Abstract
This is position paper accepted to the Computational Science & Engineering Software Sustainability and Productivity Challenges (CSESSP Challenges) Workshop, sponsored by the Networking and Information Technology Research and Development (NITRD) Software Design and Productivity (SDP) Coordinating Group, held October 15th-16th 2015 in Washington DC, USA. It discusses the role recommendation systems, based on textual and structural information in source code, and further enhanced by mining related applications, can have in improving the portability of scientific and engineering software.
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