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Roopsha Samanta

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titleconferencedate
Explainable Program Synthesis by Localizing SpecificationsOOPSLA 20232023-10-23
Introduces subspecifications that summarize what a subexpression must satisfy given a global spec, provides a two stage algorithm that constructs then…
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Enabling Bounded Verification of Doubly-Unbounded Distributed Agreement-Based S...OOPSLA 20232023-10-23
Presents Venus, an implementation that extends Quicksilver to verify systems that are unbounded in both process count and data by reducing variable domains via…
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ImageEye: Batch Image Processing using Program SynthesisPLDI 20232023-06-17
A synthesis pipeline that learns programs in a neuro-symbolic DSL uses Amazon recognition detectors and an enumerative synthesizer with equivalence-reduction…
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Trace-Guided Inductive Synthesis of Recursive Functional ProgramsPLDI 20232023-06-17
A method augments program search with explicit recursion traces and a new version space algebra that represents pairs of traces and programs under angelic…
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Business Meeting - PLDI 2022PLDI 20222022-06-13
PLDI 2022 reports concrete process changes: a single flat PC of 120 with four area chairs, no full PC meeting, and asynchronous discussion; paper assignment…
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HACCLE: Metaprogramming for Secure Multi-Party ComputationGPCE 20212021-10-17
HACCLE is a compiler toolchain that embeds a DSL (Harpoon) in Scala, uses LMS metaprogramming to lower code to a protocol‑independent acyclic circuit IR (HIR)…
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QuickSilver: Modeling and Parameterized Verification for Distributed Agreement-Based SystemsOOPSLA 20212021-10-17
QuickSilver introduces the Mercury modeling language with two concrete agreement primitives, Partition and Consensus, that abstract verified Paxos/Raft-style…
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Program Synthesis: A Dream Realized?Strange Loop 20212021-09-30
Claims a semantics-guided pipeline that augments user examples with relational properties and feeds them to existing inductive synthesizers; implements a…
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MANTIS: Semantics-driven Inductive Program SynthesisCode Mesh LDN 20202020-11-05
MANTIS applies semantic biases by augmenting user examples with relational perturbation properties (e.g., permutation invariance, value preservation) and then…
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