Rahul Gupta

I am a graduate student at department of Computer Science & Automation, Indian Institute of Science, Bangalore. I work in Software Engineering and Analysis Lab (SEAL) with Dr. Aditya Kanade. I completed my B. Tech. in Computer Science and Engineering from Rajasthan Technical University, Kota, Rajasthan.

Research Interests

  • Machine learning for software engineering
  • Program repair
  • Programming education

Publications & Preprints

  • Deep Reinforcement Learning for Syntactic Error Repair in Student Programs. PDF
    Rahul Gupta, Aditya Kanade, Shirish Shevade. AAAI 2019
  • DeepFix: Fixing Common C Language Errors by Deep Learning. PDF
    Rahul Gupta, Soham Pal, Aditya Kanade, Shirish Shevade. AAAI 2017
  • Partial Order Reduction for Event-driven Multi-threaded Programs. PDF
    Pallavi Maiya, Rahul Gupta, Aditya Kanade, Rupak Majumdar. TACAS 2016


  • RLAssist is an end-to-end deep reinforcement learning based programming language (PL) correction framework. This framework makes the PL correction task amenable to reinforcement learning. It also allows solving this task in an unsupervised manner, which was impossible with prior works.
  • DeepFix is an end to end deep learning based program repair framework for fixing common  programming errors (CPEs). DeepFix is capable of localizing and fixing multiple CPEs in a given C program of a limited size. It was tested on thousands of student programming assignment submissions. The tests demonstrated that DeepFix fixed many programs while taking only a few tens of milliseconds per program.
  • EM-Explorer is a proof-of-concept explicit state model checking framework which simulates the Android concurrency semantics given an execution trace of an Android application. It is instantiated with implementations of Vector-clock versions of two Partial Order Reduction (POR) techniques, 1) Dynamic POR (DPOR),  and 2) EM-DPOR (TACAS 2016 paper). The framework was used to compare the above two POR techniques on various popular Android applications. It successfully showed that the latter is often orders of magnitude faster than the former.

Teaching Assistance

  • noc17_ma04: Linear Algebra offered on NPTEL MOOC platform. (Spring '17)
  • E0219: Linear Algebra & Applications. (Fall '16)
  • E0239: Software Reliability Techniques. (Spring '16, '15)

Contact Information

Rahul Gupta
PhD candidate
Department of Computer Science & Automation,
Indian Institute of Science, Bangalore - 560012
email: rahulg on the iisc.ac.in domain

Last updated on Monday, Sep 26, 2018.