CuboidMatrix: Exploring Dynamic Structural Connections in Software Components Using Space-Time Cube

Schneider, Teseo; Tymchuk, Yuriy; Salgado, Ronie; Bergel, Alexandre

doi:10.1109/vissoft.2016.17

Cited by 15 publications

(6 citation statements)

References 24 publications

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“…In Matrix Cube , each time step is represented as an adjacency matrix and the matrices are stacked along a third dimension (Figure 8c) to create a cube representation. Following the same space‐time cube metaphor, Schneider et al [STSB16] created CuboidMatrix. Another way to arrange multiple time steps is to integrate multiple time steps with explicit links to connect same entities across time steps (Figure 8d).…”

Section: Design Space Of Dynamic Multivariate Networkmentioning

confidence: 99%

The State of the Art in Visualizing Dynamic Multivariate Networks

Kale

Sun

Papka

2023

Computer Graphics Forum

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Most real‐world networks are both dynamic and multivariate in nature, meaning that the network is associated with various attributes and both the network structure and attributes evolve over time. Visualizing dynamic multivariate networks is of great significance to the visualization community because of their wide applications across multiple domains. However, it remains challenging because the techniques should focus on representing the network structure, attributes and their evolution concurrently. Many real‐world network analysis tasks require the concurrent usage of the three aspects of the dynamic multivariate networks. In this paper, we analyze current techniques and present a taxonomy to classify the existing visualization techniques based on three aspects: temporal encoding, topology encoding, and attribute encoding. Finally, we survey application areas and evaluation methods; and discuss challenges for future research.

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Section: Design Space Of Dynamic Multivariate Networkmentioning

confidence: 99%

The State of the Art in Visualizing Dynamic Multivariate Networks

Kale

Sun

Papka

2023

Computer Graphics Forum

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“…ShiViz allows users to filter events and executions to reduce the visual load. Other techniques, such as aggregating the events or data [105], visualizing heatmaps [7,67], bundling edges [118], or animating the visualization [70] can also manage long executions. Inherently, these techniques aim to abstract away some details of the execution to make it possible to visualize a larger execution, while ShiViz aims to show as many details as is reasonable to help developers understand the relevant behavior.…”

Section: Visualizing Distributed Systemsmentioning

confidence: 99%

Visualizing Distributed System Executions

Beschastnikh

Liu

Xing

et al. 2020

ACM Trans. Softw. Eng. Methodol.

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Distributed systems pose unique challenges for software developers. Understanding the system’s communication topology and reasoning about concurrent activities of system hosts can be difficult. The standard approach, analyzing system logs, can be a tedious and complex process that involves reconstructing a system log from multiple hosts’ logs, reconciling timestamps among hosts with non-synchronized clocks, and understanding what took place during the execution encoded by the log. This article presents a novel approach for tackling three tasks frequently performed during analysis of distributed system executions: (1) understanding the relative ordering of events, (2) searching for specific patterns of interaction between hosts, and (3) identifying structural similarities and differences between pairs of executions. Our approach consists of XVector , which instruments distributed systems to capture partial ordering information that encodes the happens-before relation between events, and ShiViz , which processes the resulting logs and presents distributed system executions as interactive time-space diagrams. Two user studies with a total of 109 students and a case study with 2 developers showed that our method was effective, helping participants answer statistically significantly more system-comprehension questions correctly, with a very large effect size.

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“…CuboidMatrix (Schneider et al, 2016) is a visualization that uses a space-time metaphor to support users on understanding software evolution. Thus, users can navigate the space-time visualization to solve software comprehension tasks.…”

Section: Classification By Information Visualization Techniquesmentioning

confidence: 99%

A Systematic Literature Review of Modern Software Visualization

Chotisarn,

Merino,

Zheng

et al. 2020

Preprint

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We report on the state-of-the-art of software visualization. To ensure reproducibility, we adopted the Systematic Literature Review methodology. That is, we analyzed 1440 entries from IEEE Xplore and ACM Digital Library databases. We selected 105 relevant full papers published in 2013-2019, which we classified based on the aspect of the software system that is supported (i.e., structure, behavior, and evolution). For each paper, we extracted main dimensions that characterize software visualizations, such as software engineering tasks, roles of users, information visualization techniques, and media used to display visualizations. We provide researchers in the field an overview of the state-of-the-art in software visualization and highlight research opportunities. We also help developers to identify suitable visualizations for their particular context by matching software visualizations to development concerns and concrete details to obtain available visualization tools.

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CuboidMatrix: Exploring Dynamic Structural Connections in Software Components Using Space-Time Cube

Cited by 15 publications

References 24 publications

The State of the Art in Visualizing Dynamic Multivariate Networks

The State of the Art in Visualizing Dynamic Multivariate Networks

Visualizing Distributed System Executions

A Systematic Literature Review of Modern Software Visualization

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