Learning analysis strategies for Octagon and context sensitivity from labeled data generated by static analyses

DOI10.1007/s10703-017-0306-7zbMath1425.68070OpenAlexW2770096704MaRDI QIDQ1791273

Kihong Heo, Hakjoo Oh, Hongseok Yang

Publication date: 4 October 2018

Published in: Formal Methods in System Design (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10703-017-0306-7

zbMATH Keywords

static analysismachine learningcontext-sensitivityrelational analysis

Mathematics Subject Classification ID

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

Uses Software

• Apron
• Scikit
• ASTREE
• PMTK
• Sparrow

Cites Work

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• An empirical study on classification methods for alarms from a bug-finding static C analyzer
• The octagon abstract domain
• Abstraction refinement guided by a learnt probabilistic model
• Learning programs from noisy data
• A Data Driven Approach for Algebraic Loop Invariants
• Random forests

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