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Auflistung nach Autor:in "Krieter, Sebastian"

1 - 6 von 6
  • Konferenzbeitrag
    Compositional Analyses of Highly-Configurable Systems with Feature-Model Interfaces
    (Software Engineering 2017, 2017) Schröter, Reimar; Krieter, Sebastian; Thüm, Thomas; Benduhn, Fabian; Saake, Gunter
    Today’s software systems are often customizable by means of load-time or compile-time configuration options. These options are typically not independent and their dependencies can be specified by means of feature models. As many industrial systems contain thousands of options, the maintenance and utilization of feature models is a challenge for all stakeholders. In the last two decades, numerous approaches have been presented to support stakeholders in analyzing feature models. Such analyses are commonly reduced to satisfiability problems, which suffer from the growing number of options. While first attempts have been made to decompose feature models into smaller parts, they still require to compose all parts for analyses. We proposed the concept of a feature-model interface that only consists of a subset of features and hides all other features and dependencies. Based on a formalization of feature-model interfaces, we proved compositionality properties. We evaluated feature-model interfaces using a three-month history of an industrial fea- ture model with 18,616 features. Our results indicate performance benefits especially under evolution as often only parts of the feature model need to be analyzed again.
  • Konferenzbeitrag
    Effiziente Interaktive und Automatische Produktlinienkonfiguration
    (Ausgezeichnete Informatikdissertationen 2022 (Band D23), 2023) Krieter, Sebastian
    Moderne, hochgradig konfigurierbare Systeme umfassen eine enorme Anzahl von Varianten, die aus einer gemeinsamen Codebasis erstellt und auf spezifische Benutzeranforderungen zugeschnitten werden. Die Verwaltung und Benutzung dieser hohen Variabilität stellt sowohl die Benutzer als auch die Entwickler dieser Systeme vor Herausforderungen, da es für die meisten Systeme nicht möglich ist, alle möglichen Kombinationen von Konfigurationsoptionen zu testen oder auch nur zu berücksichtigen. In dieser Arbeit betrachten wir dieses Problem, indem wir Werkzeugunterstützung für automatische und halbautomatische Konfigurationsprozesse von konfigurierbaren Systemen untersuchen. Wir führen dazu neue Datenstrukturen, Algorithmen und Metriken ein, die sowohl die Effizienz als auch die Effektivität bisherige Ansätze deutlich steigern. Damit erleichtern wir den automatischen und halbautomatischen Konfigurationsprozess, insbesondere im Bezug auf das Testens und der Analyse konfigurierbarer Systeme.
  • Konferenzbeitrag
    Feature Modeling and Development with FeatureIDE
    (Modellierung 2018, 2018) Thüm, Thomas; Leich,Thomas; Krieter, Sebastian
    FeatureIDE is an open-source framework to model, develop, and analyze feature-oriented software product lines. It is mainly developed in a cooperation between TU Braunschweig, University of Magdeburg, and Metop GmbH. Nevertheless, many other institutions contributed to it in the past decade. Goal of this tutorial is to illustrate how FeatureIDE can be used to develop software around end-user features. We will show how feature models are connected to and synchronized with other artifacts. The hands-on tutorial will be highly interactive and is devoted to practitioners facing problems with variability, lecturers teaching product lines, and researchers who want to safe resources in building product-line tools.
  • Konferenzbeitrag
    Propagating Configuration Decisions with Modal Implication Graphs
    (Software Engineering and Software Management 2019, 2019) Krieter, Sebastian; Thüm, Thomas; Schulze, Sandro; Schroeter, Reimar; Saake, Gunter
    This work was originally published as “Propagating Configuration Decisions with Modal Implication Graphs” at the 40th International Conference on Software Engineering 2018 [Kr18].
  • Konferenzbeitrag
    Tseitin or not Tseitin? The Impact of CNF Transformations on Feature-Model Analyses
    (Software Engineering 2023, 2023) Kuiter, Elias; Krieter, Sebastian; Sundermann, Chico; Thüm, Thomas; Saake, Gunter
    This work was published at the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2022 [Ku22]. Feature modeling is widely used to systematically model features of variant-rich software systems and their dependencies. By translating feature models into propositional formulas and analyzing them with solvers, a wide range of automated analyses across all phases of the software development process become possible. Most solvers only accept formulas in conjunctive normal form (CNF), so an additional transformation of feature models is often necessary. However, it is unclear whether this transformation has a noticeable impact on analyses. We compare three transformations for bringing feature-model formulas into CNF. We analyze which transformation can be used to correctly perform feature-model analyses and evaluate three CNF transformation tools on a corpus of 22 real-world feature models. Our empirical evaluation illustrates that some CNF transformations do not scale to complex feature models or even lead to wrong results for model-counting analyses. Further, the choice of the CNF transformation can substantially influence the performance of subsequent analyses.
  • Konferenzbeitrag
    variED: An Editor for Collaborative, Real-Time Feature Modeling
    (Software Engineering 2023, 2023) Kuiter, Elias; Krieter, Sebastian; Krüger, Jacob; Saake, Gunter; Leich, Thomas
    This work was published in Empirical Software Engineering (EMSE) 26, 2 (2021) [Ku21]. Feature models are a helpful means to document, manage, maintain, and configure the variability of a software system. Various stakeholders in an organization may get involved in modeling the features in such a software system. Currently, collaboration in such a scenario can only be done with face-to-face meetings or by combining single-user feature-model editors with additional communication and version-control systems. While face-to-face meetings are often costly and impractical, using version-control systems can cause merge conflicts and inconsistency within a model. Advanced tools that solve these problems by enabling collaborative, real-time feature modeling, analogous to Google Docs or Overleaf for text editing, are missing. We describe the formal foundations of collaborative, real-time feature modeling; a conflict resolution algorithm; proofs that our formalization converges and preserves causality as well as user intentions; a prototype; and the results of an empirical evaluation to assess the prototype’s usability. Our contributions provide the basis for advancing existing feature-modeling practices to support collaborative feature modeling. Our prototype is considered helpful and valuable by 17 users, also indicating opportunities for new research directions.