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      "Can I Implement Your Algorithm?": A Model for Reproducible Research Software

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          Abstract

          The reproduction and replication of novel results has become a major issue for a number of scientific disciplines. In computer science and related computational disciplines such as systems biology, the issues closely revolve around the ability to implement novel algorithms and approaches. Taking an approach from the literature and applying it to a new codebase frequently requires local knowledge missing from the published manuscripts and project websites. Alongside this issue, benchmarking, and the development of fair --- and widely available --- benchmark sets present another barrier. In this paper, we outline several suggestions to address these issues, driven by specific examples from a range of scientific domains. Finally, based on these suggestions, we propose a new open platform for scientific software development which effectively isolates specific dependencies from the individual researcher and their workstation and allows faster, more powerful sharing of the results of scientific software engineering.

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          SLAyer: Memory Safety for Systems-Level Code

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            Using benchmarking to advance research: a challenge to software engineering

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              How to make ad hoc proof automation less ad hoc

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                Author and article information

                Journal
                2014-07-22
                2014-09-16
                Article
                1407.5981

                http://creativecommons.org/licenses/by-nc-sa/3.0/

                Custom metadata
                Accepted for the 2nd Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2); 5 pages, LaTeX
                cs.SE cs.CE

                Software engineering, Applied computer science

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