40 citations · 66 across the 4 of their papers we have counts for
5 papers
Deep Learning for Bug-Localization in Student Programs
Rahul Gupta, Aditya Kanade, Shirish Shevade
Providing feedback is an integral part of teaching. Most open online courses on programming make use of automated grading systems to support programming assignments and give real-t…
A framework for the extraction of Deep Neural Networks by leveraging public data
Soham Pal, Yash Gupta, Aditya Shukla +3
Machine learning models trained on confidential datasets are increasingly being deployed for profit. Machine Learning as a Service (MLaaS) has made such models easily accessible to…
Deep Reinforcement Learning for Programming Language Correction
Rahul Gupta, Aditya Kanade, Shirish Shevade
Novice programmers often struggle with the formal syntax of programming languages. To assist them, we design a novel programming language correction framework amenable to reinforce…
Semi-Supervised Verified Feedback Generation
Shalini Kaleeswaran, Anirudh Santhiar, Aditya Kanade +1
Students have enthusiastically taken to online programming lessons and contests. Unfortunately, they tend to struggle due to lack of personalized feedback when they make mistakes.…
A Logic for Correlating Temporal Properties across Program Transformations
Aditya Kanade, Amitabha Sanyal, Uday P. Khedker
Program transformations are widely used in synthesis, optimization, and maintenance of software. Correctness of program transformations depends on preservation of some important pr…