107 citations · 1k across the 45 of their papers we have counts for
12 papers · 1 filter
SyGuS-Comp 2017: Results and Analysis
Rajeev Alur, Dana Fisman, Rishabh Singh +1
Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula phi in a background the…
Data-Driven Feedback Generation for Introductory Programming Exercises
Ke Wang, RIshabh Singh, Zhendong Su
This paper introduces the "Search, Align, and Repair" data-driven program repair framework to automate feedback generation for introductory programming exercises. Distinct from exi…
WebRelate: Integrating Web Data with Spreadsheets using Examples
Jeevana Priya Inala, Rishabh Singh
Data integration between web sources and relational data is a key challenge faced by data scientists and spreadsheet users. There are two main challenges in programmatically joinin…
Not all bytes are equal: Neural byte sieve for fuzzing
Mohit Rajpal, William Blum, Rishabh Singh
Fuzzing is a popular dynamic program analysis technique used to find vulnerabilities in complex software. Fuzzing involves presenting a target program with crafted malicious input…
Dynamic Neural Program Embedding for Program Repair
Ke Wang, Rishabh Singh, Zhendong Su
Neural program embeddings have shown much promise recently for a variety of program analysis tasks, including program synthesis, program repair, fault localization, etc. However, m…
Semantic Code Repair using Neuro-Symbolic Transformation Networks
Jacob Devlin, Jonathan Uesato, Rishabh Singh +1
We study the problem of semantic code repair, which can be broadly defined as automatically fixing non-syntactic bugs in source code. The majority of past work in semantic code rep…