An empirical study of programming language trends

Yaofei Chen; Rose Dios; Ali Mili; Lan Wu; Kefei Wang

doi:10.1109/MS.2005.55

An empirical study of programming language trends

Yaofei Chen
, Rose Dios
, Ali Mili
, Lan Wu
, Kefei Wang

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

Predicting software engineering trends is hard because of the range of factors involved and the complexity of their interactions. Having developed earlier a tentative structure and some possible solutions for this problem, the authors now reduce the problem scope and try to gain some depth by focusing on a compact set of trends: programming languages. They measure the evolution of 17 languages over several years to draw statistical conclusions on what drives a language's evolution.

Original language	English (US)
Pages (from-to)	72-79
Number of pages	8
Journal	IEEE Software
Volume	22
Issue number	3
DOIs	https://doi.org/10.1109/MS.2005.55
State	Published - May 2005
Externally published	Yes

All Science Journal Classification (ASJC) codes

Software

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10.1109/MS.2005.55

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AB - Predicting software engineering trends is hard because of the range of factors involved and the complexity of their interactions. Having developed earlier a tentative structure and some possible solutions for this problem, the authors now reduce the problem scope and try to gain some depth by focusing on a compact set of trends: programming languages. They measure the evolution of 17 languages over several years to draw statistical conclusions on what drives a language's evolution.

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An empirical study of programming language trends

Abstract

All Science Journal Classification (ASJC) codes

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