@phdthesis{Chodak2021, author = {Chodak, Jacek}, title = {Spike - a tool for reproducible simulation experiments}, doi = {10.26127/BTUOpen-5850}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-58509}, school = {BTU Cottbus - Senftenberg}, year = {2021}, abstract = {Reproducibility of simulation experiments is still a significant challenge and has attracted considerable attention in recent years. One cause of this situation is bad habits of the scientific community. Many results are published without data or source code, and only a textual description of the simulation set-up is provided. Other causes are: no complete simulation set-up, no proper output data analysis and inconsistency of published data, which makes it impossible to compare results. The progress of computational modelling, amount of data and complexity of models requires designing experiments in such a way that ensures reproducibility. A textual description does not provide all the needed details. A computer code is more reliable than a textual description. It is the precise specification that describes a simulation configuration, model, etc. When computer code, data, models and all parameters are provided, the simulation results become reproducible. The main goal of this thesis is to develop a tool that ensures reproducibility and efficient execution of simulation experiments, often involving many individual simulation runs. The tool should support a wide range of application scenarios, where the typical scenario is simulation of biochemical reaction networks, which are represented as (coloured) Petri nets interpreted in the stochastic, continuous or hybrid paradigm. The model to be simulated can be given in various formats, including SBML. The result is a command line tool called Spike, which can be used for various scenarios, including benchmarking, simulation of adaptive models and parameter optimization. It builds on a human-readable configuration script SPC, supporting the efficient specification of multiple model configurations as well as multiple simulator configurations in a single configuration file.}, subject = {Petri nets; Parallel simulation; Parameter scanning; Reproducibility; Simulation of adaptive models; Petri Netze; Parallelsimulation; Parameterscannen; Reproduzierbarkeit; Simulation von adaptiven Modellen; Gef{\"a}rbtes Petri-Netz; Simulation; Reproduzierbarkeit}, language = {en} }