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LCTES 2018
co-located with PLDI 2018

Finite-state machine-based scenario-aware dataflow (FSM-SADF) is a dynamic dataflow model of computation that combines streaming data and finite-state control. For the most part, it preserves the determinism of its underlying synchronous dataflow (SDF) concurrency model and only when necessary introduces the non-deterministic variation in terms of scenarios that are represented by SDF graphs. This puts FSM-SADF in a sweet spot in the trade-off space between expressiveness and analyzability. However, FSM-SADF supports no notion of compositionality, which hampers its usability in modeling and consequent analysis of large systems. In this work we propose a compositional semantics for FSM-SADF that overcomes this problem. We base the semantics of the composition on standard composition of processes with rendezvous communication in the style of CCS or CSP at the control level and the parallel, serial and feedback composition of SDF graphs at the dataflow level. We evaluate the approach on a case study from the multimedia domain.

Conference Day
Tue 19 Jun

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

11:00 - 12:15
Full paper session on Programming LanguagesLCTES 2018 at Discovery AB
11:00
25m
Full-paper
MakeCode and CODAL: Intuitive and Efficient Embedded Systems Programming for Education
LCTES 2018
James DevineLancaster University, Joe Finney, Peli de HalleuxMicrosoft Research, Michał MoskalMicrosoft Research, Thomas BallMicrosoft Research, Steve HodgesMicrosoft
11:25
25m
Full-paper
Compositionality in Scenario-aware Dataflow: A Rendezvous Perspective
LCTES 2018
Mladen SkelinEindhoven University of Technology, Marc GeilenEindhoven University of Technology
11:50
25m
Full-paper
A Memory-Bounded, Deterministic and Terminating Semantics for the Synchronous Programming Language Céu
LCTES 2018
Guilherme F. LimaPUC-Rio, Rodrigo C. M. SantosPUC-Rio, Edward Hermann HaeuslerPUC-Rio, Roberto IerusalimschyPUC-Rio, Francisco Sant'AnnaRio de Janeiro State University