scispace - formally typeset
I

Ingo Sander

Researcher at Royal Institute of Technology

Publications -  111
Citations -  1283

Ingo Sander is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Model of computation & Design space exploration. The author has an hindex of 19, co-authored 108 publications receiving 1237 citations.

Papers
More filters
Journal ArticleDOI

System modeling and transformational design refinement in ForSyDe [formal system design]

TL;DR: In this article, the authors introduce process constructors, which cleanly separate the computation part of a process from the synchronization and communication part, and use the characteristic function for each process type to define semantic preserving and design decision transformations.
Journal ArticleDOI

Models of computation and languages for embedded system design

Axel Jantsch, +1 more
TL;DR: It is argued that different MoCs are necessary for the various tasks and phases in the design of an embedded system and have to be integrated to provide a coherent system modelling and analysis environment.

System Modeling and Design Refinement in ForSyDe

Ingo Sander
TL;DR: This thesis presents the ForSyDe (Formal System Design) methodology, which has been developed with the objective to movesystem design to a higher level of abstraction and to bridge the abstraction gap by transformational design refinement.
Proceedings ArticleDOI

Feasibility analysis of messages for on-chip networks using wormhole routing

TL;DR: A novel feasibility analysis for real-time (RT) and nonrealtime (NT) messages in wormhole-routed networks on chip is presented and a contention tree is formulated that captures contentions in the network.
Proceedings Article

Formal heterogeneous system modeling with SystemC

TL;DR: This work presents a modeling library on top of SystemC, targeting heterogeneous embedded system design, based on four models of computation, which has a formal basis where all elements are well defined and lead in construction of analyzable models.