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Programs are often subjected to significant optimizing and parallelizing transformations based on extensive dependence analysis. Formal validation of such transformations needs modelling paradigms which can capture both control and data dependences in the program vividly. Being value-based with an inherent scope of capturing parallelism, the untimed coloured Petri net (CPN) models, reported in the literature, fit the bill well; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like sequential control flow graphs (CFGs). In this work, an efficient path-based equivalence checking method for CPN models of programs on integers is presented. Extensive experimentation has been carried out on several sequential and parallel examples. Complexity and correctness issues have been treated rigorously for the method.
Zum Thema "Quo vadis, Modellierung?" hält Prof. Dr. Holger Giese am 11. Dezember 2008 seine Antrittsvorlesung an der Universität Potsdam. Der Wissenschaftler bekleidet eine Professur für Systemanalyse und Modellierung. Es handelt sich um eine gemeinsame Berufung der Universität Potsdam mit dem Hasso-Plattner- Institut für Softwaresystemtechnik an der Universität Potsdam. Seit den Anfängen der Informatik vollzieht sich die Entwicklung von detaillierten, lösungsorientierten und eher technisch geprägten Modellen hin zu solchen, die immer abstrakter und eher an den Problemen beziehungsweise Anwendungsbereichen orientiert sind. Diese ermöglichen es, die Komplexität heutiger Systeme besser zu beherrschen. Der Einsatz führt in einigen Anwendungsbereichen heute schon zu bedeutend höherer Produktivität und Qualität sowie geringeren Entwicklungszeiten. Anderseits hat sich aber auch in anderen Anwendungsgebieten gezeigt, dass die ständige Anpassung der Software an sich ändernde Anforderungen oder Organisationsstrukturen dazu führt, dass in frühen Entwicklungsphasen entstandene Modelle in der Praxis oft sehr schnell nicht mehr mit der Software übereinstimmen. In seiner Antrittsvorlesung will Holger Giese diese Entwicklung Revue passieren lassen und der Frage nachgehen, was dies für die Zukunft der Modellierung bedeutet, mit welchen aktuellen Ansätzen man diesem Problem zu begegnen versucht und welche zukünftigen Entwicklungen für die Modellierung zu erwarten sind.
Today, software has become an intrinsic part of complex distributed embedded real-time systems. The next generation of embedded real-time systems will interconnect the today unconnected systems via complex software parts and the service-oriented paradigm. Due to these interconnections, the architecture of systems can be subject to changes at run-time, e.g. when dynamic binding of service end-points is employed or complex collaborations are established dynamically. However, suitable formalisms and techniques that allow for modeling and analysis of timed and probabilistic behavior of such systems as well as of their structure dynamics do not exist so far. To fill the identified gap, we propose Probabilistic Timed Graph Transformation Systems (PTGTSs) as a high-level description language that supports all the necessary aspects of structure dynamics, timed behavior, and probabilistic behavior. We introduce the formal model of PTGTSs in this paper as well as present and formally verify a mapping of models with finite state spaces to probabilistic timed automata (PTA) that allows to use the PRISM model checker to analyze PTGTS models with respect to PTCTL properties. (C) 2018 Elsevier Inc. All rights reserved.
Evaluating the performance of self-adaptive systems (SAS) is challenging due to their complexity and interaction with the often highly dynamic environment. In the context of self-healing systems (SHS), employing simulators has been shown to be the most dominant means for performance evaluation. Simulating a SHS also requires realistic fault injection scenarios. We study the state of the practice for evaluating the performance of SHS by means of a systematic literature review. We present the current practice and point out that a more thorough and careful treatment in evaluating the performance of SHS is required.
The next generation of advanced mechatronic systems is expected to enhance their functionality and improve their performance by context-dependent behavior. Therefore, these systems require to represent information about their complex environment and changing sets of collaboration partners internally. This requirement is in contrast to the usually assumed static structures of embedded systems. In this paper, we present a model-driven approach which overcomes this situation by supporting dynamic data structures while still guaranteeing that valid worst-case execution times can be derived. It supports a flexible resource manager which avoids to operate with the prohibitive coarse worst-case boundaries but instead supports to run applications in different profiles which guarantee different resource requirements and put unused resources in a profile at other applications' disposal. By supporting the proper estimation of worst case execution time (WCET) and worst case number of iteration (WCNI) at runtime, we can further support to create new profiles, add or remove them at runtime in order to minimize the over-approximation of the resource consumption resulting from the dynamic data structures required for the outlined class of advanced systems.
The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. The engine often describes the adaptation by runtime models representing the adaptable software and by activities such as analysis and planning that use these models. To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. A runtime megamodel is a specific model capturing runtime models and adaptation activities. In this article, we go one step further and present an executable modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops explicit at a higher level of abstraction and it enables solutions where multiple feedback loops interact or operate on top of each other and self-adaptation co-exists with offline adaptation for evolution.
Incremental View Maintenance for Deductive Graph Databases Using Generalized Discrimination Networks
(2016)
Nowadays, graph databases are employed when relationships between entities are in the scope of database queries to avoid performance-critical join operations of relational databases. Graph queries are used to query and modify graphs stored in graph databases. Graph queries employ graph pattern matching that is NP-complete for subgraph isomorphism. Graph database views can be employed that keep ready answers in terms of precalculated graph pattern matches for often stated and complex graph queries to increase query performance. However, such graph database views must be kept consistent with the graphs stored in the graph database. In this paper, we describe how to use incremental graph pattern matching as technique for maintaining graph database views. We present an incremental maintenance algorithm for graph database views, which works for imperatively and declaratively specified graph queries. The evaluation shows that our maintenance algorithm scales when the number of nodes and edges stored in the graph database increases. Furthermore, our evaluation shows that our approach can outperform existing approaches for the incremental maintenance of graph query results.