  Computer science offers a large set of tools for prototyping, writing,
running, testing, validating, sharing and reproducing results, however
computational science lags behind. In the best case, authors may provide their
source code as a compressed archive and they may feel confident their research
is reproducible. But this is not exactly true. James Buckheit and David Donoho
proposed more than two decades ago that an article about computational results
is advertising, not scholarship. The actual scholarship is the full software
environment, code, and data that produced the result. This implies new
workflows, in particular in peer-reviews. Existing journals have been slow to
adapt: source codes are rarely requested, hardly ever actually executed to
check that they produce the results advertised in the article. ReScience is a
peer-reviewed journal that targets computational research and encourages the
explicit replication of already published research, promoting new and
open-source implementations in order to ensure that the original research can
be replicated from its description. To achieve this goal, the whole publishing
chain is radically different from other traditional scientific journals.
ReScience resides on GitHub where each new implementation of a computational
study is made available together with comments, explanations, and software
tests.

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