Yingjun Lyu

Yingjun Lyu

Ph.D. Student

University of Southern California

Personal Profile

I am a Ph.D. student in the Computer Science department at the University of Southern California since Fall 2014. My advisor is William G.J. Halfond. My research interest lies in software testing, analysis and optimization.

Education

University of Southern California

Ph.D. Computer Science

2014-present

The Hong Kong University of Science and Technology

Bachelor, Computer Science

2012-2014

Sun Yat-sen University

Bachelor, Computer Science

2010-2012

Publications

ELIXIR : Effective Object Oriented Program Repair

Ripon K. Saha, Yingjun Lyu, Hiroaki Yoshida, Mukul R. Prasad

ASE 2017, acceptance rate: 21%

An Empirical Study of Local Database Usage in Android Applications

Yingjun Lyu, Jiaping Gui, Mian Wan, William G. J. Halfond

ICSME 2017, acceptance rate: 27.8%

Automated Energy Optimization of HTTP Requests for Mobile Applications

Ding Li, Yingjun Lyu, Jiaping Gui, William G. J. Halfond

ICSE 2016, acceptance rate: 19%

String Analysis for Java and Android Applications

Ding Li, Yingjun Lyu, Mian Wan, William G. J. Halfond

FSE 2015, acceptance rate: 25.4%

Working Experience

NEC Laboratories of America, Inc

Research Intern, May 2017 - Aug 2017

Worked on real-time data leakage detection using system monitoring logs.

Fujitsu Laboratories of America, Inc.

Research Intern, May 2016 - Aug 2016

Worked on automated Java program repair.

Projects

Violist - A String Analysis Framework

This is a general framework for string analysis that allows researchers to more flexibly choose how they will estimate the possible string values at a given program point.

Github: https://github.com/USC-SQL/Violist

Automated Performance Analysis for Android Applications

Performance bugs of mobile applications were discovered and categorized. The tool performs an automated performance analysis tool on mobile applications and detects performance bugs in the source code. Bug reports will be generated to assist developers to improve the performance of their apps.

Github: https://github.com/winsonlyu/Performance-Checker-Wala