Modern web applications have to manage a lot of user data and often use a three-stack architecture: (1) a web interface developed by markup language like HTML (2) application logic developed by traditional object-oriented languages, and (3) a database management system (DBMS) that maintains persistent data.

Under this architecture, there are common understanding gaps between web designer and application developers and database engine. As a result, performance and correctness problems are common.

To tackle performance problems, I did one of the first studies to understand why real-world web applications are slow. Guided by that study, I used cross-stack analysis to synthesize efficient web pages, to automatically detect inefficiency in data processing code, and to help database optimization using application knowledge. My tools have found thousands of performance issues. To tackle correctness problems in web applications, I investigated how data constraints could be inconsistent across web interface, application, and database, and how to solve these problems.

Junwen Yang is a Ph.D. candidate in the Department of Computer Science at the University of Chicago. Her research focuses on automatically detecting and fixing performance and correctness bugs in big data software through a combination of program analysis, software engineering, and database techniques. Her research has led to first-author papers published at top software engineering conferences (FSE’18, ICSE’18, ICSE’19, SPLASH’19, ICSE’20), winning the 2019 SIGSOFT Distinguished Paper Award and 2019 SIGPLAN John Vlissides Award, as well as co-authored papers at database conferences (CIKM’18, CIDR’20). Her research found thousands of bugs in popular open-source web applications, raising attention in the open-source community and featured on Morning Paper blog twice, RubyWeekly, and Hacker News. She also recently won the Harper Dissertation Fellowship. Yang has served as a mentor in UChicago ACM-W mentor program and an instructor in compileHer program, teaching computer science and STEM concepts to middle school girls.