SESSL

This article introduces SESSL (&lowbarS;imulation &lowbarE;xperiment &lowbarS;pecification via a &lowbarS;cala &lowbarL;ayer), an embedded domain-specific language for simulation experiments. It serves as an additional software layer between users and simulation systems and is implemented in Scala. SESSL supports multiple simulation systems and offers various features (e.g., for experiment design, performance analysis, result reporting, and simulation-based optimization). It supports “cutting-edge” experiments by allowing to add custom code, enables a reuse of functionality across simulation systems, and improves the reproducibility of simulation experiments.

[1]  Elizabeth Chang,et al.  Goal-Directed Grid-Enabled Computing for Legacy Simulations , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[2]  Samuil Angelov,et al.  Petri Net Technology for Communication-Based Systems , 2003, Lecture Notes in Computer Science.

[3]  Adelinde M. Uhrmacher,et al.  Toward a language for the flexible observation of simulations , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[4]  Ekkart Kindler,et al.  The Petri Net Markup Language , 2003, Petri Net Technology for Communication-Based Systems.

[5]  Thierry Despeyroux.  Evolution of Ontologies and Types , 2008 .

[6]  L. Felipe Perrone,et al.  SAFE: Simulation automation framework for experiments , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[7]  Z. Merali.  Computational science: ...Error , 2010, Nature.

[8]  L. Felipe Perrone,et al.  On the automation of computer network simulators , 2009, SimuTools.

[9]  Konrad Hinsen.  A Glimpse of the Future of Scientific Programming , 2013, Computing in Science & Engineering.

[10]  Stefan Leye,et al.  Enhancing the Scalability of Simulations by Embracing Multiple Levels of Parallelization , 2010, 2010 Ninth International Workshop on Parallel and Distributed Methods in Verification, and Second International Workshop on High Performance Computational Systems Biology.

[11]  Mark Strembeck,et al.  Reusable Architectural Decisions for DSL Design Foundational Decisions in DSL Development , 2009 .

[12]  Kunle Olukotun,et al.  OptiML: An Implicitly Parallel Domain-Specific Language for Machine Learning , 2011, ICML.

[13]  Judicaël Ribault,et al.  Reuse and Scalability in Modeling and Simulation Software Engineering , 2011 .

[14]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[15]  Amit P. Sheth,et al.  Investigating ontologies for simulation modeling , 2004, 37th Annual Simulation Symposium, 2004. Proceedings..

[16]  Arie van Deursen,et al.  Domain-specific languages: an annotated bibliography , 2000, SIGP.

[17]  Krzysztof Pawlikowski,et al.  On credibility of simulation studies of telecommunication networks , 2002, IEEE Commun. Mag..

[18]  Michel Dumontier,et al.  Controlled vocabularies and semantics in systems biology , 2011, Molecular systems biology.

[19]  Eric Darve,et al.  Liszt: A domain specific language for building portable mesh-based PDE solvers , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[20]  Mark Strembeck,et al.  An approach for the systematic development of domain-specific languages , 2009 .

[21]  Martin Lukasiewycz,et al.  Opt4J: a modular framework for meta-heuristic optimization , 2011, GECCO '11.

[22]  Roland Ewald,et al.  Automatic Algorithm Selection for Complex Simulation Problems , 2011, Vieweg+Teubner Verlag.

[23]  Simon J. E. Taylor,et al.  Sakergrid: Simulation experimentation using grid enabled simulation software , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[24]  Miguel Garcia,et al.  Extending Scala with Database Query Capability , 2010, J. Object Technol..

[25]  Carlos F. Lopez,et al.  Programming biological models in Python using PySB , 2013, Molecular systems biology.

[26]  Paul Hudak,et al.  Building domain-specific embedded languages , 1996, CSUR.

[27]  D. Bruce.  What Makes a Good Domain-speciic Language? Apostle, and Its Approach to Parallel Discrete Event Simulation , 1997 .

[28]  Jacky L. Snoep,et al.  Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language , 2011, BMC Systems Biology.

[29]  Melanie I. Stefan,et al.  BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models , 2010, BMC Systems Biology.

[30]  Erik De Schutter,et al.  STEPS: efficient simulation of stochastic reaction–diffusion models in realistic morphologies , 2012, BMC Systems Biology.

[31]  Stefan Leye,et al.  Flexible experimentation in the modeling and simulation framework JAMES II - implications for computational systems biology , 2010, Briefings Bioinform..

[32]  Nicolas Le Novère,et al.  Simulation Experiment Description Markup Language (SED-ML) : Level 1 Version 1 , 2011 .

[33]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[34]  John A. Miller,et al.  Using Domain Specific Language for modeling and simulation: ScalaTion as a case study , 2010, Proceedings of the 2010 Winter Simulation Conference.

[35]  Anthony M. Sloane,et al.  Experiences with Domain-Specific Language Embedding in Scala , 2008 .

[36]  Nicolas Le Novère,et al.  Simulation Experiment Description Markup Language (SED-ML) , 2014, Encyclopedia of Computational Neuroscience.

[37]  Linda R Petzold,et al.  Efficient step size selection for the tau-leaping simulation method. , 2006, The Journal of chemical physics.

[38]  Jean G. Vaucher,et al.  SSJ: a framework for stochastic simulation in Java , 2002, Proceedings of the Winter Simulation Conference.

[39]  Hiroaki Kitano,et al.  Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration. , 2003, Omics : a journal of integrative biology.

[40]  Mark Strembeck,et al.  An approach for the systematic development of domain‐specific languages , 2009, Softw. Pract. Exp..

[41]  Adelinde M. Uhrmacher,et al.  A flexible and scalable experimentation layer , 2008, 2008 Winter Simulation Conference.

[42]  Aruna Raja,et al.  Domain Specific Languages , 2010 .

[43]  Martin Odersky,et al.  Scalable component abstractions , 2005, OOPSLA '05.

[44]  Averill Law,et al.  Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management) , 2006 .

[45]  Nicolas Le Novère,et al.  Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 2 , 2015, J. Integr. Bioinform..

[46]  Mark Strembeck,et al.  Comparing complexity of API designs: an exploratory experiment on DSL-based framework integration , 2011, GPCE '11.

[47]  Adelinde M. Uhrmacher,et al.  Plug'n Simulate , 2007, 40th Annual Simulation Symposium (ANSS'07).

[48]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .

[49]  Mark Strembeck,et al.  Reusable Architectural Decisions for DSL Design: Foundational Decisions in DSL Projects , 2009, EuroPLoP.

[50]  Friedrich Leisch,et al.  Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis , 2002, COMPSTAT.

[51]  Andy Hallagan,et al.  The Design of XML-Based Model and Experiment Description Languages for Network Simulation , 2011 .

[52]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[53]  Kenton O'Hara,et al.  Troubling Trends in Scientific Software Use , 2013, Science.