Issue Downloads
Adversities in Abstract Interpretation - Accommodating Robustness by Abstract Interpretation
Robustness is a key and desirable property of any classifying system, in particular, to avoid the ever-rising threat of adversarial attacks. Informally, a classification system is robust when the result is not affected by the perturbation of the input. ...
Homeostasis: Design and Implementation of a Self-Stabilizing Compiler
Mainstream compilers perform a multitude of analyses and optimizations on the given input program. Each analysis (such as points-to analysis) may generate a program-abstraction (such as points-to graph). Each optimization is typically composed of multiple ...
CFLOBDDs: Context-Free-Language Ordered Binary Decision Diagrams
This article presents a new compressed representation of Boolean functions, called CFLOBDDs (for Context-Free-Language Ordered Binary Decision Diagrams). They are essentially a plug-compatible alternative to BDDs (Binary Decision Diagrams), and hence are ...
Decomposition-based Synthesis for Applying Divide-and-Conquer-like Algorithmic Paradigms
Algorithmic paradigms such as divide-and-conquer (D&C) are proposed to guide developers in designing efficient algorithms, but it can still be difficult to apply algorithmic paradigms to practical tasks. To ease the usage of paradigms, many research ...
