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20032026
most citedSemantic Robustness of Models of Source Code

76 citations · 344 across the 30 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.LG2021

Neural Program Generation Modulo Static Analysis

Rohan Mukherjee, Yeming Wen, Dipak Chaudhari +3

State-of-the-art neural models of source code tend to be evaluated on the generation of individual expressions and lines of code, and commonly fail on long-horizon tasks such as th…

cs.SE2021

Lightweight, Multi-Stage, Compiler-Assisted Application Specialization

Mohannad Alhanahnah, Rithik Jain, Vaibhav Rastogi +2

Program debloating aims to enhance the performance and reduce the attack surface of bloated applications. Several techniques have been recently proposed to specialize programs. The…

cs.PL2021★ 1 cited

Synthesizing Abstract Transformers

Pankaj Kumar Kalita, Sujit Kumar Muduli, Loris D'Antoni +2

This paper addresses the problem of creating abstract transformers automatically. The method we present automates the construction of static analyzers in a fashion similar to the w…

cs.PL2021★ 1 cited

Sound Probabilistic Inference via Guide Types

Di Wang, Jan Hoffmann, Thomas Reps

Probabilistic programming languages aim to describe and automate Bayesian modeling and inference. Modern languages support programmable inference, which allows users to customize i…

cs.PL2021★ 2 cited

Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems

Di Wang, Jan Hoffmann, Thomas Reps

In this article, we present a semantics-level adaption of the Optional Stopping Theorem, sketch an expected-cost analysis as its application, and survey different variants of the O…

cs.SE2021

Shipwright: A Human-in-the-Loop System for Dockerfile Repair

Jordan Henkel, Denini Silva, Leopoldo Teixeira +2

Docker is a tool for lightweight OS-level virtualization. Docker images are created by performing a build, controlled by a source-level artifact called a Dockerfile. We studied Doc…

cs.PL2021

Synthesis with Asymptotic Resource Bounds

Qinheping Hu, John Cyphert, Loris D'Antoni +1

We present a method for synthesizing recursive functions that satisfy both a functional specification and an asymptotic resource bound. Prior methods for synthesis with a resource…