Abstract
In this paper, we propose an automata-based method for modeling the problem of communicating with devices operating in configurations which are uncertain, but where certain information is given about the possible space of configurations, as well as probabilities for the various configuration choices. Drawing inspiration from feature models for describing configurability, an extensible automata model is described, and two decision problems modeling the question of deciding the most likely configuration (as a set of extensions) for a given communicating device are given. A series of hardness results (the entirely general problems both being NP-complete) and efficient algorithms for relevant restricted cases are then given.
Keywords
- Hardness Results
- Uncertain Configuration
- Monotonic Weight
- Full-featured Model
- Feature-oriented Programming (FOP)
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes
- 1.
The devices as eventually defined will state the “outright” probability of a feature, e.g. feature X has a 80% chance of being included, but as this probability does not account for how the feature may interact with other features (e.g. X cannot be combined with Y, which is very likely) it is often better for intuition to think about it as including feature X causing a 20% drop of probability.
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Acknowledgements
This work is based on the research supported in part by the National Research Foundation of South Africa (Grant Number 115007).
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Berglund, M., Schaefer, I. (2018). An Automata-Based View on Configurability and Uncertainty. In: Fischer, B., Uustalu, T. (eds) Theoretical Aspects of Computing – ICTAC 2018. ICTAC 2018. Lecture Notes in Computer Science(), vol 11187. Springer, Cham. https://doi.org/10.1007/978-3-030-02508-3_5
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