SEAug 17, 2015

Supporting Developers in Porting Software via Combined Textual and Structural Analysis of Software Artifacts

arXiv:1508.04044v1
Originality Synthesis-oriented
AI Analysis

It addresses software sustainability challenges for developers in computational science and engineering, but is incremental as it builds on existing recommendation and mining techniques.

This position paper tackles the problem of improving software portability for scientific and engineering applications by proposing recommendation systems that analyze textual and structural information in source code, enhanced by mining related applications.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes