English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Finite-state models are widely used in software engineering, especially in control systems development. Commonly, in control applications such models are developed manually, hence, keeping them up-to-date requires extra effort. To simplify the maintenance process, an automatic approach may be used, allowing inference of models from behavior examples and temporal specification. As an example of a specific control systems development application, we focus on inferring finite-state models of function blocks (FBs) defined by the IEC 61499 international standard for distributed automation systems. In this paper, we propose a method for FB model inference from behavior examples based on reduction to Boolean satisfiability problem (SAT). Additionally, we take into account linear temporal properties using counterexample-guided synthesis. The developed tool fbSAT implementing the proposed method is evaluated in three case studies: inference of a finite-state controller for a Pick-and-Place manipulator, reconstruction of randomly generated automata, and minimization of transition systems. In contrast to existing approaches, the suggested method is more efficient and produces finite-state models minimal both in terms of number of states and guard conditions complexity.

fbSAT: Automatic Inference of Minimal Finite-State Models of Function Blocks Using SAT Solver