Mining Technology Landscape from Stack Overflow

Chunyang Chen, Zhenchang Xing

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

42 Citations (Scopus)

Abstract

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 Such online resources are primarily opinion-based and are often out of date.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.

Original languageEnglish
Title of host publication10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781450344272
DOIs
Publication statusPublished - 8 Sept 2016
Externally publishedYes
Event10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016 - TBC, Ciudad Real, Spain
Duration: 8 Sept 20169 Sept 2016

Publication series

NameInternational Symposium on Empirical Software Engineering and Measurement
Volume08-09-September-2016
ISSN (Print)1949-3770
ISSN (Electronic)1949-3789

Conference

Conference10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
Country/TerritorySpain
CityCiudad Real
Period8/09/169/09/16
Other8 September 2016 through 9 September 2016

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