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SEAMS 2022
Mon 23 - Tue 24 May 2022
co-located with ICSE 2022
Thu 19 May 2022 12:30 - 12:35 at SEAMS room - Analysis and Planning Chair(s): Gabriel A. Moreno, Genaína Nunes Rodrigues

video link

To assure performance on the fly, planning is arguably one of the most important steps for self-adaptive systems (SASs), especially when they are highly configurable with a daunting number of adaptation options. However, there has been little understanding of the planning landscape or ways by which it can be analyzed. This inevitably creates barriers to the design of better and tailored planners for SASs. In this paper, we showcase how the planning landscapes of SASs can be quantified and reasoned, particularly with respect to the different environments. We do so by using the notions and metrics in fitness landscape analysis — a well-established field from the optimization community. Through studying four real-world SASs and 14 different environments that are of diverse domains, scales, and search spaces, we found that (1) the SAS planning landscapes often provide strong guidance to the planner, but their ruggedness and multi-modality can be the major obstacle; (2) the extents of guidance and number of global/local optima are sensitive to the changing environment, but not the ruggedness of the surface; (3) the local optima are often closer to the global optimum than other random points; and (4) there are considerable (and useful) overlaps on the global/local optima between landscapes under different environments. We then summarize what our findings mean and their potential implications to the future work of planner designs for SASs. To promote open science, we release all the code and data at https://doi.org/10.5281/zenodo.5866808.

Thu 19 May

Displayed time zone: Eastern Time (US & Canada) change

12:30 - 14:00
Analysis and Planning SEAMS 2022 at SEAMS room
Chair(s): Gabriel A. Moreno Carnegie Mellon University, USA, Genaína Nunes Rodrigues University of Brasília
12:30
5m
Paper
Planning Landscape Analysis for Self-Adaptive SystemsShort Research Paper
SEAMS 2022
Tao Chen Loughborough University
Pre-print
12:40
5m
Paper
PRESTO: Predicting System-level Disruptions through Parametric Model CheckingShort Research Paper
SEAMS 2022
Xinwei Fang University of York, UK, Radu Calinescu University of York, UK, Colin Paterson University of York, Julie Wilson University of York
Pre-print
12:45
5m
Paper
Run-Time Adaptation of Quality Attributes for Automated PlanningShort Research Paper
SEAMS 2022
Rebekka Wohlrab Carnegie Mellon University, Rômulo Meira-Góes Carnegie Mellon University, Michael Vierhauser Johannes Kepler University Linz
Pre-print
12:50
5m
Paper
Towards Model Co-evolution Across Self-Adaptation Steps for Combined Safety and Security AnalysisShort Research Paper
SEAMS 2022
Thomas Witte Ulm University, Raffaela Groner Ulm University, Alexander Raschke Ulm University, Matthias Tichy Ulm University, Germany, Irdin Pekaric University of Innsbruck, Michael Felderer University of Innsbruck
Pre-print
12:55
65m
Panel
Discussion
SEAMS 2022


Information for Participants
Thu 19 May 2022 12:30 - 14:00 at SEAMS room - Analysis and Planning Chair(s): Gabriel A. Moreno, Genaína Nunes Rodrigues
Info for room SEAMS room:

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