Yutian Tang

Short Bio

Dr. Yutian Tang (Chris) [CV] is an Assistant Professor at School of Information Science and Technology, ShanghaiTech University (PI, Ph.D. Supervisor, Co-Appointed Research Professor -研究员、博导). He received his Ph.D. degree from the Department of Computing, The Hong Kong Polytechnic University, under the supervision of Dr. Xiapu Luo and Dr. Hareton Leung. He received his B.Sc in Computer Science from Jilin University, under the supervision of Prof. Lan Huang. His research interests include software engineering (product line; program understanding; testing), cybersecurity, blockchain, machine learning (NLP; deep) and empirical software engineering. He is a member of IEEE, HKCS, CCF and EuroSys.

Chris has published over 20 papers at premier software engineering venues such as ESEC/FSE, ASE, SANER, ISSRE, ICPC conferences and IEEE Transaction on Software Engineering (TSE), IEEE Transactions on Reliability (TReli), JSS, IST journals. One work received Best Industry Paper Award at ISSRE'18. Three works reported defects in Android OS, which are confirmed by Google Security Team. His future research plans are directed towards advancing the techniques to automatically test apps and locate bugs, and providing tool support for their applications.

+1. We actively recruit new RAs, PhD students, Msc students, and PostDocs with background in program analysis, software testing, and Android apps (NLP or deep learning experiences is a plus) Email: tangyt1@shanghaitech.edu.cn.

+2. We also have openings for Undergraduate Interns.

Note: Our current research topic : Fuzzing, AI+SE, Security, Android。

CS132 Software Engineering - Office Hour
Time: Every Wed 7:00-8:00 PM; Loc: 1A-106 (W1-W4;W13-W16)

Research Overview:

1. Android Security, Vulnerability, and Privacy

(1) Vunlerability Discovery:

  • Resource Race Attack Model in Android (SANER'20);
  • Vulnerabilities in App Link Scheme (ESEC/FSE'20);

(2) Potentially Harmful Apps (PHAs) Analysis:

  • DiehardDetector: Detecting Diehard Android Apps (ASE'20);

(3) Third-party Library Analysis:

  • APMHunter: Detecting (mis)use of Application Performance Management Libraries in Apps (ASE'19);
  • Comparative Study of Android Repackaged Apps Detection Techniques (SANER'19)

2. Software Product Line Enginering

  • Feature modelling (SANER'17, ICEIS"15, SOFTENG'15);
  • Modularity and type system in product line engineering (ICPC'17);

3. AI + SE

  • Knowledge graph in software engineering (ISSRE'18);

News (all/21/20/19)

  • [02/2021] The journal version of our paper QRS'20 has been accepted to IEEE Transcations on Reliability.
  • [11/2020] Our paper entitled " Just-in-Time Defect Prediction for Android Apps via Imbalanced Deep Learning Model" has been accepted to SAC Conference.
  • [10/2020] Our paper entitled " Feature Selection and Embedding Based Cross Project Framework for Identifying Crashing Fault Residence" has been accepted to IST.
  • [07/2020] Our paper entitled "Demystifying Diehard Android Apps" has been accepted to ASE'20.
  • [06/2020] Our paper entitled "Simplified Deep Forest Model based Just-In-Time Defect Prediction for Android Mobile Apps" has been accepted to QRS'20.
  • [05/2020] Our paper entitled "All Your App Links are Belong to Us: Understanding the Threats of Instant Apps based Attacks" has been accepted to ESEC/FSE'20.
  • [11/2019] Our paper entitled "Resource Race Attacks on Android" has been accepted to SANER'20.
  • [08/2019] Our paper entitled "Demystifying Application Performance Management Libraries for Android" has been accepted to ASE'19.