TY - GEN
T1 - Mining Technology Landscape from Stack Overflow
AU - Chen, Chunyang
AU - Xing, Zhenchang
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/9/8
Y1 - 2016/9/8
N2 - The sheer number of available technologies and the complex relationships among them make it challenging to choose the right technologies for software projects. Developers often turn to online resources (e.g., expert articles and community answers) to get a good understanding of the technology landscape. Such online resources are primarily opinion-based and are often out of date. Furthermore, information is often scattered in many online resources, which has to be aggregated to have a big picture of the technology landscape. In this paper, we exploit the fact that Stack Overflow users tag their questions with the main technologies that the questions revolve around, and develop association rule mining and community detection techniques to mine technology landscape from Stack Overflow question tags. The mined technology landscape is represented in a graphical Technology Associative Network (TAN). Our empirical study shows that the mined TAN captures a wide range of technologies, the complex relationships among the technologies, and the trend of the technologies in the developers' discussions on Stack Overflow. We develop a website (https://graphofknowledge.appspot.com/) for the community to access and evaluate the mined technology landscape. The website visit statistics by Google Analytics shows the developers' general interests in our technology landscape service. We also report a small-scale user study to evaluate the potential usefulness of our tool.
AB - The sheer number of available technologies and the complex relationships among them make it challenging to choose the right technologies for software projects. Developers often turn to online resources (e.g., expert articles and community answers) to get a good understanding of the technology landscape. Such online resources are primarily opinion-based and are often out of date. Furthermore, information is often scattered in many online resources, which has to be aggregated to have a big picture of the technology landscape. In this paper, we exploit the fact that Stack Overflow users tag their questions with the main technologies that the questions revolve around, and develop association rule mining and community detection techniques to mine technology landscape from Stack Overflow question tags. The mined technology landscape is represented in a graphical Technology Associative Network (TAN). Our empirical study shows that the mined TAN captures a wide range of technologies, the complex relationships among the technologies, and the trend of the technologies in the developers' discussions on Stack Overflow. We develop a website (https://graphofknowledge.appspot.com/) for the community to access and evaluate the mined technology landscape. The website visit statistics by Google Analytics shows the developers' general interests in our technology landscape service. We also report a small-scale user study to evaluate the potential usefulness of our tool.
KW - Association Rule Mining
KW - Community Detection
KW - Technology Associative Network
KW - Technology Landscape
UR - http://www.scopus.com/inward/record.url?scp=84991676959&partnerID=8YFLogxK
U2 - 10.1145/2961111.2962588
DO - 10.1145/2961111.2962588
M3 - Conference contribution
T3 - International Symposium on Empirical Software Engineering and Measurement
BT - 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
PB - IEEE Computer Society
T2 - 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
Y2 - 8 September 2016 through 9 September 2016
ER -