To address this problem, we propose a novel optimization strategy that uses domain and contextual information to optimize the performance of constraint solvers ...
To address this problem, we propose a novel optimization strategy that uses domain and contextual information to optimize the performance of constraint solvers ...
This paper proposes a new fashion of symbolic execution, named Speculative Symbolic Execution (SSE), to speed up symbolic execution by reducing the ...
Mar 23, 2023 · Ikpeme Erete, Alessandro Orso: Optimizing Constraint Solving to Better Support Symbolic Execution. ICST Workshops 2011: 310-315.
Feb 16, 2023 · We propose a machine learning-based method to improve the efficiency of the CEGAR-based array constraint solving.
Missing: Optimizing | Show results with:Optimizing
In this talk, I start by presenting the state of the art in dynamic symbolic execution, including its main enablers, namely mixed concrete/symbolic execution, ...
Symbolic execution executes programs with symbolic inputs and systematically analyzes program behaviors by exploring all feasible paths.
Missing: Support | Show results with:Support
The existing approaches for optimizing the constraint solv- ing in symbolic execution do the optimizations before invoking the solver, such as caching [5], ...
By aggressively following paths for which feasibility can be quickly determined without using a con- straint solver, our approach can minimise the constraint ...
Mar 18, 2020 · Techniques like Green and GreenTrie reuse constraint solutions to speed up constraint solving for symbolic execution; however, these reuse ...
Missing: Optimizing | Show results with:Optimizing