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There exists an educational gap between the software engineering education given by the Computer Science departments at universities and the requirements imposed by practical work in software projects. Even worse, this gap has presumably grown wider during recent years, as the body of knowledge that one has to master in software projects has grown. One solution to this problem is to arrange, in close cooperation between software industry and the universities, “non-scientific” training programmes that serve the needs of practical work in software projects. The Sofko programme, organized in cooperation with the universities and software industry in Tampere, is a special postgraduate education programme for project managers. This report describes its design process, course contents and some initial experiences.

Sofko is a special education program for software project managers. The program has been planned in close cooperation with universities and local software companies, and it also receives government support. In a larger context, Sofko program is one of the efforts of the Finnish government to support the decentralization of software industry away from the capital area. This report describes the background, organization and preliminary course contents of the Sofko program.

The fields of computing and software engineering are evolving rapidly. Typically, a new generation of a software based product may require 5–10 times more effort than the previous one. This is causing an increasing need for software process improvement in software companies. The improvement is impossible without retraining existing personnel. On the other hand, there seems to be a mismatch between the software engineering education given by the CS departments at universities, and the requirements imposed by practical work in software projects. This problem is difficult, or even impossible to be solved by the universities alone: An active interaction between the software industry and the universities is required. This report describes our experiences with one form of such interaction; i.e. the Sofko project manager education program.

Experimnental results are given about the performance of six sorting algorithms in a virtual memory based on the working set principle. With one exception, the algorithms are general internal sorting algorithms and not especially tuned for virtual memory. Algorithms are compared in terms of their time requirements, space requirements, and space-time integrals. The relative performances of the algorithms vary from one measure to the other. Especially in terms of a space-time integral, quicksort turns out to be the best algorithm, also in a working set virtual memory environment.

Program restructuring in a segmented virtual memory system is examined on the base of empirical data. The measure of connectivity is based on the decrease of the space-time integral caused by combining the two segments. A heuristic clustering algorithm, based on the use of effectively reduced memory reference strings, is presented. It turns out that performance problems in a segmented system are created by the large number of small segments. Restructuring is able to improve the performance of the system essentially; the optimal performance is reached with values of the memory control parameter which are one magnitude smaller than those applicable to original programs. The clusters formed do not correspond to program phases, but to smaller units of program execution; thus the clustering result supports a hierarchical model of program locality. The restructuring process is reasonably insensitive both to the memory control parameters and to the input data used.

Program behaviour characteristics were examined using data gathered from real program executions. Experiments were performed in a segmented virtual memory with a working set policy; the analyzing costs were kept low using an efficient data reduction method. Empirical results were obtained concerning the influence of the window size on program behaviour characteristics, the accuracy of some average working set size approximations and the sensitivity of program behaviour to the program's input data. These results show that some commonly used assumptions concerning program behaviour are inaccurate. Also there seem to exist “ill-behaving” programs, the behaviour of which does not correspond well with results obtained earlier. The effects of real-time delays during program execution were considered using a new simple method. As an additional experiment, segmenting and paging were compared using various performance statistics; the results seem to favour segmenting.