Evo-Clocks: Software Evolution at a Glance

Abstract

Understanding the evolution of a project is crucial in reverse-engineering, auditing and otherwise understanding existing software. Visualizing how software evolves can be challenging, as it typically abstracts a multi-dimensional graph structure where individual components undergo frequent but localized changes. Existing approaches typically consider either only a small number of revisions or they focus on one particular aspect, such as the evolution of code metrics or architecture. Approaches using a static view with a time axis (such as line charts) are limited in their expressiveness regarding structure, and approaches visualizing structure quickly become cluttered with an increasing number of revisions and components. We propose a novel trade-off between displaying global structure over a large time period with reduced accuracy and visualizing fine-grained changes of individual components with absolute accuracy. We demonstrate how our approach displays changes by blending redundant visual features (such as scales or repeating data points) where they are not expressive. We show how using this approach to explore software evolution can reveal ephemeral information when familiarizing oneself with a new project. We provide a working implementation as an extension to our open-source library for fine-grained evolution analysis, LISA.

The State of the Art in Visualizing Dynamic Multivariate Networks

“…Multiple encodings have been designed by customizing these marks for some specific data types and tasks to address the challenges in showing changes in structure and attributes together. Figure 14 shows two common approaches: On‐node encoding [PGFL05,APBG19] and On‐edge encoding [LL16].…”

“…Each node is also embedded with a small time‐series chart highlighting the temporal trend of the group. Alexandru et al [APBG19] use hierarchies present in the software components to drive the node positions in the network layout.…”

“…If an edge is not present in a time step t i , the i th segment of the edge will be grayed out. Alexandru et al's Evo‐Clocks [APBG19] also uses a glyph to embed multiple attributes on nodes in the DMVN representing evolution of a project software.…”

Leveraging Structural Properties of Source Code Graphs for Just-In-Time Bug Prediction

“…Visualizing a software system can help to analyze the evolution of software architecture, identify the developer network, find stable software releases, and monitor software quality trends [Diehl (2007a)]. A rich body of studies [Alexandru et al (2019); Burch et al (2011); Kim et al (2020);Sandoval Alcocer et al (2013); Tomida et al (2019)] explored different ways to visualize evolving software systems for making it easily understandable to keep the consistent evolution. Chevalier et al (2007) did a visualization of evolution patterns in C++ source code by rendering syntax matched code blocks in consecutive versions to detect the code fragments which have been changed during evolution.…”

ViBERT: Visual Behavior Regression Testing

“…Visual clues such as color, shape, and metaphors ease the cognitive load of understanding software systems [7] [40]. Numerous research has been proposed and various tools have been built to visualize different aspects of software systems, such as static program structures [11] [17] [21], dynamic program executions [8][14] [16][29], software evolution [6] [9], and debugging results [12].…”