You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Given a set of interacting components with non-deterministic variable update and given safety requirements, the goal of priority synthesis is to restrict, by means of priorities, the set of possible interactions in such a way as to guarantee the given safety conditions for all possible runs. In distributed priority synthesis we are interested in obtaining local sets of priorities, which are deployed in terms of local component controllers sharing intended next moves between components in local neighborhoods only. These possible communication paths between local controllers are specified by means of a communication architecture. We formally define the problem of distributed priority synthesis in terms of a multi-player safety game between players for (angelically) selecting the next transition of the components and an environment for (demonically) updating uncontrollable variables; this problem is NP-complete. We propose several optimizations including a solution-space exploration based on a diagnosis method using a nested extension of the usual attractor computation in games together with a reduction to corresponding SAT problems. When diagnosis fails, the method proposes potential candidates to guide the exploration. These optimized algorithms for solving distributed priority synthesis problems have been integrated into our VissBIP framework. An experimental validation of this implementation is performed using a range of case studies including scheduling in multicore processors and modular robotics.

Cited Abstract(s):
[1]: We present the tool Sycraft (SYmboliC synthesizeR and Adder of Fault-Tolerance). In Sycraft , a distributed fault-intolerant program is specified in terms of a set of processes and an invariant. Each process is specified as a set of actions in a guarded command language, a set of variables that the process can read, and a set of variables that the process can write. Given a set of fault actions and a specification, the tool transforms the input distributed fault-intolerant program into a distributed fault-tolerant program via a symbolic implementation of respective algorithms.

[2]: In this paper, we concentrate on automated synthesis of fault recovery mechanism for fault-intolerant component-based models that encompass a cyber-physical system. We define the notion of fault recovery for cyber-physical component-based models. We also present synthesis constraints that preserve the correctness and cyber-physical nature of a given fault-intolerant model under which recovery can be added. We show that the corresponding synthesis problem is NP-complete and consequently introduce symbolic heuristics to tackle the exponential complexity. Our experimental results validate effectiveness of our heuristics for relatively large models.
It is also important to reason that distributed priority synthesis, similar to our existing work, enables a direct execution of the resulting system (as synthesized priorities are artifacts compatible with the BIP model). The synthesized system is flexible in execution: it can be executed under a centralized controller or priorities can be equipped locally on each component (for distributed execution). Furthermore, priority synthesis is an approach which restricts existing behaviors predefined in the system, while works in [1] [2] target to add additional behaviors (i.e., non-existing transitions). Lastly, by releasing constraints inherent in BIP systems, we also study how (i) the use of knowledge and (ii) the release of transitivity constraints can assist the finding of distributed controllers.