TY - CHAP
T1 - Simulation reproducibility with python and pweave
AU - Kim, Kyeong Soo (Joseph)
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - As the amount and complexity of model source code, configuration files, and resulting data for simulative experiments are ever increasing, it becomes a real challenge to reliably and efficiently reproduce simulation data and their analysis results published in a scientific paper not only by its readers but also by the authors themselves, which makes the claims and contributions made in the paper questionable. The idea of reproducible research comes as a solution to this problem and suggests that any scientific claims should be published together with relevant experimental data and software code for their analysis so that readers may verify the findings and build upon them; in case of computer simulation, the details of simulation implementation and its configurations should be provided as well. In this chapter, we illustrate the practice of reproducible research for OMNeT++ simulation based on Pweave and Python. We show how to embed simulation configuration files and Python analysis code, import simulation data with automatic updating of simulation results, and analyze data and present the results in a file.
AB - As the amount and complexity of model source code, configuration files, and resulting data for simulative experiments are ever increasing, it becomes a real challenge to reliably and efficiently reproduce simulation data and their analysis results published in a scientific paper not only by its readers but also by the authors themselves, which makes the claims and contributions made in the paper questionable. The idea of reproducible research comes as a solution to this problem and suggests that any scientific claims should be published together with relevant experimental data and software code for their analysis so that readers may verify the findings and build upon them; in case of computer simulation, the details of simulation implementation and its configurations should be provided as well. In this chapter, we illustrate the practice of reproducible research for OMNeT++ simulation based on Pweave and Python. We show how to embed simulation configuration files and Python analysis code, import simulation data with automatic updating of simulation results, and analyze data and present the results in a file.
UR - http://www.scopus.com/inward/record.url?scp=85090512318&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-12842-5_8
DO - 10.1007/978-3-030-12842-5_8
M3 - Chapter
AN - SCOPUS:85090512318
T3 - EAI/Springer Innovations in Communication and Computing
SP - 281
EP - 299
BT - EAI/Springer Innovations in Communication and Computing
PB - Springer Science and Business Media Deutschland GmbH
ER -