An Empirical Study of Programming Language Trends

Authors:
Yaofei Chen;Rose Dios;Ali Mili;Lan Wu;Kefei Wang
Affiliations:
New Jersey Institute of Technology;New Jersey Institute of Technology;New Jersey Institute of Technology;New Jersey Institute of Technology;State University of New York, Albany
Venue:
IEEE Software
Year:
2005

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Abstract

Predicting software engineering trends is difficult because of the wide range of factors involved and the complexity of their interactions. In an earlier article, the authors discussed a tentative structure for this complex problem and gave a set of possible methods to approach it. Here, they reduce the problem's scope and try to gain some depth by focusing on a compact set of trends: programming languages. They choose 17 languages, measure their evolution over several years, then draw statistical conclusions on what drivesa language's evolution.