Key Research Areas

1. Automated Program Analysis, Software Testing and Verification, AI for Software Engineering

About

1. Dr. Arpita Dutta joined the School of Computing and Electrical Engineering at the Indian Institute of Technology Mandi in June 2026 as an Assistant Professor. Prior to joining IIT Mandi, she was a Senior Postdoctoral Research Fellow in the Department of Computer Science at the National University of Singapore (NUS). She received her Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Kharagpur in 2021 and her M.Tech. in Computer Science and Engineering from the National Institute of Technology Rourkela in 2017. Her research interests span Software Engineering, Programming Languages, and Formal Methods, with a particular focus on software testing, automated fault localization, symbolic execution, program analysis, and software verification. More recently, her research explores the integration of large language models with program analysis techniques to build intelligent tools for software debugging, testing, and maintenance. Dr. Dutta is an active contributor to TracerX (https://github.com/tracer-x/TracerX), an open-source symbolic execution framework, and has published her research in leading international conferences and journals, including the ACM International Symposium on Software Testing and Analysis (ISSTA), the International Conference on Fundamental Approaches to Software Engineering (FASE), and IEEE Transactions on Reliability. Her current research aims to develop scalable, trustworthy, and AI-assisted techniques for improving software quality and reliability.

Recent Publications

1. Arpita Dutta, and Joxan Jaffar, Incremental and Unbounded Loop Analysis, 2025, In ACM SIGPLAN Int. Conf. on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH’25), Singapore
2. Arpita Dutta, Rasool Maghareh, Joxan Jaffar, Sangharatna Godboley, and Xiao Liang Yu, 2025, TracerX: Enhancing Dynamic Symbolic Execution with Weakest Precondition & Deletion Interpolation (Poster). In Int. Joint Conf. On Theory and Practice of Software (ETAPS'25), Hamilton, Canada
3. Arpita Dutta, Rasool Maghareh, Joxan Jaffar, Sangharatna Godboley, and Xiao Liang Yu, 2024, TracerX: Pruning Dynamic Symbolic Execution with Deletion and Weakest Precondition Interpolation (CC). In 27th Int. Conf. on Fundamental Approaches to Software Engineering (FASE’24), Luxembourg, pp. 320-325.

Courses Taught

1. DS-313: Statistical Foundations for Data Science

Faculty Image
Dr. Arpita Dutta

Designation: Assistant Professor