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Auflistung nach Autor:in "Young, Jeffrey M."

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  • Konferenzbeitrag
    Evaluating State-of-the-Art #SAT Solvers on Industrial Configuration Spaces
    (Software Engineering 2024 (SE 2024), 2024) Sundermann, Chico; Heß, Tobias; Nieke, Michael; Bittner, Paul Maximilian; Young, Jeffrey M.; Thüm, Thomas; Schaefer, Ina
  • Konferenzbeitrag
    Feature Trace Recording - Summary
    (Software Engineering 2022, 2022) Bittner, Paul Maximilian; Schultheiß, Alexander; Thüm, Thomas; Kehrer, Timo; Young, Jeffrey M.; Linsbauer, Lukas
    In this work, we report about recent research on Feature Trace Recording, originally published at the Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2021. Tracing requirements to their implementation is crucial to all stakeholders of a software development process. When managing software variability, requirements are typically expressed in terms of features, a feature being a user-visible characteristic of the software. While feature traces are fully documented in software product lines, ad-hoc branching and forking, known as clone-and-own, is still the dominant way for developing multi-variant software systems in practice. Retroactive migration to product lines suffers from uncertainties and high effort because knowledge of feature traces must be recovered but is scattered across teams or even lost. We propose a semi-automated methodology for recording feature traces proactively, during software development when the necessary knowledge is present. To support the ongoing development of previously unmanaged clone-and-own projects, we explicitly deal with the absence of domain knowledge for both existing and new source code. We evaluate feature trace recording by replaying code edit patterns from the history of two real-world product lines. Our results show that feature trace recording reduces the manual effort to specify traces.
  • Konferenzbeitrag
    Variational Satisfiability Solving: Efficiently Solving Lots of Related SAT Problems - Summary
    (Software Engineering 2023, 2023) Young, Jeffrey M.; Bittner, Paul Maximilian; Walkingshaw, Eric; Thüm, Thomas
    We report about recent research on satisfiability solving for variational domains, originally published in 2022 in the Empirical Software Engineering Journal (EMSE) within the special issue on configurable systems[ Yo22]. Incremental SAT solving is an extension of classic SAT solving that enables solving a set of related SAT problems by identifying and exploiting shared terms. However, using incremental solvers effectively is hard since performance is sensitive to the input order of subterms and results must be tracked manually. This paper translates the ordering problem to an encoding problem and automates the use of incremental solving. We introduce variational SAT solving, which differs from incremental solving by accepting all related problems as a single variational input and returning all results as a single variational output. Variational SAT solving automates the interaction with the incremental solver and enables a method to automatically optimize sharing in the input. We formalize a variational SAT algorithm, construct a prototype variational solver, and perform an empirical analysis on two real-world datasets that applied incremental solvers to software evolution scenarios. We show that the prototype solver scales better for these problems than four off-the-shelf incremental solvers while also automatically tracking individual results.