9 Result(s)
within
Alex Aiken
Software Engineering
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Chapter and Conference Paper
Inferring Invariants with Quantifier Alternations: Taming the Search Space Explosion
We present a PDR/IC3 algorithm for finding inductive invariants with quantifier alternations. We tackle scalability issues that arise due to the large search space of quantified invariants by combining a bread...
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Chapter and Conference Paper
A Data Driven Approach for Algebraic Loop Invariants
We describe a Guess-and-Check algorithm for computing algebraic equation invariants of the form ∧ i f i (x ...
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Chapter and Conference Paper
Minimum Satisfying Assignments for SMT
A minimum satisfying assignment of a formula is a minimum-cost partial assignment of values to the variables in the formula that guarantees the formula is true. Minimum satisfying assignments have applications in...
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Chapter and Conference Paper
Interpolants as Classifiers
We show how interpolants can be viewed as classifiers in supervised machine learning. This view has several advantages: First, we are able to use off-the-shelf classification techniques, in particular support ...
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Chapter and Conference Paper
Reasoning about Lock Placements
A lock placement describes, for each heap location, which lock guards the location, and under what circumstances. We formalize methods for reasoning about lock placements, making precise the interactions between ...
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Chapter and Conference Paper
Simplifying Loop Invariant Generation Using Splitter Predicates
We present a novel static analysis technique that substantially improves the quality of invariants inferred by standard loop invariant generation techniques. Our technique decomposes multi-phase loops, which requ...
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Chapter and Conference Paper
Fluid Updates: Beyond Strong vs. Weak Updates
We describe a symbolic heap abstraction that unifies reasoning about arrays, pointers, and scalars, and we define a fluid update operation on this symbolic heap that relaxes the dichotomy between strong and weak ...
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Chapter and Conference Paper
Cuts from Proofs: A Complete and Practical Technique for Solving Linear Inequalities over Integers
We propose a novel, sound, and complete Simplex-based algorithm for solving linear inequalities over integers. Our algorithm, which can be viewed as a semantic generalization of the branch-and-bound technique, sy...
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Chapter and Conference Paper
Saturn: A SAT-Based Tool for Bug Detection
Saturn is a boolean satisfiability (SAT) based framework for static bug detection. Saturn targets software written in C and is designed to support a wide range of property checkers.
