TY  - CHAP
AU  - Semeráth, Oszkár
AU  - Nagy, András Szabolcs
AU  - Varró, Dániel
ED  - Marsha, Chechik
ED  - Mark, Harman
TI  - A Graph Solver for the Automated Generation of Consistent Domain-Specific Models
T2  - ICSE '18
PB  - ACM Press
CY  - New York, New York
SN  - 9781450356381
PY  - 2018
SP  - 980
EP  - 980
PG  - 12
DO  - 10.1145/3180155.3180186
UR  - https://m2.mtmt.hu/api/publication/3335161
ID  - 3335161
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Nagy, András Szabolcs
AU  - Varró, Dániel
ED  - Pataki, Béla
TI  - Effects of Graph Transformation Rules to Design Space Exploration Problems
T2  - Proceedings of the 24th PhD Mini-Symposium
PB  - BME Méréstechnika és Információs Rendszerek Tanszék
CY  - Budapest
SN  - 9789633132432
PY  - 2017
SP  - 58
EP  - 61
PG  - 4
DO  - 10.5281/zenodo.291901
UR  - https://m2.mtmt.hu/api/publication/3203907
ID  - 3203907
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Nagy, András Szabolcs
AU  - Szárnyas, Gábor
ED  - Antonio, Garcia-Dominguez
ED  - Filip, Křikava
ED  - Louis, M Rose
TI  - Class Responsibility Assignment Case: a VIATRA-DSE Solution
T2  - Proceedings of the 9th Transformation Tool Contest
PB  - CEUR Workshop Proceedings
PY  - 2016
SP  - 39
EP  - 44
PG  - 6
UR  - https://m2.mtmt.hu/api/publication/3169906
ID  - 3169906
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Alexandra, Anna Sólyom
AU  - Nagy, András Szabolcs
ED  - [sn], null
TI  - Swarm Intelligence Meets Rule-Based Design Space Exploration
T2  - Proceedings of the 23rd PhD Mini-Symposium
PB  - BME Méréstechnika és Információs Rendszerek Tanszék
CY  - Budapest
SN  - 9789633132203
PY  - 2016
SP  - 42
EP  - 45
PG  - 4
UR  - https://m2.mtmt.hu/api/publication/3094035
ID  - 3094035
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Hani, Abdeen
AU  - Varró, Dániel
AU  - Houari, Sahraoui
AU  - Nagy, András Szabolcs
AU  - Debreceni, Csaba
AU  - Hegedüs, Ábel
AU  - Horváth, Ákos
ED  - Anon, null
TI  - Multi-Objective Optimization in Rule-Based Design Space Exploration
T2  - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
PB  - ACM Press
CY  - New York, New York
SN  - 1450330134
PY  - 2014
SP  - 289
EP  - 300
PG  - 12
DO  - 10.1145/2642937.2643005
UR  - https://m2.mtmt.hu/api/publication/2763246
ID  - 2763246
AB  - Design space exploration (DSE) aims to find optimal design 
candidates of a domain with respect to different objectives 
where design candidates are constrained by complex structural 
and numerical restrictions. Rule-based DSE aims to find such 
candidates that are reachable from an initial model by 
applying a sequence of exploration rules. Solving a rule-
based DSE problem is a difficult challenge due to the 
inherently dynamic nature of the problem.

In the current paper, we propose to integrate multi-objective 
optimization techniques by using Non-dominated Sorting 
Genetic Algorithms (NSGA) to drive rule-based design space 
exploration. For this purpose, finite populations of the most 
promising design candidates are maintained wrt. different 
optimization criteria. In our context, individuals of a 
generation are defined as a sequence of rule applications 
leading from an initial model to a candidate model. 
Populations evolve by mutation and crossover operations which 
manipulate (change, extend or combine) rule execution 
sequences to yield new individuals.

Our multi-objective optimization approach for rule-based DSE 
is domain independent and it is automated by tooling built on 
the Eclipse framework. The main added value is to seamlessly 
lift multi-objective optimization techniques to the 
exploration process preserving both domain independence and a 
high-level of abstraction. Design candidates will still be 
represented as models and the evolution of these models as 
rule execution sequences. Constraints are captured by model 
queries while objectives can be derived both from models or 
rule applications.
LA  - English
DB  - MTMT
ER  -