Model-Driven Software Engineering: A Bibliometric Analysis

  • سال انتشار: 1400
  • محل انتشار: مجله محاسبات و امنیت، دوره: 8، شماره: 1
  • کد COI اختصاصی: JR_JCSE-8-1_007
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 128
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نویسندگان

Hamed Barangi

MDSE Research Group, Dept. of Software Engineering, University of Isfahan, Isfahan, Iran.

Shekoufeh Kolahdouz Rahimi

MDSE Research Group, Dept. of Software Engineering, University of Isfahan, Isfahan, Iran.

Bahman Zamani

MDSE Research Group, Dept. of Software Engineering, University of Isfahan, Isfahan, Iran.

Ali Akbar Khasseh

Department of Library and Information Science, Payame Noor University, Iran.

چکیده

Model-Driven Software Engineering (MDSE) is a software development methodology that reduces the cost and production time of the final product by concentratingon a higher level of abstraction. The main focus of MDSE is to generate automated code by applying different types of transformations to high-level models. The effectiveness of MDSE has been proved in different domains for solving various types of problems.This research provides the bibliometric analysis of research in the field of MDSE. The population of the study consists of all MDSE articles indexed in the Web of Science database in ten years from ۲۰۱۰ to ۲۰۱۹. The work aims to identify the volume of scientific production, the most influential countries, universities, authors, and journals, the cooperation network among the countries, universities, and authors, keyword ranking, and Co-word analysis of keywords and titles of the articles. Keyword analysis revealed that Model Transformation and Model Checking are two very important clusters and topics of interest to researchers in this field. The results provide valuable insights that can be used as a guideline by both fresh and experienced researchers for the current state and future trend of MDSE research in different scientific disciplines to establish a baseline beforeinitiating an MDSE research project in the future.

کلیدواژه ها

Model-Driven Software Engineering, Bibliometrics, Web of Science, Literature Review

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