738 research outputs found
Code Flows: Visualizing Structural Evolution of Source Code
No full textUnderstanding detailed changes done to source code is of great importance in software maintenance. We present Code Flows, a method to visualize the evolution of source code geared to the understanding of fine and mid-level scale changes across several file versions. We enhance an existing visual metaphor to depict software structure changes with techniques that emphasize both following unchanged code as well as detecting and highlighting important events such as code drift, splits, merges, insertions and deletions. The method is illustrated with the analysis of a real-world C++ code system.
sj-pdf-1-ivi-10.1177_14738716221086589 – Supplemental material for Visual cluster separation using high-dimensional sharpened dimensionality reduction
No full textSupplemental material, sj-pdf-1-ivi-10.1177_14738716221086589 for Visual cluster separation using high-dimensional sharpened dimensionality reduction by Youngjoo Kim, Alexandru C Telea, Scott C Trager and Jos BTM Roerdink in Information Visualization</p
Robust Feature Detection and Local Classification for Surfaces Based on Moment Analysis
No full textThe stable local classification of discrete surfaces with respect to features such as edges and corners or concave and convex regions, respectively, is as quite difficult as well as indispensable for many surface processing applications. Usually, the feature detection is done via a local curvature analysis. If concerned with large triangular and irregular grids, e.g., generated via a marching cube algorithm, the detectors are tedious to treat and a robust classification is hard to achieve. Here, a local classification method on surfaces is presented which avoids the evaluation of discretized curvature quantities. Moreover, it provides an indicator for smoothness of a given discrete surface and comes together with a built-in multiscale. The proposed classification tool is based on local zero and first moments on the discrete surface. The corresponding integral quantities are stable to compute and they give less noisy results compared to discrete curvature quantities. The stencil width for the integration of the moments turns out to be the scale parameter. Prospective surface processing applications are the segmentation on surfaces, surface comparison, and matching and surface modeling. Here, a method for feature preserving fairing of surfaces is discussed to underline the applicability of the presented approach.
Evaluating Visual Realism in Drawing Areas of Interest on UML Diagrams
No full textAreas of interest (AOIs) are defined as an addition to UML diagrams: groups of elements of system architecture diagrams that share some common property. Some methods have been proposed to automatically draw AOIs on UML diagrams. However, it is not clear how users perceive the results of such methods as compared to human-drawn areas of interest. We present here a process of studying and improving the perceived quality of computer-drawn AOIs. We qualitatively evaluated how users perceive the quality of computer- and human-drawn AOIs, and used these results to improve an existing algorithm for drawing AOIs. Finally, we designed a quantitative comparison for AOI drawings and used it to show that our improved renderings are closer to human drawings than the original rendering algorithm results. The combined user evaluation, algorithmic improvements, and quantitative comparison support our claim of improving the perceived quality of AOIs rendered on UML diagrams.
Comparison of Node-Link and Hierarchical Edge Bundling Layouts: A User Study
No full textVisually investigating large network-like structures is a challenging task.
Several approaches have been proposed in the past: node-link diagrams,
adjacency matrices, and, more recently, hierarchical edge bundles. We present a
recent experiment that compares the effectiveness of the classical node-link diagrams with the more recent hierarchical bundled edges. The users involved several computer science practitioners, the data ranged from graphs of several hundreds to several tens of hundreds of nodes, the tasks involved answering a number of structural overview as well as detailed questions involved system dependencies
Texture-based Visualization of Metrics on Software Architectures
No full textWe present a method that combines textures, blending, and scattered-data interpolation to visualize several metrics defined on overlapping areas-of-interest on UML class diagrams. We aim to simplify the task of visually correlating the distribution and outlier values of a multivariate metric dataset with a system’s structure. We illustrate our method on a class diagram of a real-world system.
A Tool for Optimizing the Build Performance of Large Software Code Bases
No full textWe present Build Analyzer, a tool that helps developers optimize the build performance of huge systems written in C. Due to complex C header dependencies, even small code changes can cause extremely long rebuilds, which are problematic when code is shared and modified by teams of hundreds of individuals. Build Analyzer supports several use cases. For developers, it provides an estimate of the build impact and distribution caused by a given change. For architects, it shows why a build is costly, how its cost is spread over the entire code base, which headers cause build bottlenecks, and suggests ways to refactor these to reduce the cost. We demonstrate Build Analyzer with a use-case on a real industry code base.
Skeletonization and segmentation of binary voxel shapes
No full textPreface. This dissertation is the result of research that I conducted between January 2005 and December 2008 in the Visualization research group of the Technische Universiteit Eindhoven. I am pleased to have the opportunity to thank a number of people that made this work possible. I owe my sincere gratitude to Alexandru Telea, my supervisor and first promotor. I did not consider pursuing a PhD until my Master’s project, which he also supervised. Due to our pleasant collaboration from which I learned quite a lot, I became convinced that becoming a doctoral student would be the right thing to do for me. Indeed, I can say it has greatly increased my knowledge and professional skills. Alex, thank you for our interesting discussions and the freedom you gave me in conducting my research. You made these four years a pleasant experience. I am further grateful to Jack vanWijk, my second promotor. Our monthly discussions were insightful, and he continuously encouraged me to take a more formal and scientific stance. I would also like to thank Prof. Jan de Graaf from the department of mathematics for our discussions on some of my conjectures. His mathematical rigor was inspiring. I am greatly indebted to the Netherlands Organisation for Scientific Research (NWO) for funding my PhD project (grant number 612.065.414). I thank Prof. Kaleem Siddiqi, Prof. Mark de Berg, and Dr. Remco Veltkamp for taking part in the core doctoral committee and Prof. Deborah Silver and Prof. Jos Roerdink for participating in the extended committee. Our Visualization group provides a great atmosphere to do research in. In particular, I would like to thank my fellow doctoral students Frank van Ham, Hannes Pretorius, Lucian Voinea, Danny Holten, Koray Duhbaci, Yedendra Shrinivasan, Jing Li, NielsWillems, and Romain Bourqui. They enabled me to take my mind of research from time to time, by discussing political and economical affairs, and more trivial topics. Furthermore, I would like to thank the senior researchers of our group, Huub van de Wetering, Kees Huizing, and Michel Westenberg. In particular, I thank Andrei Jalba for our fruitful collaboration in the last part of my work. On a personal level, I would like to thank my parents and sister for their love and support over the years, my friends for providing distractions outside of the office, and Michelle for her unconditional love and ability to light up my mood when needed
Combining Extended Table Lens and Treemap Techniques for Visualizing Tabular Data
No full textWe present a framework for visualizing large tabular data that combines two views: the table view and the treemap view. The table view extends the known table lens as follows: We cluster related elements to reduce subsampling artifacts and achieve table size independent rendering time; we use multiple-column sorting to create scenario-specific data hierarchies on the fly; and we use shaded cushions to show data structure and variation. Hierarchies built in the table view are shown in a customizable treemap view. One can choose both layout and rendering by a few clicks, effectively creating visual scenarios on-the-fly. We illustrate our framework on real-life stock data.
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