A system for graph-based visualization of the evolution of software

Collberg, Christian; Kobourov, Stephen G.; Nagra, Jasvir; Pitts, Jacob; Wampler, Kevin

doi:10.1145/774841.774844

Cited by 92 publications

(32 citation statements)

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“…Gall et al [11] presented a threedimensional visual representation for examining a system's release history. Collberg et al [12] presented a visualization system that extracts evolution information from version control systems and displays it using a temporal graph visualizer. Van Rysselberghe and Demeyer [13] applied a simple visualization technique to recognize relevant changes such as unstable components and coherent entities.…”

Section: Related Workmentioning

confidence: 99%

Summarizing Evolutionary Trajectory by Grouping and Aggregating relevant code changes

Jiang

Peng

Wang

et al. 2015

2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

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The lifecycle of a large-scale software system can undergo many releases. Each release often involves hundreds or thousands of revisions committed by many developers over time. Many code changes are made in a systematic and collaborative way. However, such systematic and collaborative code changes are often undocumented and hidden in the evolution history of a software system. It is desirable to recover commonalities and associations among dispersed code changes in the evolutionary trajectory of a software system. In this paper, we present SETGA (Summarizing Evolutionary Trajectory by Grouping and Aggregation), an approach to summarizing historical commit records as trajectory patterns by grouping and aggregating relevant code changes committed over time. SETGA extracts change operations from a series of commit records from version control systems. It then groups extracted change operations by their common properties from different dimensions such as change operation types, developers and change locations. After that, SETGA aggregates relevant change operation groups by mining various associations among them. The proposed approach has been implemented and applied to three open-source systems. The results show that SETGA can identify various types of trajectory patterns that are useful for software evolution management and quality assurance.

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Section: Related Workmentioning

confidence: 99%

Summarizing Evolutionary Trajectory by Grouping and Aggregating relevant code changes

Jiang

Peng

Wang

et al. 2015

2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

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“…Visualization of software architecture has been also research for years. The tools like SourceViewer3D [16], Gevol [4], EvolutionRadar [9] and StarGate [15] are interesting attempts in visualization. However none of them simultaneously supports aggregation (e.g.…”

Section: Motivation and Related Workmentioning

confidence: 99%

On quick comprehension and assessment of software

Bartoszuk

Dąbrowski

Stencel

et al. 2013

Proceedings of the 14th International Conference on Computer Systems and Technologies

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By an architecture of a software system we mean the fundamental organization of the system embodied in its components, their relationships to one another and to the system's environment. It also encompasses principles governing the system's design and evolution. Architectures of complex systems are obviously complex as well. The goal of our research is to harness this complexity. In this paper we focus on providing software architects with ability to quickly comprehend the complexity and assess the quality of software. The essential tools we use are: (1) a graph-based repository for collecting information on software artefacts, accompanied by (2) tools to perform software intelligence tasks, like analyzing dependencies among those artefacts, calculating their importance, and quality. On top of those tools we implement visualization methods that render the relative importance using size and the quality using colours. By means of such methods a software architect can at glance comprehend and assess the software, He/she can (1) find the starting points to dig into a complex system; (2) judge the cohesion and coupling of system components; and (3) assess the overall quality. We demonstrate this method using selected open-source projects of various sizes and qualities.

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“…storyboards, are effective methods that designers can easily evaluate [8,24,29]. Scalability is achieved by using focus plus context technique which joint with a usersteered clustering algorithm [28].…”

Section: Scenario Analyses -Uml and Use Case Diagrammentioning

confidence: 99%

Emerging convergences of HCI techniques for graphical scalable visualization: Efficient filtration and location transparency of visual transformation

Sim

2011

2011 7th International Conference on Information Technology in Asia

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Human-Computer Interaction (HCI) techniques are important in visualization because a good combination of them can help users to design a good visualization system while optimizing its visualization effects. In order to incorporate different HCI techniques to 'work together' to achieve the synergy effects for optimizing graphical scalable visualization, three of them, i.e. goal, task and scenario analyses, are applied to an XML visualization system 1 which has just been recently developed last year. The order of applying these HCI techniques will be researched upon. The recognition of patterns and models in a visualization system 1 is important because this affects the efficiency of visual queries to be processed by the intended viewer. Singularity of forms for patterns recognition during visualization is important for designing user interfaces. The reason is that when designing visual interfaces to an interactive program, a good visualization system should decide how the visual information should change in response to every action taken by the users.

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A system for graph-based visualization of the evolution of software

Cited by 92 publications

References 0 publications

Summarizing Evolutionary Trajectory by Grouping and Aggregating relevant code changes

Summarizing Evolutionary Trajectory by Grouping and Aggregating relevant code changes

On quick comprehension and assessment of software

Emerging convergences of HCI techniques for graphical scalable visualization: Efficient filtration and location transparency of visual transformation

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