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A Machine-Learning Algorithm with Disjunctive Model for Data-Driven Program Analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Constraint-based type inference and parametric polymorphism
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Learning a Strategy for Choosing Widening Thresholds from a Large Codebase
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Large Spurious Cycle in Global Static Analyses and Its Algorithmic Mitigation
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Efficient and Effective Handling of Exceptions in Java Points-to Analysis
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Learning a Variable-Clustering Strategy for Octagon from Labeled Data Generated by a Static Analysis
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Making k-Object-Sensitive Pointer Analysis More Precise with Still k-Limiting
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Learning analysis strategies for octagon and context sensitivity from labeled data generated by static analyses
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The octagon abstract domain
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Machine-Learning-Guided Selectively Unsound Static Analysis
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Parameterized object sensitivity for points-to analysis for Java
inferredcites →https://doi.org/10.1145/1094811.1094817openalex-snapshot
Demand-driven points-to analysis for Java
inferredcites →https://doi.org/10.1145/1108768.1108797openalex-snapshot
Evaluating the impact of context-sensitivity on Andersen's algorithm for Java programs
inferredcites →https://doi.org/10.1145/1108792.1108797openalex-snapshot
Evaluating the impact of context-sensitivity on Andersen's algorithm for Java programs
inferredcites →https://doi.org/10.1145/1133255.1134027openalex-snapshot
Refinement-based context-sensitive points-to analysis for Java
inferredcites →https://doi.org/10.1145/1133981.1134027openalex-snapshot
Refinement-based context-sensitive points-to analysis for Java
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The trace partitioning abstract domain
inferredcites →https://doi.org/10.1145/1391984.1391987openalex-snapshot
Evaluating the benefits of context-sensitive points-to analysis using a BDD-based implementation
inferredcites →https://doi.org/10.1145/1639949.1640108openalex-snapshot
Strictly declarative specification of sophisticated points-to analyses
inferredcites →https://doi.org/10.1145/1640089.1640108openalex-snapshot
Strictly declarative specification of sophisticated points-to analyses
inferredcites →https://doi.org/10.1145/1925844.1926391openalex-snapshot
Learning minimal abstractions
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Learning minimal abstractions
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Efficient context-sensitive pointer analysis for C programs
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Context-insensitive alias analysis reconsidered
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Efficient context-sensitive pointer analysis for C programs
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Design and implementation of sparse global analyses for C-like languages
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Hybrid context-sensitivity for points-to analysis
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Selective context-sensitivity guided by impact pre-analysis
inferredcites →https://doi.org/10.1145/2594291.2594327openalex-snapshot
On abstraction refinement for program analyses in Datalog
inferredcites →https://doi.org/10.1145/263698.264352openalex-snapshot
Call graph construction in object-oriented languages
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Proceedings of the 24th ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '97
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Learning a strategy for adapting a program analysis via bayesian optimisation
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On fast large-scale program analysis in Datalog
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Semantic-directed clumping of disjunctive abstract states
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Efficient and precise points-to analysis: modeling the heap by merging equivalent automata
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Sound Non-Statistical Clustering of Static Analysis Alarms
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Data-driven context-sensitivity for points-to analysis
inferredcites →https://doi.org/10.1145/318774.318943openalex-snapshot
Efficient points-to analysis for whole-program analysis
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Effective synchronization removal for Java
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A static analyzer for large safety-critical software
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A static analyzer for large safety-critical software
inferredcites →https://doi.org/10.4230/lipics.ecoop.2015.712openalex-snapshot
Adaptive Context-sensitive Analysis for JavaScript
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Automatically generating features for learning program analysis heuristics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Inferring Empirical Sound Resource Bounds via Symbolic Execution and Linear Programming
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A practical algorithm for learning disjunctive abstraction heuristics in static program analysis
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Precise Data-Driven Approximation for Program Analysis via Fuzzing
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Module-Aware Context Sensitive Pointer Analysis
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Learning Approximate Execution Semantics From Traces for Binary Function Similarity
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Learning graph-based heuristics for pointer analysis without handcrafting application-specific features
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Return of CFA: call-site sensitivity can be superior to object sensitivity even for object-oriented programs
inferred← citeshttps://doi.org/10.1145/3591242openalex-snapshot
Context Sensitivity without Contexts: A Cut-Shortcut Approach to Fast and Precise Pointer Analysis
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Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
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Tai-e: A Developer-Friendly Static Analysis Framework for Java by Harnessing the Good Designs of Classics
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Learning Abstraction Selection for Bayesian Program Analysis
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Falcon: A Fused Approach to Path-Sensitive Sparse Data Dependence Analysis
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Scaling Abstraction Refinement for Program Analyses in Datalog using Graph Neural Networks
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Stack Filtering: Elevating Precision and Efficiency in Rust Pointer Analysis
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The Incredible Shrinking Context... in a Decompiler Near You
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inferred← citeshttps://doi.org/10.1145/3759425.3763378openalex-snapshot
Hallucination-Resilient LLM-Driven Sound and Tunable Static Analysis: A Case of Higher-Order Control-Flow Analysis
inferred← citeshttps://doi.org/10.1145/3763111openalex-snapshot
Towards a Theoretically-Backed and Practical Framework for Selective Object-Sensitive Pointer Analysis
inferred← citeshttps://doi.org/10.1145/3798211openalex-snapshot
Hermes: Making Path-Sensitive Pointer Analysis Scalable for Sparse Value-Flow Analysis
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Cut-Shortcut Whole-Program Pointer Analysis: Re-Imagining Context-Sensitivity without Contexts
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Scalable Machine Learning Methods and Datasets for Software Vulnerability Detection
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