TY - GEN
T1 - ReproZip
T2 - 2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016
AU - Chirigati, Fernando
AU - Rampin, Rémi
AU - Shasha, Dennis
AU - Freire, Juliana
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/6/26
Y1 - 2016/6/26
N2 - We present ReproZip, the recommended packaging tool for the SIGMOD Reproducibility Review. ReproZip was designed to simplify the process of making an existing computational experiment reproducible across platforms, even when the experiment was put together without reproducibility in mind. The tool creates a self-contained package for an experiment by automatically tracking and identifying all its required dependencies. The researcher can share the package with others, who can then use ReproZip to unpack the experiment, reproduce the findings on their favorite operating system, as well as modify the original experiment for reuse in new research, all with little effort. The demo will consist of examples of non-trivial experiments, showing how these can be packed in a Linux machine and reproduced on different machines and operating systems. Demo visitors will also be able to pack and reproduce their own experiments.
AB - We present ReproZip, the recommended packaging tool for the SIGMOD Reproducibility Review. ReproZip was designed to simplify the process of making an existing computational experiment reproducible across platforms, even when the experiment was put together without reproducibility in mind. The tool creates a self-contained package for an experiment by automatically tracking and identifying all its required dependencies. The researcher can share the package with others, who can then use ReproZip to unpack the experiment, reproduce the findings on their favorite operating system, as well as modify the original experiment for reuse in new research, all with little effort. The demo will consist of examples of non-trivial experiments, showing how these can be packed in a Linux machine and reproduced on different machines and operating systems. Demo visitors will also be able to pack and reproduce their own experiments.
KW - Computational reproducibility
KW - Provenance
KW - ReproZip
UR - http://www.scopus.com/inward/record.url?scp=84979683953&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979683953&partnerID=8YFLogxK
U2 - 10.1145/2882903.2899401
DO - 10.1145/2882903.2899401
M3 - Conference contribution
AN - SCOPUS:84979683953
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
SP - 2085
EP - 2088
BT - SIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data
PB - Association for Computing Machinery
Y2 - 26 June 2016 through 1 July 2016
ER -