ITU
Adrian Hoff

Adrian Hoff

PhD fellow

IT University of Copenhagen
Rued Langgaards Vej 7
DK-2300 Copenhagen S
Denmark

Building: 4F16-4T50

Information Desk: 72185000

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  1. 2022
  2. Published

    Experiences with Constructing and Evolving a Software Product Line with Delta-Oriented Programming

    Nieke, M., Hoff, A., Schaefer, I. & Seidl, C., 2022, Proceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS ’22). Association for Computing Machinery, (International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS)).

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  3. 2021
  4. Published

    Towards Immersive Software Archaeology: Regaining Legacy Systems’ Design Knowledge via Interactive Exploration in Virtual Reality

    Hoff, A., Nieke, M. & Seidl, C., 20 Aug 2021, Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE ’21). Association for Computing Machinery, p. 1455-1458 4 p.

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  5. Published

    Augmenting Metamodels with Seamless Support for Planning, Tracking, and Slicing Model Evolution Timelines

    Nieke, M., Hoff, A., Seidl, C. & Schaefer, I., 2021, In: Journal of Computer Languages.

    Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

  6. 2020
  7. Published

    Consistency-Preserving Evolution Planning on Feature Models

    Hoff, A., Nieke, M., Seidl, C., Halvard Sæther, E., Sandberg Motzfeldt, I., Din, C. C., Yu, I. C. & Schaefer, I., Oct 2020, Proceedings of the 24th ACM International Systems and Software Product Line Conference. Association for Computing Machinery, p. 1-12 8

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

ID: 85409565