http://dl.gi.de/handle/20.500.12116/19969 Tue, 21 Jul 2026 13:20:57 GMT 2026-07-21T13:20:57Z http://dl.gi.de:80/bitstream/id/25fbf3b2-2085-4074-962a-d7d0c91c5bf3/ http://dl.gi.de/handle/20.500.12116/19969 http://dl.gi.de/handle/20.500.12116/18381 Supporting the context establishment according to ISO 27005 using patterns Beckers, Kristian; Faßbender, Stephan Jähnichen, Stefan; Rumpe, Bernhard; Schlingloff, Holger The documentation of an information and communication system according to the requirements of the ISO 27005 standard is difficult, because the standard only provides sparse descriptions. We propose the use of specific patterns for the ISO 27005 standard, which can be instantiated for any given information and communication system. Each of our pattern will cover a section of the standard. In this paper we present one pattern for Section 7 of the standard, the context establishment. This is one of the initial steps of the standards and it is the input for following steps, e.g., the asset identification. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18381 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18378 Fehlalarmfreie Abstraktion in ISO-C konformer Semantik Richter, Dirk; Hoffmann, Roberto Jähnichen, Stefan; Rumpe, Bernhard; Schlingloff, Holger Viele Aussagen zum Programmverhalten sind in turingmächtigen Programmiersprachen unentscheidbar (Rice Theorem). Mittels Abstraktion vom Programmverhalten können nicht-turingmächtige Modelle automatisch erzeugt werden. Modelle in Form von symbolischen Kellersystemen (SPDS) erlauben eine so präzise Darstellung des Programmverhaltens, sodass eine ISO-C konforme Semantik möglich ist [RB12, KZR09]. Allerdings führen präzisere Darstellungen stets auch zu komplexeren und umfangreicheren Modellen. Dies erschwert Software-Modellprüfung, modellbasiertes Testen und Testdatenund Codegenerierung. Mehr Abstraktion führt hingegen zu kleineren Modellen, allerdings auch zu mehr Fehlalarmen. Ziel dieser Arbeit ist es, bezüglich temporaler Aussagen unwichtige Teile eines SPDS zu identifizieren und von diesen Teilen so zu abstrahieren, dass keine Fehlalarme entstehen. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18378 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18377 Making MPI intelligent Tetzlaff, Dirk; Glesner, Sabine Jähnichen, Stefan; Rumpe, Bernhard; Schlingloff, Holger Mapping parallel applications to multi-processor architectures requires information about the execution times of the concurrent processes to find an optimal allocation and must take into account the interprocessor communication at runtime, whose overheads have emerged as the major performance limitation. However, both information cannot be statically known in advance. In this paper we present a sophisticated approach for mapping parallel MPI applications to concurrent architectures using machine learning techniques. This automatically generates heuristics that provide the compiler with knowledge of the considered runtime behavior, hence yielding more precise heuristics than those generated by pure static analyses. The heuristics can be used to direct the runtime environment of MPI, which enables the reallocation of processes to other processors at runtime and, furthermore, results in a better initial allocation of MPI processes. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18377 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18380 Exploring software variance with hypermodelling – an exemplary approach Frey, Tim; Köppen, Veit Jähnichen, Stefan; Rumpe, Bernhard; Schlingloff, Holger Framework manufacturers face the challenge to determine which parts of frameworks are used and varied. Application developers want to know on which framework elements their application is depending. Currently, programs need to be parsed to extract information about framework usage what consumes time and effort and makes information mining inflexible. Hypermodelling utilizes Data Warehouse technologies for source code investigations to overcome the current limitations. In this paper, we demonstrate that Hypermodelling is suitable to explore software variance. We present reports based on real application data of one project example to reveal multiple facts about the software variance. We show visualizations at different granularity levels. This supports our theory that Hypermodelling can be used to explore software variance in an easy way. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18380 2012-01-01T00:00:00Z