Na Meng

Associate Professor
Computer Science
Virginia Tech

Gilbert Place, Room 4311A

Na Meng is an Associate Professor in the Department of Computer Science at Virginia Tech since 2021. She received her B.E. in Software Engineering from Northeastern University (NEU) in China in 2006, and received her M.S. in Computer Science from Peking University in China in 2009. She obtained her Ph.D. in Computer Science from The University of Texas at Austin in 2014, advised by Miryung Kim and Kathryn S. McKinley. She started working in Virginia Tech as an Assistant Professor in 2015. Her research interests include Software Engineering, Programming Languages, Software Security, and Artificial Intelligence. Her research group NiSE (iNnovations in Software Engineering) conduct various empirical studies and propose novel automatic approaches. The research mission is to reveal unknown and interesting phenomena in current software practices, to invent new tools that facilitate better software development and maintenance in the future, and to help with secure coding practices by developers. In particular, the group developed machine learning-based approaches to analyze source code and to predict developers' maintenance needs in the future. They also developed software engineering-based or programming language-based approaches to improve AI techniques. Dr. Meng received the NSF CAREER Award in 2019. Her research has been supported by NSF and ONR.


04/2024: Our paper on "ConflictBench: A Benchmark to Evaluate Software Merge Tools" was accepted by Journal of Systems and Software!

04/2024: Our project on "AI-Accessibility: reconceiving the inclusive co-design of building elements and navigation software" has received a funding from ICAT of VT!

02/2024: Our paper on "Methods and Benchmark for Detecting Cryptographic API Misuses in Python" was accepted by TSE!

01/2024: Our paper on "Understanding the Impact of Branch Edit Features for the Automatic Prediction of Merge Conflict Resolutions" was accepted by the RENE track of ICPC 2024!

12/2023: Our project on "An Empirical Evaluation of Large Language Models (LLMs) in Generating Security Tests to Mitigate Supply Chain Attacks" has received a funding from the Supply Chain Cybersecurity Program by CCI SWVA!

12/2023: Our paper on "Compiler-directed Migrating API Callsite of Client Code" was accepted by ICSE 2024!

12/2023: Our paper one "Broadly Enabling KLEE to Effortlessly Find Unrecoverable Errors in Rust" was accepted by ICSE SEIP 2024!

Current Students

Bowen Shen (PhD student, Fall 2018 - )
Md Mahir Asef Kabir (PhD student, Fall 2019 - )
Sheikh Shadab Towqir (PhD student, Spring 2020 - )
Sheik Murad Hassan Anik (PhD student, Spring 2020 - )
Waad Aldndni (PhD student, Spring 2022 - )
Rishith Gandham (MS student, Summer 2023 - )


CS6704: Software Engineering Research [Spring17][Spring19][Spring21]
CS5704: Software Engineering [Spring16][Spring18][Spring20][Spring24]
CS3304: Comparative Languages [Fall16][Fall17][Fall18][Fall20]
CS3704: Intermediate Software Design and Engineering [Fall15][Fall19][Spring22][Fall23]

Selected Research Topics

Security coding practices[SecDev22][ICPC22][IEEE S&P'22][TSE22][SecDev20][TIFS19][ICSE19][ICSE18]
Artificial intelligence and software engineering[IJCNN21][TDSC19][ICSME18a][ICSME17a]
Automated program generation[ESEC/FSE21][ITiCSE21][IJCAI19]
Automated program transformations [ASE20][ICPC19][MOBILESoft18][ICSE15][ICSE13][PLDI11]
Software bugs and fixes[ASE22][TOSEM'22][SANER22][ICSE21][JSS19][ICSME18b][EMSE17][ICSME17b][ICPC17]
Program comprehension[ICSE20][LCTES19][JSS18]
Cyber-Physical Systems[JOBE'22][CRC22]


System to uncover root cause of non-deterministic (flaky) tests (Patent Number 9,311,220).
Jungwoo Ha, Jaeheon Yi, Peter Dinges, Jeremy Manson, Caitlin Harrison Sadowski, Na Meng


The implementations from nearly all of my publications are publicly available. Other researchers have used several of these implementations in their publications. See projects and GitHub for details.


ONR N00014-22-1-2057, NSF-2006278, NSF-1929701, NSF-1845446, ONR N00014-17-1-2498, NSF-1565827

Graduated Students