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VaryMinions: leveraging RNNs to identify variants in event logs.

, , , , and . MaLTeSQuE@ESEC/SIGSOFT FSE, page 13-18. ACM, (2021)

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VaryMinions: leveraging RNNs to identify variants in event logs., , , , and . MaLTeSQuE@ESEC/SIGSOFT FSE, page 13-18. ACM, (2021)A Vision to identify Architectural Smells in Self-Adaptive Systems using Behavioral Maps (short paper)., , , and . ECSA (Companion), volume 2978 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Behavioral Maps: Identifying Architectural Smells in Self-adaptive Systems at Runtime., , , and . ECSA (Tracks and Workshops), volume 13365 of Lecture Notes in Computer Science, page 159-180. Springer, (2021)Towards Feature-based ML-enabled Behaviour Location., , , and . VaMoS, page 152-154. ACM, (2024)Variability-aware Behavioural Learning.. SPLC (B), page 11-15. ACM, (2023)LIFTS: learning featured transition systems.. SPLC (B), page 1-6. ACM, (2021)An SMT-Based Concolic Testing Tool for Logic Programs., , , , , and . FLOPS, volume 12073 of Lecture Notes in Computer Science, page 215-219. Springer, (2020)