Pranav Garg

Publication Activity (10 Years)

Years Active: 2011-2022
Publications (10 Years): 12

Top Topics

Top Venues

Proc. ACM Program. Lang.

Publications

Pranav Garg, Srinivasan Sengamedu
Example-based Synthesis of Static Analysis Rules. CoRR (2022)
Pranav Garg, Srinivasan H. Sengamedu
Synthesizing code quality rules from examples. Proc. ACM Program. Lang. 6 (OOPSLA2) (2022)
Daniel Neider, P. Madhusudan, Shambwaditya Saha, Pranav Garg, Daejun Park
A Learning-Based Approach to Synthesizing Invariants for Incomplete Verification Engines. J. Autom. Reason. 64 (7) (2020)
Daniel Neider, Shambwaditya Saha, Pranav Garg, P. Madhusudan
Sorcar: Property-Driven Algorithms for Learning Conjunctive Invariants. SAS (2019)
Mohammad Ruhul Amin, Pranav Garg, Baris Coskun
CADENCE: Conditional Anomaly Detection for Events Using Noise-Contrastive Estimation. AISec@CCS (2019)
P. Ezudheen, Daniel Neider, Deepak D'Souza, Pranav Garg, P. Madhusudan
Horn-ICE learning for synthesizing invariants and contracts. Proc. ACM Program. Lang. 2 (OOPSLA) (2018)
Daniel Neider, Pranav Garg, P. Madhusudan, Shambwaditya Saha, Daejun Park
Invariant Synthesis for Incomplete Verification Engines. TACAS (1) (2018)
Deepak D'Souza, P. Ezudheen, Pranav Garg, P. Madhusudan, Daniel Neider
Horn-ICE Learning for Synthesizing Invariants and Contracts. CoRR (2017)
Alex Gyori, Pranav Garg, Edgar Pek, P. Madhusudan
Efficient Incrementalized Runtime Checking of Linear Measures on Lists. ICST (2017)
Edgar Pek, Pranav Garg, Muntasir Raihan Rahman, Karl Palmskog, Indranil Gupta, P. Madhusudan
Inferring Formal Properties of Production Key-Value Stores. CoRR (2017)
Daniel Neider, Pranav Garg, P. Madhusudan, Shambwaditya Saha, Daejun Park
Invariant Synthesis for Incomplete Verification Engines. CoRR (2017)
Pranav Garg, Daniel Neider, P. Madhusudan, Dan Roth
Learning invariants using decision trees and implication counterexamples. POPL (2016)
Pranav Garg, Christof Löding, P. Madhusudan, Daniel Neider
Quantified data automata for linear data structures: a register automaton model with applications to learning invariants of programs manipulating arrays and lists. Formal Methods Syst. Des. 47 (1) (2015)
Shambwaditya Saha, Pranav Garg, P. Madhusudan
Alchemist: Learning Guarded Affine Functions. CAV (1) (2015)
Pranav Garg, Christof Löding, P. Madhusudan, Daniel Neider
ICE: A Robust Framework for Learning Invariants. CAV (2014)
Ankush Desai, Pranav Garg, P. Madhusudan
Natural proofs for asynchronous programs using almost-synchronous reductions. OOPSLA (2014)
Xiaokang Qiu, Pranav Garg, Andrei Stefanescu, Parthasarathy Madhusudan
Natural proofs for structure, data, and separation. PLDI (2013)
Pranav Garg, P. Madhusudan, Gennaro Parlato
Quantified Data Automata on Skinny Trees: an Abstract Domain for Lists CoRR (2013)
Pranav Garg, Franjo Ivancic, Gogul Balakrishnan, Naoto Maeda, Aarti Gupta
Feedback-directed unit test generation for C/C++ using concolic execution. ICSE (2013)
Pranav Garg, Christof Löding, P. Madhusudan, Daniel Neider
Learning Universally Quantified Invariants of Linear Data Structures CoRR (2013)
Pranav Garg, P. Madhusudan, Gennaro Parlato
Quantified Data Automata on Skinny Trees: An Abstract Domain for Lists. SAS (2013)
Pranav Garg, Christof Löding, P. Madhusudan, Daniel Neider
Learning Universally Quantified Invariants of Linear Data Structures. CAV (2013)
Rishi Agarwal, Pranav Garg, Josep Torrellas
Rebound: scalable checkpointing for coherent shared memory. ISCA (2011)
Pranav Garg, P. Madhusudan
Compositionality Entails Sequentializability. TACAS (2011)