TY - JOUR
T1 - Empirical Research in Software Engineering — A Literature Survey
AU - Zhang, Li
AU - Tian, Jia Hao
AU - Jiang, Jing
AU - Liu, Yi Jun
AU - Pu, Meng Yuan
AU - Yue, Tao
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Empirical research is playing a significant role in software engineering (SE), and it has been applied to evaluate software artifacts and technologies. There have been a great number of empirical research articles published recently. There is also a large research community in empirical software engineering (ESE). In this paper, we identify both the overall landscape and detailed implementations of ESE, and investigate frequently applied empirical methods, targeted research purposes, used data sources, and applied data processing approaches and tools in ESE. The aim is to identify new trends and obtain interesting observations of empirical software engineering across different sub-fields of software engineering. We conduct a mapping study on 538 selected articles from January 2013 to November 2017, with four research questions. We observe that the trend of applying empirical methods in software engineering is continuously increasing and the most commonly applied methods are experiment, case study and survey. Moreover, open source projects are the most frequently used data sources. We also observe that most of researchers have paid attention to the validity and the possibility to replicate their studies. These observations are carefully analyzed and presented as carefully designed diagrams. We also reveal shortcomings and demanded knowledge/strategies in ESE and propose recommendations for researchers.
AB - Empirical research is playing a significant role in software engineering (SE), and it has been applied to evaluate software artifacts and technologies. There have been a great number of empirical research articles published recently. There is also a large research community in empirical software engineering (ESE). In this paper, we identify both the overall landscape and detailed implementations of ESE, and investigate frequently applied empirical methods, targeted research purposes, used data sources, and applied data processing approaches and tools in ESE. The aim is to identify new trends and obtain interesting observations of empirical software engineering across different sub-fields of software engineering. We conduct a mapping study on 538 selected articles from January 2013 to November 2017, with four research questions. We observe that the trend of applying empirical methods in software engineering is continuously increasing and the most commonly applied methods are experiment, case study and survey. Moreover, open source projects are the most frequently used data sources. We also observe that most of researchers have paid attention to the validity and the possibility to replicate their studies. These observations are carefully analyzed and presented as carefully designed diagrams. We also reveal shortcomings and demanded knowledge/strategies in ESE and propose recommendations for researchers.
KW - empirical method
KW - empirical software engineering
KW - systematic mapping study
UR - https://www.scopus.com/pages/publications/85053333492
U2 - 10.1007/s11390-018-1864-x
DO - 10.1007/s11390-018-1864-x
M3 - 文章
AN - SCOPUS:85053333492
SN - 1000-9000
VL - 33
SP - 876
EP - 899
JO - Journal of Computer Science and Technology
JF - Journal of Computer Science and Technology
IS - 5
ER -