images/pub-01.jpg
Research
Understanding how developers use — and rely on — the crowd.
I study crowdsourcing in software engineering, empirical software engineering, mining software repositories, and software ecosystems, using data mining, machine learning, and statistical analysis on historical project data. Below: current research areas and a full list of publications, each with a short summary figure and a PDF download.
Research areas
Mining software repositories
Empirical software engineering
Software evolution and maintenance
Software reuse
Crowdsourced software engineering
Data-driven software engineering
Software ecosystems
Publications
28 entries
Paper thumbnail
images/pub-01.jpg
images/pub-01.jpg
Paper thumbnail
images/pub-02.jpg
images/pub-02.jpg
Dependency Update Strategies and Package Characteristics
Paper thumbnail
images/pub-03.jpg
images/pub-03.jpg
Qualitative Analysis of Security-Related Code Reviews: An Empirical Study
Paper thumbnail
images/pub-04.jpg
images/pub-04.jpg
What are the Characteristics of High-used Packages? A Case Study on the npm Ecosystem
Paper thumbnail
images/pub-05.jpg
images/pub-05.jpg
23 Shades of Self-Admitted Technical Debt: An Empirical Study on Machine Learning Software
Paper thumbnail
images/pub-06.jpg
images/pub-06.jpg
Combining Static and Dynamic Analysis to Decompose Monolithic Application into Microservices
Paper thumbnail
images/pub-07.jpg
images/pub-07.jpg
On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests
Paper thumbnail
images/pub-08.jpg
images/pub-08.jpg
On the Co-Occurrence of Refactoring of Test and Source Code
Paper thumbnail
images/pub-09.jpg
images/pub-09.jpg
Towards Using Package Centrality Trend to Identify Packages in Decline
Paper thumbnail
images/pub-10.jpg
images/pub-10.jpg
Dependency Smells in JavaScript Projects
Paper thumbnail
images/pub-11.jpg
images/pub-11.jpg
On the Untriviality of Trivial Packages: An Empirical Study of npm JavaScript Packages
Paper thumbnail
images/pub-12.jpg
images/pub-12.jpg
How Effective is Continuous Integration in Indicating Single-Statement Bugs?
Paper thumbnail
images/pub-13.jpg
images/pub-13.jpg
Breaking Type Safety in Go: An Empirical Study on the Usage of the unsafe Package
Paper thumbnail
images/pub-14.jpg
images/pub-14.jpg
Helping or not Helping? Why and How Trivial Packages Impact the npm Ecosystem
Paper thumbnail
images/pub-15.jpg
images/pub-15.jpg
On the Removal of Feature Toggles: A Study of Python Projects and Practitioners' Motivations
Paper thumbnail
images/pub-16.jpg
images/pub-16.jpg
Using Others' Tests to Avoid Breaking Updates
Paper thumbnail
images/pub-17.jpg
images/pub-17.jpg
Challenges in Chatbot Development: A Study of Stack Overflow Posts
Paper thumbnail
images/pub-18.jpg
images/pub-18.jpg
A Machine Learning Approach to Improve the Detection of CI Skip Commits
Paper thumbnail
images/pub-19.jpg
images/pub-19.jpg
On the Impact of Using Trivial Packages: An Empirical Case Study on npm and PyPI
Paper thumbnail
images/pub-20.jpg
images/pub-20.jpg
Which Commits Can Be CI Skipped?
Paper thumbnail
images/pub-21.jpg
images/pub-21.jpg
An Empirical Study of Android Wear User Complaints
Paper thumbnail
images/pub-22.jpg
images/pub-22.jpg
Studying Permission-Related Issues in Android Wearable Apps
Paper thumbnail
images/pub-23.jpg
images/pub-23.jpg
What Do Developers Use the Crowd For? A Study Using Stack Overflow
Paper thumbnail
images/pub-24.jpg
images/pub-24.jpg
On Code Reuse from StackOverflow: An Exploratory Study on Android Apps
Paper thumbnail
images/pub-25.jpg
images/pub-25.jpg
Why Do Developers Use Trivial Packages? An Empirical Case Study on npm
Paper thumbnail
images/pub-26.jpg
images/pub-26.jpg
Reasons and Drawbacks of Using Trivial npm Packages: The Developers' Perspective
Paper thumbnail
images/pub-27.jpg
images/pub-27.jpg
An Empirical Study on the Removal of Self-Admitted Technical Debt
Paper thumbnail
images/pub-28.jpg
images/pub-28.jpg
Examining User Complaints of Wearable Apps: A Case Study on Android Wear
Full, up-to-date list also available on Google Scholar and DBLP.