TY - JOUR
T1 - Investigation of Empirical Researches in Software Engineering
AU - Zhang, Li
AU - Pu, Meng Yuan
AU - Liu, Yi Jun
AU - Tian, Jia Hao
AU - Yue, Tao
AU - Jiang, Jing
N1 - Publisher Copyright:
© Copyright 2018, Institute of Software, the Chinese Academy of Sciences. All rights reserved.
PY - 2018
Y1 - 2018
N2 - To depict, understand, evaluate, predict, control, manage or enhance software-related artifacts, researchers and practitioners often rely on empirical methods. Empirical methods have been widely used in software engineering, and they are attracting increasing attention over the years. By conducting a systematic mapping, this paper aims to provide a literature survey of 250 papers published in a typical journal-Empirical Software Engineering, from January 2013 to June 2017. With qualitative and quantitative analysis, this survey reveals the commonly used empirical research methods, research purposes, and the application of the methods in subfields of software engineering, including the solved problems and some new features. The findings also cover the use of open source projects, data source, data collection methods and commonly used mathematical statistics methods. Finally, this paper illustrates validity threats and discusses the future work, opportunity and some open issues of empirical research in the era of big data.
AB - To depict, understand, evaluate, predict, control, manage or enhance software-related artifacts, researchers and practitioners often rely on empirical methods. Empirical methods have been widely used in software engineering, and they are attracting increasing attention over the years. By conducting a systematic mapping, this paper aims to provide a literature survey of 250 papers published in a typical journal-Empirical Software Engineering, from January 2013 to June 2017. With qualitative and quantitative analysis, this survey reveals the commonly used empirical research methods, research purposes, and the application of the methods in subfields of software engineering, including the solved problems and some new features. The findings also cover the use of open source projects, data source, data collection methods and commonly used mathematical statistics methods. Finally, this paper illustrates validity threats and discusses the future work, opportunity and some open issues of empirical research in the era of big data.
KW - Empirical method
KW - Empirical software engineering
KW - Literature survey
UR - https://www.scopus.com/pages/publications/85049555118
U2 - 10.13328/j.cnki.jos.005520
DO - 10.13328/j.cnki.jos.005520
M3 - 文章
AN - SCOPUS:85049555118
SN - 1000-9825
VL - 29
SP - 1422
EP - 1450
JO - Ruan Jian Xue Bao/Journal of Software
JF - Ruan Jian Xue Bao/Journal of Software
IS - 5
ER -