The Community for Technology Leaders
Green Image
Issue No. 03 - May/June (2005 vol. 22)
ISSN: 0740-7459
pp: 72-78
Yaofei Chen , New Jersey Institute of Technology
Rose Dios , New Jersey Institute of Technology
Ali Mili , New Jersey Institute of Technology
Lan Wu , New Jersey Institute of Technology
Kefei Wang , State University of New York, Albany
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 drives a language's evolution.
programming languages, software engineering trends, empirical software engineering, statistical modeling

L. Wu, A. Mili, Y. Chen, K. Wang and R. Dios, "An Empirical Study of Programming Language Trends," in IEEE Software, vol. 22, no. , pp. 72-78, 2005.
80 ms
(Ver 3.3 (11022016))