VEIL: Reading Control Flow Graphs Like Code
November 07, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
arXiv ID
2511.05066
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.GR
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Control flow graphs (CFGs) are essential tools for understanding program behavior, yet the size of real-world CFGs makes them difficult to interpret. With thousands of nodes and edges, sophisticated graph drawing algorithms are required to present them on screens in ways that make them readable and understandable. However, being designed for general graphs, these algorithms frequently break the natural flow of execution, placing later instructions before earlier ones and obscuring critical program structures. In this paper, we introduce a set of criteria specifically tailored for CFG visualization, focusing on preserving execution order and making complex structures easier to follow. Building on these criteria, we present VEIL, a new layout algorithm that uses dominator analysis to produce clearer, more intuitive CFG layouts. Through a study of CFGs from real-world applications, we show how our method improves readability and provides improved layout performance compared to state of the art graph drawing techniques.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted