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20152026
most citedOptimal and Perfectly Parallel Algorithms for On-demand Data-flow Analysis

15 citations · 66 across the 23 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.PL2020★ 1 cited

Quantitative Analysis of Assertion Violations in Probabilistic Programs

Jinyi Wang, Yican Sun, Hongfei Fu +2

In this work, we consider the fundamental problem of deriving quantitative bounds on the probability that a given assertion is violated in a probabilistic program. We provide autom…

cs.PL2020

Concentration-Bound Analysis for Probabilistic Programs and Probabilistic Recurrence Relations

Jinyi Wang, Yican Sun, Hongfei Fu +3

Analyzing probabilistic programs and randomized algorithms are classical problems in computer science. The first basic problem in the analysis of stochastic processes is to conside…

cs.PL2020★ 1 cited

Inductive Reachability Witnesses

Ali Asadi, Krishnendu Chatterjee, Hongfei Fu +2

In this work, we consider the fundamental problem of reachability analysis over imperative programs with real variables. The reachability property requires that a program can reach…

cs.DS2020★ 1 cited

Faster Algorithms for Quantitative Analysis of Markov Chains and Markov Decision Processes with Small Treewidth

Ali Asadi, Krishnendu Chatterjee, Amir Kafshdar Goharshady +2

Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting pro…

cs.DS2020★ 15 cited

Optimal and Perfectly Parallel Algorithms for On-demand Data-flow Analysis

Krishnendu Chatterjee, Amir Kafshdar Goharshady, Rasmus Ibsen-Jensen +1

Interprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointer…