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Software simplified

Andrew Silver

Containerization technology takes the hassle out of setting up software and can boost the reproducibility of data-driven research.

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[...] Containers are essentially lightweight, configurable virtual machines — simulated versions of an operating system and its hardware, which allow software developers to share their computational environments. Researchers use them to distribute complicated scientific software systems, thereby allowing others to execute the software under the same conditions that its original developers used. In doing so, containers can remove one source of variability in computational biology. [...]
Lab-built tools rarely come ready to run. They often take the form of scripts or programming source code, which must be processed and configured. Much of the software requires additional tools and libraries, which the user may not have installed. Even if users can get the software to work, differences in computational environments, such as the installed versions of the tools it depends on, can subtly alter performance, affecting reproducibility. Containers reduce that complexity by packaging the key elements of the computational environment needed to run the desired software, including settings and add-ons, into a lightweight, virtual box. They don't alter the resources required to run it — if a tool needs a lot of memory, then so too will its container. But they make the software much easier to use, and the results easier to reproduce. [...]
But containers are only as good as the tools they encapsulate, says Lorena Barba, a mechanical and aerospace engineer at George Washington University, Washington DC. “If researchers start stuffing their bad code into a container and pass it on, we are foredoomed to failure.” And, says Brown, without pressure from funding agencies and journals, containers are unlikely to make researchers suddenly embrace computational reproducibility. [...]

Nature, Vol. 546, No. 7656. (29 May 2017), pp. 173-174, 
Key: INRMM:14366294



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