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Comprehending Object State via Dynamic Class Invariant Learning
Boockmann, Jan Henrik; Lüttgen, Gerald (2024): Comprehending Object State via Dynamic Class Invariant Learning, in: Dirk Beyer, Ana Cavalcanti, Dirk Beyer, u. a. (Hrsg.), Fundamental Approaches to Software Engineering : 27th International Conference, FASE 2024, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024, Luxembourg City, Luxembourg, April 6–11, 2024, Proceedings, Cham: Springer Nature Switzerland, S. 143–164, doi: 10.1007/978-3-031-57259-3_7.
Faculty/Chair:
Author:
Title of the compilation:
Fundamental Approaches to Software Engineering : 27th International Conference, FASE 2024, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024, Luxembourg City, Luxembourg, April 6–11, 2024, Proceedings
Editors:
Beyer, Dirk
Cavalcanti, Ana
Conference:
ETAPS 2024 ; Luxembourg
Publisher Information:
Year of publication:
2024
Pages:
ISBN:
978-3-031-57258-6
9783031572593
Language:
English
Type:
Conferenceobject
Activation date:
October 2, 2024
Permalink
https://fis.uni-bamberg.de/handle/uniba/98466