 90 % of the rows of the relation, if the row has value 1 in the columns in set W , then it has 1 also in column B". Efficient methods exist for discovering association rules from large collections of data. The number of discovered rules can, however, be so large that browsing the rule set and finding interesting rules from it can be quite difficult for the user. We show how a simple formalism of rule templates makes it possible to easily describe the structure of interesting rules. We also give examples of visualization of rules, and show how a visualization tool interfaces with rule templates. 1 Introduction Data mining (knowledge discovery in databases) is a field of increasing interest combining databases, artificial intelligence, and machine learning. The purpose of data mining is to facilitate understanding large amounts of data by discovering interesting regularities or exceptions (see e...

Several variants of quicksort are compared in order to find an efficient internal sorting algorithm for sorting large files in a virtual memory environment. The algorithms compared are original quicksort; ‘Esort’, which uses a fixed memory partition of two page frames; ‘Wsort’, which combines quicksort with merging and sorts one page at a time to reduce page fetches; and ‘Psort’, which uses manual replacement of pages guided by estimates of the interval to the next reference. The comparison is based on several sorting runs on different-size random-ordered files. A memory management simulator with fetch on demand and working set replacement strategy is used to achieve performance measures: the total execution time, the main memory space allocation, and the main memory space-time integral. Quicksort achieves its best performance with a relatively small page size and a very small window size. Reducing page faults by increasing the window size results in excessive space allocation. In an optimal environment, Psort gives some 30-40% smaller space-time integral than quicksort. The space allocation sizes are close to each other, but Psort needs less that half of the page fetches of quicksort. The results for Esort are close to those of quicksort. Wsort does not compete favourably with the original quicksort. In a typical virtual memory environment with a large page size and a large window size, both Esort and Psort perform remarkably better than original quicksort. The space-time integral difference of Psort and quicksort is over 50%, and it increases with an increasing file size.

Database referencing behaviour is analyzed with respect to locality features. The analysis is based on database reference strings collected from several runs of typical batch programs accessing a real database. Locality of reference is measured by the stack distance probability distribution, the number of block faults, and a locality measure based on the memory reservation size.