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P. Madhusudan

University of Illinois at Urbana-Champaign

6 papers hereh-index 419.4k citations121 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.PL4
  • cs.DC1
  • cs.LO1
affiliations
  • University of Illinois at Urbana-Champaign
Homepage
same name
  • P. Madhusudan — 8 papers, h 7
  • P. Madhusudan — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122018
most citedSequentializing Parameterized Programs

26 citations · 39 across the 4 of their papers we have counts for

collaborators
Showing cs.PLShow all

4 papers · 1 filter

cs.PL2018

Decidable Verification of Uninterpreted Programs

Umang Mathur, P. Madhusudan, Mahesh Viswanathan

We study the problem of completely automatically verifying uninterpreted programs---programs that work over arbitrary data models that provide an interpretation for the constants,…

cs.PL2018

Invariant Synthesis for Incomplete Verification Engines

Daniel Neider, Pranav Garg, P. Madhusudan +2

We propose a framework for synthesizing inductive invariants for incomplete verification engines, which soundly reduce logical problems in undecidable theories to decidable theorie…

cs.PL2013

Quantified Data Automata on Skinny Trees: an Abstract Domain for Lists

Pranav Garg, P. Madhusudan, Gennaro Parlato

We propose a new approach to heap analysis through an abstract domain of automata, called automatic shapes. The abstract domain uses a particular kind of automata, called quantifie…

cs.PL2013★ 13 cited

Learning Universally Quantified Invariants of Linear Data Structures

Pranav Garg, Christof Loding, P. Madhusudan +1

We propose a new automaton model, called quantified data automata over words, that can model quantified invariants over linear data structures, and build poly-time active learning…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.