Using High-Rising Cities to Visualize Performance in Real-Time

For developers concerned with a performance drop or improvement in their software, a profiler allows a developer to quickly search and identify bottlenecks and leaks that consume much execution time. Non real-time profilers analyze the history of already executed stack traces, while a real-time profiler outputs the results concurrently with the execution of software, so users can know the results instantaneously. However, a real-time profiler risks providing overly large and complex outputs, which is difficult for developers to quickly analyze. In this paper, we visualize the performance data from a real-time profiler. We visualize program execution as a three-dimensional (3D) city, representing the structure of the program as artifacts in a city (i.e., classes and packages expressed as buildings and districts) and their program executions expressed as the fluctuating height of artifacts. Through two case studies and using a prototype of our proposed visualization, we demonstrate how our visualization can easily identify performance issues such as a memory leak and compare performance changes between versions of a program. A demonstration of the interactive features of our prototype is available at https://youtu.be/eleVo19Hp4k.Comment: 10 pages, VISSOFT 2017, Artifact: https://github.com/sefield/high-rising-city-artifac

AMIDA : a Sequence Diagram Extraction Toolkit Supporting Automatic Phase Detection

ICSE Companion '08: Companion of the 30th international conference on Software engineeringLeipzig, GermanyMay 10 - 18, 200

Visualization of graphs and trees for software analysis

A software architecture is an abstraction of a software system, which is indispensable for many software engineering tasks. Unfortunately, in many cases information pertaining to the software architecture is not available, outdated, or inappropriate for the task at hand. The RECONSTRUCTOR project focuses on software architecture reconstruction, i.e., obtaining architectural information from an existing system. Our research, which is part of RECONSTRUCTOR, focuses on interactive visualization and tries to answer the following question: How can users be enabled to understand the large amounts of information relevant for program understanding using visual representations? To answer this question, we have iteratively developed a number of techniques for visualizing software systems. A large number of these cases consists of hierarchically organized data, combined with adjacency relations. Examples are function calls within a hierarchically organized software system and correspondence relations between two different versions of a hierarchically organized software system. Hierarchical Edge Bundles (HEBs) are used to visualize adjacency relations in hierarchically organized data, such as the aforementioned function calls within a software system. HEBs significantly reduce visual clutter by visually bundling relations together. Massive Sequence Views (MSVs) are used in conjunction with HEBs to enable analysis of sequences of relations, such as function-call traces. HEBs are furthermore used to visually compare hierarchically organized data, e.g., two different versions of a software system. HEBs visually emphasize splits, joins, and relocations of subhierarchies and provide for interactive selection of sets of relations. Since HEBs require a hierarchy to perform the bundling, we present Force-Directed Edge Bundles (FDEBs) as an alternative to visually bundle relations together in the absence of a hierarchical component. FDEBs use a self-organizing approach to bundling in which edges are modeled as flexible springs that can attract each other. As a result, visual clutter is reduced and high-level edge patterns are better visible. Finally, in all these methods, a clear depiction of the direction of edges is important. We have therefore performed a separate study in which we evaluated ten representations (including the standard arrow) for depicting directed edges in a controlled user study

Visualizing an Execution Trace as a Compact Sequence Diagram Using Dominance Algorithms

Visualizing an execution trace of an object-oriented system as sequence diagrams is effective to understand the behavior of the system. However, sequence diagrams extracted from an execution trace are too large for developers to inspect since a trace involves a large number of objects and method calls. To support developers to understand extracted sequence diagrams, it is necessary to remove the less important details of the diagrams. In this paper, we apply a dominance algorithm to a dynamic call graph among objects in order to detect and remove local objects contributing to internal behavior of dominator objects. The case study shows our approach automatically removed about 40 percent of the objects from execution traces on average.4th International Workshop on Program Comprehension through Dynamic Analysis(PCODA'08)co-located with the 15th International Working Conference on Reverse Engineering (WCRE’08)October 16th, 2008 – Antwerp, BelgiumAndy Zaidman, Abdelwahab Hamou-Lhadj, Orla Greevy, David Röthlisberger(editors)刊行年月日は会議開催日を参考にし

Maleku: an evolutionary visual software analytics tool for providing insights into software evolution

Software maintenance is a complex process that requires the understanding and comprehension of software project details. It involves the understanding of the evolution of the software project, hundreds of software components and the relationships among software items in the form of inheritance, interface implementation, coupling and cohesion. Consequently, the aim of evolutionary visual software analytics is to support software project managers and developers during software maintenance. It takes into account the mining of evolutionary data, the subsequent analysis of the results produced by the mining process for producing evolution facts, the use of visualizations supported by interaction techniques and the active participation of users. Hence, this paper proposes an evolutionary visual software analytics tool for the exploration and comparison of project structural, interface implementation and class hierarchy data, and the correlation of structural data with metrics, as well as socio-technical relationships. Its main contribution is a tool that automatically retrieves evolutionary software facts and represent them using a scalable visualization design