Learning programs from noisy data

DOI10.1145/2837614.2837671zbMath1347.68092OpenAlexW2238673293MaRDI QIDQ2828319

Martin Vechev, Veselin Raychev, Andreas Krause, Pavol Bielik

Publication date: 24 October 2016

Published in: Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1145/2837614.2837671

zbMATH Keywords

regularizationnoisy dataprogram synthesisanomaly detectionbig codestatistical code completion

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Mathematical aspects of software engineering (specification, verification, metrics, requirements, etc.) (68N30)

Related Items (3)

Introduction to Model Checking ⋮ Bootstrapping library-based synthesis ⋮ Learning analysis strategies for Octagon and context sensitivity from labeled data generated by static analyses

Uses Software

• CheckCell

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