@book{BarkowskyGiese2023, author = {Barkowsky, Matthias and Giese, Holger}, title = {Triple graph grammars for multi-version models}, number = {155}, isbn = {978-3-86956-556-9}, issn = {1613-5652}, doi = {10.25932/publishup-57399}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-573994}, publisher = {Universit{\"a}t Potsdam}, pages = {28 -- 28}, year = {2023}, abstract = {Like conventional software projects, projects in model-driven software engineering require adequate management of multiple versions of development artifacts, importantly allowing living with temporary inconsistencies. In the case of model-driven software engineering, employed versioning approaches also have to handle situations where different artifacts, that is, different models, are linked via automatic model transformations. In this report, we propose a technique for jointly handling the transformation of multiple versions of a source model into corresponding versions of a target model, which enables the use of a more compact representation that may afford improved execution time of both the transformation and further analysis operations. Our approach is based on the well-known formalism of triple graph grammars and a previously introduced encoding of model version histories called multi-version models. In addition to showing the correctness of our approach with respect to the standard semantics of triple graph grammars, we conduct an empirical evaluation that demonstrates the potential benefit regarding execution time performance.}, language = {en} } @book{BarkowskyGiese2023, author = {Barkowsky, Matthias and Giese, Holger}, title = {Modular and incremental global model management with extended generalized discrimination networks}, number = {154}, isbn = {978-3-86956-555-2}, issn = {1613-5652}, doi = {10.25932/publishup-57396}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-573965}, publisher = {Universit{\"a}t Potsdam}, pages = {63 -- 63}, year = {2023}, abstract = {Complex projects developed under the model-driven engineering paradigm nowadays often involve several interrelated models, which are automatically processed via a multitude of model operations. Modular and incremental construction and execution of such networks of models and model operations are required to accommodate efficient development with potentially large-scale models. The underlying problem is also called Global Model Management. In this report, we propose an approach to modular and incremental Global Model Management via an extension to the existing technique of Generalized Discrimination Networks (GDNs). In addition to further generalizing the notion of query operations employed in GDNs, we adapt the previously query-only mechanism to operations with side effects to integrate model transformation and model synchronization. We provide incremental algorithms for the execution of the resulting extended Generalized Discrimination Networks (eGDNs), as well as a prototypical implementation for a number of example eGDN operations. Based on this prototypical implementation, we experiment with an application scenario from the software development domain to empirically evaluate our approach with respect to scalability and conceptually demonstrate its applicability in a typical scenario. Initial results confirm that the presented approach can indeed be employed to realize efficient Global Model Management in the considered scenario.}, language = {en} } @article{BarkowskyGiese2020, author = {Barkowsky, Matthias and Giese, Holger}, title = {Hybrid search plan generation for generalized graph pattern matching}, series = {Journal of logical and algebraic methods in programming}, volume = {114}, journal = {Journal of logical and algebraic methods in programming}, publisher = {Elsevier}, address = {New York}, issn = {2352-2208}, doi = {10.1016/j.jlamp.2020.100563}, pages = {29}, year = {2020}, abstract = {In recent years, the increased interest in application areas such as social networks has resulted in a rising popularity of graph-based approaches for storing and processing large amounts of interconnected data. To extract useful information from the growing network structures, efficient querying techniques are required. In this paper, we propose an approach for graph pattern matching that allows a uniform handling of arbitrary constraints over the query vertices. Our technique builds on a previously introduced matching algorithm, which takes concrete host graph information into account to dynamically adapt the employed search plan during query execution. The dynamic algorithm is combined with an existing static approach for search plan generation, resulting in a hybrid technique which we further extend by a more sophisticated handling of filtering effects caused by constraint checks. We evaluate the presented concepts empirically based on an implementation for our graph pattern matching tool, the Story Diagram Interpreter, with queries and data provided by the LDBC Social Network Benchmark. Our results suggest that the hybrid technique may improve search efficiency in several cases, and rarely reduces efficiency.}, language = {en} } @inproceedings{KurbelNowakAzodietal.2015, author = {Kurbel, Karl and Nowak, Dawid and Azodi, Amir and Jaeger, David and Meinel, Christoph and Cheng, Feng and Sapegin, Andrey and Gawron, Marian and Morelli, Frank and Stahl, Lukas and Kerl, Stefan and Janz, Mariska and Hadaya, Abdulmasih and Ivanov, Ivaylo and Wiese, Lena and Neves, Mariana and Schapranow, Matthieu-Patrick and F{\"a}hnrich, Cindy and Feinbube, Frank and Eberhardt, Felix and Hagen, Wieland and Plauth, Max and Herscheid, Lena and Polze, Andreas and Barkowsky, Matthias and Dinger, Henriette and Faber, Lukas and Montenegro, Felix and Czach{\´o}rski, Tadeusz and Nycz, Monika and Nycz, Tomasz and Baader, Galina and Besner, Veronika and Hecht, Sonja and Schermann, Michael and Krcmar, Helmut and Wiradarma, Timur Pratama and Hentschel, Christian and Sack, Harald and Abramowicz, Witold and Sokolowska, Wioletta and Hossa, Tymoteusz and Opalka, Jakub and Fabisz, Karol and Kubaczyk, Mateusz and Cmil, Milena and Meng, Tianhui and Dadashnia, Sharam and Niesen, Tim and Fettke, Peter and Loos, Peter and Perscheid, Cindy and Schwarz, Christian and Schmidt, Christopher and Scholz, Matthias and Bock, Nikolai and Piller, Gunther and B{\"o}hm, Klaus and Norkus, Oliver and Clark, Brian and Friedrich, Bj{\"o}rn and Izadpanah, Babak and Merkel, Florian and Schweer, Ilias and Zimak, Alexander and Sauer, J{\"u}rgen and Fabian, Benjamin and Tilch, Georg and M{\"u}ller, David and Pl{\"o}ger, Sabrina and Friedrich, Christoph M. and Engels, Christoph and Amirkhanyan, Aragats and van der Walt, Est{\´e}e and Eloff, J. H. P. and Scheuermann, Bernd and Weinknecht, Elisa}, title = {HPI Future SOC Lab}, editor = {Meinel, Christoph and Polze, Andreas and Oswald, Gerhard and Strotmann, Rolf and Seibold, Ulrich and Schulzki, Bernhard}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-102516}, pages = {iii, 154}, year = {2015}, abstract = {Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Erm{\"o}glichung und F{\"o}rderung des Austausches zwischen Forschungsgemeinschaft und Industrie. Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei f{\"u}r Forschungszwecke zur Verf{\"u}gung gestellt. Dazu z{\"a}hlen teilweise noch nicht am Markt verf{\"u}gbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren w{\"a}ren, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien. In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2015 vorgestellt. Ausgew{\"a}hlte Projekte stellten ihre Ergebnisse am 15. April 2015 und 4. November 2015 im Rahmen der Future SOC Lab Tag Veranstaltungen vor.}, language = {en} }